def calculate(self):
# read start and end point
startX = int(self.main.startPointX.text())
startY = int(self.main.startPointY.text())
endX = int(self.main.endPointX.text())
endY = int(self.main.endPointY.text())
# read image data
costLayer = self.rasterLayers[self.main.costSelector.currentIndex()]
cost_array = get_cost_array(costLayer)
# progress bar
progressBar = self.main.progressBar
#self.worker = Worker()
#self.worker.progress.connect(self.main.progressBar.setValue)
#self.worker.start()
# using algorithm
if self.main.AlgorithmSelector.currentIndex() == 0:
map = SPFA(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
elif self.main.AlgorithmSelector.currentIndex() == 1:
map = SLF(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
elif self.main.AlgorithmSelector.currentIndex() == 2:
map = LLL(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
elif self.main.AlgorithmSelector.currentIndex() == 3:
map = SLFandLLL(cost_array, startX, startY, endX, endY,
progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
elif self.main.AlgorithmSelector.currentIndex() == 4:
map = dijkstra(cost_array, startX, startY, endX, endY)
self.showItems(map, costLayer)
progressBar.setValue(0)
elif self.main.AlgorithmSelector.currentIndex() == 5:
map = astar(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
elif self.main.AlgorithmSelector.currentIndex() == 6:
map = SPFA(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
map = SLF(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
map = LLL(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
map = SLFandLLL(cost_array, startX, startY, endX, endY,
progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
map = dijkstra(cost_array, startX, startY, endX, endY)
self.showItems(map, costLayer)
progressBar.setValue(0)
map = astar(cost_array, startX, startY, endX, endY, progressBar)
self.showItems(map, costLayer)
progressBar.setValue(0)
def determineNextMove(player_location, opponentLocation, coins):
"""Return the next direction"""
global route, currentcoin, meta_route, best_weight, best_path, coins_to_search
#the second test prevents the player from going to coins which have been taken by the opponent
if currentcoin == player_location or opponentLocation in coins_to_search:
dists_matrix, routes_matrix = u.update_dists_from_each(
dist_matrix, route_matrix, player_location, mazeMap, coins)
coins_to_search = get_n_shortest(3, coins, player_location,
dist_matrix)
ennemy_dists = algo.dijkstra(mazeMap, opponentLocation)
may_be_lost_coins = []
# Remove from coins_to_search the first coin which is closer to the opponent than to the player
for c in coins_to_search:
if len(coins_to_search) >= 2 and ennemy_dists[1][c] < dists_matrix[
player_location][c]:
may_be_lost_coins.append(c)
if len(may_be_lost_coins) != 0:
coins_to_search.remove(may_be_lost_coins[0])
best_weight = float("inf")
best_path = []
exhaustive(coins_to_search, player_location, [], 0, dist_matrix)
meta_route = [player_location] + best_path
route = u.location_list_to_route(meta_route, route_matrix)
currentcoin = meta_route[1]
return u.direction(player_location, route.pop(0))
def CreatTourSortGraph(graph):
"""
Parameters:
------------
ALGraph or dataframe
Returns:
---------
tour route
list
"""
if utils.graph_type(graph)[0] == "ALGraph":
return
else:
(dfs_visit,
path), dist = algorithms.DFSTraverse(graph,
start=graph.columns.values[0])
i = 0
while i < len(dfs_visit) - 1:
# if is_fin(dfs_visit[:i+2], graph.index):
# return dfs_visit[:i+2]
if dfs_visit[i + 1] not in utils.LocateVex(graph, dfs_visit[i]):
_, templist = algorithms.dijkstra(graph,
start=dfs_visit[i],
end=dfs_visit[i + 1])
for insert_poi in templist:
dfs_visit.insert(i + 1, insert_poi)
i += 1
else:
i += 1
return dfs_visit
def print_min_distance(graph, source, target):
try:
distance, path = dijkstra(graph, source, target)
print('- Min distance between ({},{}) is {} following this path: {}'.
format(source, target, distance, path))
except InvalidPathError:
print('- There is no path between ({},{})'.format(source, target))
def determineNextMove(player_location, opponentLocation, coins):
"""Return the next direction"""
global route, currentcoin, meta_route, best_weight, best_path, coins_to_search, index
if opponentLocation in coins_to_search:
coins_to_search, meta_route, route = change_way(coins, opponentLocation, player_location)[:3]
index = 0
elif currentcoin == player_location:
if len(route) != 0:
old_dist = algo.dijkstra(mazeMap, player_location)[1][meta_route[index+1]]
coins_to_search2, meta_route2, route2, new_dist = change_way(coins, opponentLocation, player_location)
#dist_matrix, route_matrix = u.update_dists_from_each(dists_matrix, routes_matrix, player_location, mazeMap, coins)
#coins_to_search = get_n_shortest(3, coins, player_location, dists_matrix)
#ennemy_dists = algo.dijkstra(mazeMap, opponentLocation)
#for c in coins_to_search:
#if len(coins_to_search) >= 2 and ennemy_dists[1][c] < dists_matrix[player_location][c]:
# coins_to_search.remove(c)
#break
#best_weight = float("inf")
#best_path = []
#exhaustive(coins_to_search, player_location, [], 0, dist_matrix)
#meta_route2 = [player_location] + best_path
#route2 = u.location_list_to_route(meta_route2, route_matrix)
#new_dist = dist_matrix[player_location][meta_route2[1]]
if len(route) == 0 or old_dist - new_dist > 3:
route = route2
meta_route = meta_route2
index = 0
index += 1
currentcoin = meta_route[index]
#api.debug(route)
return u.direction(player_location, route.pop(0))
def determineNextMove(player_location, opponentLocation, coins):
"""Return the next direction"""
global route, currentcoin, meta_route, best_weight, best_path, coins_to_search
#the second test prevents the player from going to coins which have been taken by the opponent
if currentcoin == player_location or opponentLocation in coins_to_search:
dists_matrix, routes_matrix = u.update_dists_from_each(dist_matrix, route_matrix, player_location, mazeMap, coins)
coins_to_search = get_n_shortest(3, coins, player_location, dist_matrix)
ennemy_dists = algo.dijkstra(mazeMap, opponentLocation)
may_be_lost_coins = []
# Remove from coins_to_search the first coin which is closer to the opponent than to the player
for c in coins_to_search:
if len(coins_to_search) >= 2 and ennemy_dists[1][c] < dists_matrix[player_location][c]:
may_be_lost_coins.append(c)
if len(may_be_lost_coins) != 0:
coins_to_search.remove(may_be_lost_coins[0])
best_weight = float("inf")
best_path = []
exhaustive(coins_to_search, player_location, [], 0, dist_matrix)
meta_route = [player_location]+best_path
route = u.location_list_to_route(meta_route, route_matrix)
currentcoin = meta_route[1]
return u.direction(player_location, route.pop(0))
def test_praktikum_5(arg):
"""
Reading and converting the graphs (web/file).
"""
graph_url = 'http://www.hoever.fh-aachen.de/webDateien/mmi/Grafen/Wege1.txt'
#graph_url = 'http://www.hoever.fh-aachen.de/webDateien/mmi/Grafen/G_10_20.txt'
result = convert_edge_list(retrieve_information_web(graph_url))
# input_file = 'graphs/K_test.txt'
# result = convert_edge_list(retrieve_information_file(input_file))
if arg == 'dij':
"""
Tests for Dijkstra-Algorithm
"""
print "=" * 40
print "Dijkstra-Algorithm"
print "=" * 40
try:
dijkstra(result, int(sys.argv[2]))
except:
print 'Usage python tests.py <dij> <source>'
if arg == 'sp':
"""
Tests for Shortest-Path (Source -> Target)
"""
print "=" * 40
print "Shortest-Path (Source -> Target)"
print "=" * 40
try:
dijkstra(result, int(sys.argv[2]), int(sys.argv[3]))
except:
print 'Usage: python tests.py <sp> <start> <target>'
if arg == 'bell':
"""
Tests for Bellman-Ford
"""
print "=" * 40
print "Bellman-Ford"
print "=" * 40
try:
bellman_ford(result, int(sys.argv[2]))
except:
print 'Usage python tests.py <bell> <source>'
def test_beispiel(show: bool):
"""Stellt ein Beispiel anhand eines konstruierten Graphes dar, den die Algorithmen Dijkstra, Floyd-Warshall
und Bellman-Ford einmal ablaufen. Von jedem Algorithmus werden die Ergebnisse ausgegeben.
A-Stern wurde ausgelassen, da die Haversine Distance nicht mit simplen Knoten funktioniert.
"""
graph = nx.MultiDiGraph()
graph.add_nodes_from([1, 2, 3, 4, 5])
graph.add_edge(1, 4, length=10)
graph.add_edge(1, 2, length=5)
graph.add_edge(2, 3, length=3)
graph.add_edge(3, 4, length=1)
graph.add_edge(3, 5, length=8)
graph.add_edge(4, 3, length=1)
if (show):
nx.draw(graph)
plt.show()
print("*** DURCHLAUF TEST_BEISPIEL(): ")
print(""" 10
(1)------->(4)
| /|\
5 | |
| | 1
\|/ |
(2)------->(3)------->(5)
3 8
""")
print(f"===== START Dijkstra")
dist, pred, count = dijkstra(graph, 1)
print(f"= Distanz von Startpunkt zum jeweiligen Key: {dist}".replace(
"{", "").replace("}", ""))
print(f"= Vorheriger Knoten zum jeweiligen Key: {pred}".replace(
"{", "").replace("}", ""))
print(f"===== ENDE Dijkstra")
print(f"===== START Bellman-Ford")
dist, pred, count = bellman_ford(graph, 1)
print(f"= Distanz von Startpunkt zum jeweiligen Key: {dist}".replace(
"{", "").replace("}", ""))
print(f"= Vorheriger Knoten zum jeweiligen Key: {pred}".replace(
"{", "").replace("}", ""))
print(f"===== ENDE Bellman-Ford")
print(f"===== START Floyd-Warshall")
dist, next, count = floyd_warshall(graph)
result_dist = prepare_matrix_for_printing(dist)
result_next = prepare_matrix_for_printing(next)
print("= Distanz von Startpunkt zum jeweiligen Key:")
print(result_dist)
print(
f"= Nächster Knoten auf dem optimalen Pfad von A (Links) Nach B (Oben):"
)
print(result_next)
print(f"===== ENDE Floyd-Warshall")
def update_dists_from_each(dists_matrix, routes_matrix, new_location, maze_map, coins):
routing_table, dists_table = algo.dijkstra(maze_map, new_location)
dists_matrix[new_location] = {}
routes_matrix[new_location] = {}
for loc in coins:
route = u.way_width(routing_table, new_location, loc)
dists_matrix[new_location][loc] = dists_table[loc]
routes_matrix[new_location][loc] = route
dists_matrix[loc][new_location] = dists_table[loc]
routes_matrix[loc][new_location] = [l for l in reversed(route[:-1])] + [new_location]
return dists_matrix, routes_matrix
def dijkstra_function(self):
self.draw_button_function() # this is to be sure that the plotted graph and the graph from memory are same
node1 = self.dijkstra1.get(1.0, 'end-1c') # this take first node
node2 = self.dijkstra2.get(1.0, 'end-1c') # this take second node
node1 = str(node1)
node2 = str(node2)
not_found = False # this for error if one of the nodes in not in the graph
if node1 not in self.G:
# this check if first node is in the graph
self.insert_in_textbox(self.dijkstra_answer, "First node is not in the graph")
self.insert_in_textbox(self.dijkstra_answer2, '')
not_found = True
if node2 not in self.G:
# this check if the second node is in the graph
if node1 in self.G:
self.insert_in_textbox(self.dijkstra_answer, '')
txt = "Second node is not in the graph"
self.insert_in_textbox(self.dijkstra_answer2, txt)
not_found = True
# if first node is not in the graph, this will be displayed in dijkstra_answer
# if second node is not in the graph, this will be displayed in dijkstra_answer2
if not_found:
return
# this take the meeting point and distances between (calculated in algorithm)
meeting_node, distance1, distance2 = algorithms.dijkstra(self.G, node1, node2, self.is_weighted)
# here is the display process
txt = str()
if not meeting_node == '-1':
txt = "One of the optimal meeting points is " + meeting_node + "."
else:
txt = "There is no meeting point."
self.insert_in_textbox(self.dijkstra_answer, txt)
txt = str()
if distance1 < 999999999999999999999:
txt = "Distance from first node to second is " + str(distance1) + "."
else:
txt = "There is no way from first node to second."
if distance2 < 999999999999999999999:
txt = txt + " Distance from second node to first is " + str(distance2) + "."
else:
txt = txt + " There is no way from second node to first."
self.insert_in_textbox(self.dijkstra_answer2, txt)
def update_dists_from_each(dists_matrix, routes_matrix, new_location, maze_map,
coins):
routing_table, dists_table = algo.dijkstra(maze_map, new_location)
dists_matrix[new_location] = {}
routes_matrix[new_location] = {}
for loc in coins:
route = u.way_width(routing_table, new_location, loc)
dists_matrix[new_location][loc] = dists_table[loc]
routes_matrix[new_location][loc] = route
dists_matrix[loc][new_location] = dists_table[loc]
routes_matrix[loc][new_location] = [l for l in reversed(route[:-1])
] + [new_location]
return dists_matrix, routes_matrix
def test_dijkstra():
g1 = nx.Graph()
g1.add_nodes_from([i for i in range(6)])
g1.add_weighted_edges_from([(0, 2, 4), (0, 4, 8), (1, 2, 3), (1, 4, 5),
(1, 3, 6), (2, 5, 12), (3, 5, 9), (4, 5, 1)])
min_paths_dict = a.dijkstra(g1, 0)
new_nodes = {i: (i, j) for i, j in min_paths_dict.items()}
nx.relabel_nodes(g1, new_nodes, copy=False)
pos = nx.spring_layout(g1)
nx.draw(g1, pos=pos, with_labels=True)
labels = {(u, v): g1.get_edge_data(u, v).get('weight')
for (u, v) in g1.edges}
nx.draw_networkx_edge_labels(g1, pos=pos, edge_labels=labels)
plt.show()
def change_way(coins, opponentLocation, player_location):
"""Return the new coin to search, coin sequence, route and the distance from the player to the first coin of the route"""
global best_weight, best_path
dist_matrix, route_matrix = u.update_dists_from_each(dists_matrix, routes_matrix, player_location, mazeMap, coins)
coins_to_search = get_n_shortest(5, coins, player_location, dists_matrix)
ennemy_dists = algo.dijkstra(mazeMap, opponentLocation)
for c in coins_to_search:
if len(coins_to_search) >= 2 and ennemy_dists[1][c] < dists_matrix[player_location][c]:
coins_to_search.remove(c)
break
best_weight = float("inf")
best_path = []
api.debug(coins_to_search)
exhaustive(coins_to_search, player_location, [], 0, dist_matrix)
meta_route = [player_location] + best_path
api.debug(meta_route)
route = u.location_list_to_route(meta_route, route_matrix)
return coins_to_search, meta_route, route, dist_matrix[player_location][meta_route[1]]
def change_way(coins, opponentLocation, player_location):
"""Return the new coin to search, coin sequence, route and the distance from the player to the first coin of the route"""
global best_weight, best_path
dist_matrix, route_matrix = u.update_dists_from_each(
dists_matrix, routes_matrix, player_location, mazeMap, coins)
coins_to_search = get_n_shortest(5, coins, player_location, dists_matrix)
ennemy_dists = algo.dijkstra(mazeMap, opponentLocation)
for c in coins_to_search:
if len(coins_to_search) >= 2 and ennemy_dists[1][c] < dists_matrix[
player_location][c]:
coins_to_search.remove(c)
break
best_weight = float("inf")
best_path = []
api.debug(coins_to_search)
exhaustive(coins_to_search, player_location, [], 0, dist_matrix)
meta_route = [player_location] + best_path
api.debug(meta_route)
route = u.location_list_to_route(meta_route, route_matrix)
return coins_to_search, meta_route, route, dist_matrix[player_location][
meta_route[1]]
def generate_g(file_name, nodes=10000):
#seed = nx.generators.random_graphs.random_regular_graph(4, 80000)
seed = build_graph(nodes, 8)
edges = [ (u, v, data['weight'] * nodes) for (u, v, data) in seed.edges(data=True) ]
g = nx.DiGraph()
for (u, v, w) in edges:
g.add_edge(u,v, weight=w)
s = g.nodes()[0]
cover, distances = dijkstra(g, s)
t = choice(cover.nodes())
reachable = dict((node, True) for node in cover.nodes())
edges= [ (u, v, w) for (u,v,w) in edges if u in reachable and v in
reachable ]
nodes = [ (node, seed.node[node]['coords'][0] * nodes,
seed.node[node]['coords'][1] * nodes) for node in cover.nodes() ]
with open(file_name, 'a') as file:
pickle.dump((nodes, edges, s), file)
def determineNextMove(player_location, opponentLocation, coins):
"""Return the next direction"""
global route, currentcoin, meta_route, best_weight, best_path, coins_to_search, index
if opponentLocation in coins_to_search:
coins_to_search, meta_route, route = change_way(
coins, opponentLocation, player_location)[:3]
index = 0
elif currentcoin == player_location:
if len(route) != 0:
old_dist = algo.dijkstra(mazeMap,
player_location)[1][meta_route[index + 1]]
coins_to_search2, meta_route2, route2, new_dist = change_way(
coins, opponentLocation, player_location)
#dist_matrix, route_matrix = u.update_dists_from_each(dists_matrix, routes_matrix, player_location, mazeMap, coins)
#coins_to_search = get_n_shortest(3, coins, player_location, dists_matrix)
#ennemy_dists = algo.dijkstra(mazeMap, opponentLocation)
#for c in coins_to_search:
#if len(coins_to_search) >= 2 and ennemy_dists[1][c] < dists_matrix[player_location][c]:
# coins_to_search.remove(c)
#break
#best_weight = float("inf")
#best_path = []
#exhaustive(coins_to_search, player_location, [], 0, dist_matrix)
#meta_route2 = [player_location] + best_path
#route2 = u.location_list_to_route(meta_route2, route_matrix)
#new_dist = dist_matrix[player_location][meta_route2[1]]
if len(route) == 0 or old_dist - new_dist > 3:
route = route2
meta_route = meta_route2
index = 0
index += 1
currentcoin = meta_route[index]
#api.debug(route)
return u.direction(player_location, route.pop(0))
def dists_from_each(locations, maze_map):
""" Return the dists and routes from each locations
TODO :
- Cache routes and dists
"""
dists_matrix = {l: {} for l in locations}
routes_matrix = {l: {} for l in locations}
for i in range(len(locations)):
l1 = locations[i]
routing_table, dists_table = algo.dijkstra(maze_map, l1)
for j in range(i + 1, len(locations)):
l2 = locations[j]
route = u.way_width(routing_table, l1, l2)
dists_matrix[l1][l2] = dists_table[l2]
routes_matrix[l1][l2] = route
dists_matrix[l2][l1] = dists_table[l2]
routes_matrix[l2][l1] = [l for l in reversed(route[:-1])] + [l1]
return dists_matrix, routes_matrix
def dists_from_each(locations, maze_map):
""" Return the dists and routes from each locations
TODO :
- Cache routes and dists
"""
dists_matrix = {l: {} for l in locations}
routes_matrix = {l: {} for l in locations}
for i in range(len(locations)):
l1 = locations[i]
routing_table, dists_table = algo.dijkstra(maze_map, l1)
for j in range(i + 1, len(locations)):
l2 = locations[j]
route = u.way_width(routing_table, l1, l2)
dists_matrix[l1][l2] = dists_table[l2]
routes_matrix[l1][l2] = route
dists_matrix[l2][l1] = dists_table[l2]
routes_matrix[l2][l1] = [l for l in reversed(route[:-1])] + [l1]
return dists_matrix, routes_matrix
def determineNextMove(playerLocation, opponentLocation, coins):
global route, currentcoin
if coinsNumber != len(coins):
routingTable = algo.dijkstra(mazeMap, playerLocation)
route = u.way_width(routingTable, playerLocation, coins[0])
return u.direction(playerLocation, route.pop(0))
def main(display, width, rows):
grid = helpers.make_grid(rows, WIDTH)
start_pos = None
end_pos = None
running = True
already_executed = False
generated_walls = False
# game loop
while running:
helpers.draw(display, grid, rows, width, buttons)
# event loop
for event in pygame.event.get():
pos = pygame.mouse.get_pos()
if event.type == pygame.QUIT:
running = False
# process mouse input
if pygame.mouse.get_pressed()[0]: # left mouseclick
# if click is in the bottom of the game screen (buttons)
if pos[1] > WIDTH:
# check each button for a click (needs refactoring)
for button in buttons:
if button.is_clicked(pos):
print("Clicked the button " + button.label)
if button.label == "A*":
if start_pos and end_pos and already_executed is False:
for row in grid:
for cell in row:
cell.update_neighbors(grid)
a_star(
lambda: helpers.draw(
display, grid, rows, width), grid,
start_pos, end_pos)
already_executed = True
elif already_executed is True:
Tk().wm_withdraw()
messagebox.showwarning(
"Invalid state",
"You must clear the board first")
else:
Tk().wm_withdraw()
messagebox.showwarning(
"Invalid state",
"You must set start and end positions")
if button.label == "Clear":
start_pos = None
end_pos = None
already_executed = False
generated_walls = False
grid = helpers.make_grid(rows, WIDTH)
if button.label == "Visited":
for row in grid:
for cell in row:
if cell.is_visited(
) or cell.is_available(
) or cell.is_path():
cell.reset()
already_executed = False
if button.label == "Dijkstra":
if start_pos and end_pos and already_executed is False:
for row in grid:
for cell in row:
cell.update_neighbors(grid)
# dijkstra(lambda: helpers.draw(display, grid,
# rows, width), grid, start_pos, end_pos)
dijkstra(
lambda: helpers.draw(
display, grid, rows, width), grid,
start_pos, end_pos)
already_executed = True
elif already_executed is True:
Tk().wm_withdraw()
messagebox.showwarning(
"Invalid state",
"You must clear the board first")
else:
Tk().wm_withdraw()
messagebox.showwarning(
"Invalid state",
"You must set start and end positions")
if button.label == "Walls" and generated_walls is False:
draw_borders(
lambda: helpers.draw(
display, grid, rows, width), grid,
start_pos, end_pos)
generate_walls(
lambda: helpers.draw(
display, grid, rows, width), grid,
start_pos, end_pos)
generated_walls = True
button.clicked = False
else:
row, col = helpers.get_mouse_pos(pos, rows, WIDTH)
cell = grid[row][col]
if not start_pos and cell != end_pos:
start_pos = cell
start_pos.set_start()
elif not end_pos and cell != start_pos:
end_pos = cell
end_pos.set_end()
elif cell != end_pos and cell != start_pos:
cell.set_barrier()
elif pygame.mouse.get_pressed()[2]: # right mouseclick
row, col = helpers.get_mouse_pos(pos, rows, WIDTH)
cell = grid[row][col]
cell.reset()
if cell == start_pos:
start_pos = None
if cell == end_pos:
end_pos = None
pygame.quit()
def get_route_compare_algs(file_path):
all_node = []
all_node_alone = []
all_edge = []
all_edge_alone = []
all_edge_alone_order = []
one_edge = []
one_edge1 = []
one_edge_order = []
one_node = []
source = []
terminal = []
weight = []
flow_sfc = []
fd = file_path + '/SIMPLE_path.txt'
if os.path.exists(fd):
os.remove(fd)
fd = file_path + '/PDA_path.txt'
if os.path.exists(fd):
os.remove(fd)
k = 0
for line in open(file_path + "/flow_feasible_vnf.txt"):
flow_path = txt_wrap_by("'", "'", line, 0)
#
#print flow_path,flow_path[0]
flow_sfc.append(flow_path)
if k % 3 == 0:
source.append(flow_path[0])
terminal.append(flow_path[len(flow_path) - 2])
weight.append(flow_path[len(flow_path) - 1])
k = k + 1
print len(source), len(flow_sfc), k
flow_number = len(source)
print "flow_number", flow_number
for sr in range(0, flow_number):
if sr % 100 == 0:
print "source is ", sr, source[sr], terminal[sr]
main_path_all = []
one_source_edge = []
one_source_edge_order = []
one_source_node = []
main_path = []
for q in range(0, len(flow_sfc[3 * sr]) - 2):
#print "sfc",flow_sfc[3*sr][q+1]
path = dijkstra(g, str(flow_sfc[3 * sr][q]),
str(flow_sfc[3 * sr][q + 1]))
main_path_seg = path.get('path')
for i in range(0, len(main_path_seg)):
main_path_seg[i] = main_path_seg[i].encode(CODEC)
for i in range(0, len(main_path_seg) - 1):
main_path.append(main_path_seg[i])
if q == len(flow_sfc[3 * sr]) - 3:
main_path.append(main_path_seg[len(main_path_seg) - 1])
#print main_path
for i in range(0, len(main_path)):
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
siwtch1 = int(main_path[f + 1][1])
siwtch2 = int(main_path[f + 2][1])
one_edge_order = main_path[f + 1] + main_path[f + 2]
if len(main_path[f + 1]) == 3:
siwtch1 = siwtch1 * 10 + int(main_path[f + 1][2])
if len(main_path[f + 1]) == 4:
siwtch1 = siwtch1 * 100 + int(main_path[f + 1][2]) * 10 + int(
main_path[f + 1][3])
if len(main_path[f + 2]) == 3:
siwtch2 = siwtch2 * 10 + int(main_path[f + 2][2])
if len(main_path[f + 2]) == 4:
siwtch2 = siwtch2 * 100 + int(main_path[f + 2][2]) * 10 + int(
main_path[f + 2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f + 1] + main_path[f + 2]
one_edge1 = main_path[f + 2] + main_path[f + 1]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
one_edge1 = main_path[f + 1] + main_path[f + 2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
# print all_node_alone,all_edge_alone,all_edge_alone_order
#sleep(600)
one_source_edge_order = []
one_source_node = []
one_source_edge = []
main_path = []
for q in range(0, len(flow_sfc[3 * sr + 1]) - 2):
#print "sfc",flow_sfc[3*sr+1][q+1]
path = dijkstra2(g, str(flow_sfc[3 * sr + 1][q]),
str(flow_sfc[3 * sr + 1][q + 1]), main_path_all)
main_path_seg = path.get('path')
for i in range(0, len(main_path_seg)):
main_path_seg[i] = main_path_seg[i].encode(CODEC)
for i in range(0, len(main_path_seg) - 1):
main_path.append(main_path_seg[i])
if q == len(flow_sfc[3 * sr + 1]) - 3:
main_path.append(main_path_seg[len(main_path_seg) - 1])
#print main_path
for i in range(0, len(main_path)):
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
siwtch1 = int(main_path[f + 1][1])
siwtch2 = int(main_path[f + 2][1])
one_edge_order = main_path[f + 1] + main_path[f + 2]
if len(main_path[f + 1]) == 3:
siwtch1 = siwtch1 * 10 + int(main_path[f + 1][2])
if len(main_path[f + 1]) == 4:
siwtch1 = siwtch1 * 100 + int(main_path[f + 1][2]) * 10 + int(
main_path[f + 1][3])
if len(main_path[f + 2]) == 3:
siwtch2 = siwtch2 * 10 + int(main_path[f + 2][2])
if len(main_path[f + 2]) == 4:
siwtch2 = siwtch2 * 100 + int(main_path[f + 2][2]) * 10 + int(
main_path[f + 2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f + 1] + main_path[f + 2]
one_edge1 = main_path[f + 2] + main_path[f + 1]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
one_edge1 = main_path[f + 1] + main_path[f + 2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
one_source_node = []
one_source_edge = []
one_source_edge_order = []
main_path = []
for q in range(0, len(flow_sfc[3 * sr + 2]) - 2):
#print "sfc",flow_sfc[3*sr+2][q+1]
path = dijkstra3(g, str(flow_sfc[3 * sr + 2][q]),
str(flow_sfc[3 * sr + 2][q + 1]), main_path_all)
main_path_seg = path.get('path')
for i in range(0, len(main_path_seg)):
main_path_seg[i] = main_path_seg[i].encode(CODEC)
for i in range(0, len(main_path_seg) - 1):
main_path.append(main_path_seg[i])
if q == len(flow_sfc[3 * sr + 2]) - 3:
main_path.append(main_path_seg[len(main_path_seg) - 1])
#print main_path
for i in range(0, len(main_path)):
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
siwtch1 = int(main_path[f + 1][1])
siwtch2 = int(main_path[f + 2][1])
one_edge_order = main_path[f + 1] + main_path[f + 2]
if len(main_path[f + 1]) == 3:
siwtch1 = siwtch1 * 10 + int(main_path[f + 1][2])
if len(main_path[f + 1]) == 4:
siwtch1 = siwtch1 * 100 + int(main_path[f + 1][2]) * 10 + int(
main_path[f + 1][3])
if len(main_path[f + 2]) == 3:
siwtch2 = siwtch2 * 10 + int(main_path[f + 2][2])
if len(main_path[f + 2]) == 4:
siwtch2 = siwtch2 * 100 + int(main_path[f + 2][2]) * 10 + int(
main_path[f + 2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f + 1] + main_path[f + 2]
one_edge1 = main_path[f + 2] + main_path[f + 1]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
one_edge1 = main_path[f + 1] + main_path[f + 2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
#print all_node_alone
#print all_edge_alone_order
weight[sr] = int(weight[sr])
for flow_traffic in range(1, 2):
for randome_time in range(0, 1):
for entries in range(31, 32): #300-4200
entries = entries * 10000
ce = 10000
#print entries
for alg in range(0, 10):
if alg == 2: #SIMPLE alg, linke load balancing
used_ce = defaultdict(lambda: None)
used_entries = defaultdict(lambda: None)
for v in all_node:
used_entries[v] = 0
for e in all_edge:
used_ce[e] = 0
lambda1 = 0
max_entries = 0
temp2 = 0
for i in range(0, flow_number):
temp = [[0 for col in range(2)]
for row in range(3)]
for row in range(0, 3):
for col in range(0, 2):
temp[row][col] = 0
for j in range(0, 3):
for n in range(0,
len(all_edge_alone[3 * i + j])):
q = 0
for m in range(
0, len(all_edge_alone[3 * i + j])):
if all_edge_alone[
3 * i +
j][n] == all_edge_alone[3 * i +
j][m]:
q = q + 1
if temp[j][1] < (used_ce[all_edge_alone[
3 * i + j][n]] + q *
weight[i]) / float(ce):
temp[j][1] = (
used_ce[all_edge_alone[3 * i +
j][n]] +
q * weight[i]) / float(ce)
temp1 = 1000000
k = 0 #Indicate which of several feasible paths is selected
for j in range(0, 3):
if temp[j][
1] < temp1: #Select the feasible path that meets the flow table constraints and has the lightest load.
k = j
temp1 = temp[j][1]
for n in range(
0, len(all_edge_alone[3 * i + k])
): #Select one of the feasible paths (Article k), and use link capacity and flow entries.
used_ce[all_edge_alone[3 * i + k]
[n]] = used_ce[all_edge_alone[
3 * i + k][n]] + weight[i]
for n in range(0, len(all_node_alone[3 * i + k])):
used_entries[all_node_alone[
3 * i + k][n]] = used_entries[
all_node_alone[3 * i + k][n]] + 1
alg2_choosed_path = []
alg2_choosed_path.append(source[i])
for j in range(0, len(all_node_alone[3 * i + k])):
alg2_choosed_path.append(all_node_alone[3 * i +
k][j])
alg2_choosed_path.append(terminal[i])
alg2_choosed_path.append(weight[i])
fd = open(file_path + '/SIMPLE_path.txt', 'a')
fd.write(str(alg2_choosed_path) + '\n')
fd.close()
alg2_entries = {}
for j in used_entries:
if 's' in str(j):
alg2_entries[j] = used_entries[j]
if max_entries < used_entries[j]:
max_entries = used_entries[j]
p1 = file_path + "/SIMPLE_entries.json" #rounding
fd = open(p1, 'w')
fd.write(json.dumps(alg2_entries, indent=1))
fd.close()
p1 = file_path + "/SIMPLE_ce.json" #rounding
p2 = file_path + "/SIMPLE_NF_load.json" # rounding
fd1 = open(p1, 'w')
fd2 = open(p2, 'w')
alg2_ce_link = {}
alg2_ce_middlebox = {}
for e in all_edge:
isMark = 0
#Link load and midllebox load
for key in capacity:
if key in e:
alg2_ce_middlebox[key] = float(
used_ce[e]
) / 2 #eg, path: s4-F2-s4. ce(F2s4)= double, but load(F2) = single
isMark = 1
if isMark == 0:
alg2_ce_link[e] = float(used_ce[e]) / float(ce)
fd1.write(json.dumps(alg2_ce_link, indent=1))
fd1.close()
fd2.write(json.dumps(alg2_ce_middlebox, indent=1))
fd2.close()
lambda1 = 0
for j in alg2_ce_link:
if lambda1 < alg2_ce_link[j]:
lambda1 = alg2_ce_link[j]
SIMPLE_max_NF = 0
for j in alg2_ce_middlebox:
if SIMPLE_max_NF < alg2_ce_middlebox[j]:
SIMPLE_max_NF = alg2_ce_middlebox[j]
print "SIMPLE", lambda1, max_entries
p1 = file_path + "/SIMPLE_lambda.json"
fd = open(p1, 'w')
fd.write(json.dumps(lambda1))
fd.close()
p1 = file_path + "/SIMPLE_max_entries.json"
fd = open(p1, 'w')
fd.write(json.dumps(max_entries))
fd.close()
p1 = file_path + "/SIMPLE_max_NF.json"
fd = open(p1, 'w')
fd.write(json.dumps(SIMPLE_max_NF))
fd.close()
if alg == 3: #PDA alg
used_ce = defaultdict(lambda: None)
used_entries = defaultdict(lambda: None)
for v in all_node:
used_entries[v] = 0
for e in all_edge:
used_ce[e] = 0
lambda1 = 0
max_entries = 0
temp2 = 0
for i in range(0, flow_number):
temp = [[0 for col in range(2)]
for row in range(3)]
for row in range(0, 3):
for col in range(0, 2):
temp[row][col] = 0
for j in range(0, 3):
for n in range(0,
len(all_node_alone[3 * i + j])):
q = 0
for m in range(
0, len(all_node_alone[3 * i + j])):
if all_node_alone[
3 * i +
j][n] == all_node_alone[3 * i +
j][m]:
q = q + 1
if temp[j][1] < used_entries[
all_node_alone[3 * i + j][n]] + q:
temp[j][1] = used_entries[
all_node_alone[3 * i + j][n]] + q
temp1 = 10000000
k = 0 #Indicate which of several feasible paths is selected
for j in range(0, 3):
if temp[j][
1] < temp1: #Select the feasible path that meets the flow table constraints and has the lightest load.
k = j
temp1 = temp[j][1]
for n in range(
0, len(all_edge_alone[3 * i + k])
): #Select one of the feasible paths (Article k), and use link capacity and flow entries.
used_ce[all_edge_alone[3 * i + k]
[n]] = used_ce[all_edge_alone[
3 * i + k][n]] + weight[i]
#if used_ce[all_edge_alone[3*i+k][n]]/float(ce) > lambda1:
#lambda1 = used_ce[all_edge_alone[3*i+k][n]]/float(ce) #Record the largest lambda
for n in range(0, len(all_node_alone[3 * i + k])):
used_entries[all_node_alone[
3 * i + k][n]] = used_entries[
all_node_alone[3 * i + k][n]] + 1
alg3_choosed_path = []
alg3_choosed_path.append(source[i])
for j in range(0, len(all_node_alone[3 * i + k])):
alg3_choosed_path.append(all_node_alone[3 * i +
k][j])
alg3_choosed_path.append(terminal[i])
alg3_choosed_path.append(weight[i])
fd = open(file_path + '/PDA_path.txt', 'a')
fd.write(str(alg3_choosed_path) + '\n')
fd.close()
print "PDA_used_ce", used_ce["s3F3"], used_ce[
"F3s3"], used_ce["s1s3"], used_ce["s3s1"], all_edge
alg3_entries = {}
for j in used_entries:
if 's' in str(j):
alg3_entries[j] = used_entries[j]
if max_entries < used_entries[j]:
max_entries = used_entries[j]
p1 = file_path + "/PDA_entries.json" #rounding
fd = open(p1, 'w')
fd.write(json.dumps(alg3_entries, indent=1))
fd.close()
p1 = file_path + "/PDA_ce.json" #rounding
p2 = file_path + "/PDA_NF_load.json" # rounding
fd1 = open(p1, 'w')
fd2 = open(p2, 'w')
alg3_ce_link = {}
alg3_ce_middlebox = {}
for e in all_edge:
isMark = 0
#Link load and midllebox load
for key in capacity:
if key in e:
alg3_ce_middlebox[key] = float(
used_ce[e]) / 2
isMark = 1
if isMark == 0:
alg3_ce_link[e] = float(used_ce[e]) / float(ce)
fd1.write(json.dumps(alg3_ce_link, indent=1))
fd1.close()
fd2.write(json.dumps(alg3_ce_middlebox, indent=1))
fd2.close()
lambda1 = 0
for j in alg3_ce_link:
if lambda1 < alg3_ce_link[j]:
lambda1 = alg3_ce_link[j]
PDA_max_NF = 0
for j in alg3_ce_middlebox:
if PDA_max_NF < alg3_ce_middlebox[j]:
PDA_max_NF = alg3_ce_middlebox[j]
print "PDA", lambda1, max_entries
p1 = file_path + "/PDA_lambda.json"
fd = open(p1, 'w')
fd.write(json.dumps(lambda1))
fd.close()
p1 = file_path + "/PDA_max_entries.json"
fd = open(p1, 'w')
fd.write(json.dumps(max_entries))
fd.close()
p1 = file_path + "/PDA_max_NF.json"
fd = open(p1, 'w')
fd.write(json.dumps(PDA_max_NF))
fd.close()
print "Compare_algs Finished"
if (node.position_x, node.position_y) != grid.start_node and (
node.position_x, node.position_y) != grid.end_node:
if node.visited:
draw_node(node.position_x, node.position_y, yellow)
if node.obstacle:
draw_node(node.position_x, node.position_y, dark_grey)
for node in old_visited_list:
if node not in visited_list and not node.obstacle:
draw_node(node.position_x, node.position_y, white)
if run_a_star:
visited_list, old_visited_list, total_cost, total_time = algorithms.a_star(
nodes_list, grid.start_node, grid.end_node, visited_list)
elif run_dijkstra:
visited_list, old_visited_list, total_cost, total_time = algorithms.dijkstra(
nodes_list, grid.start_node, grid.end_node, visited_list)
if run_a_star or run_dijkstra:
start_node = nodes_list[grid.start_node[0]][grid.start_node[1]]
end_node = nodes_list[grid.end_node[0]][grid.end_node[1]]
path = end_node
path_dist = 0
path_list.clear()
while path.parent is not None:
if path.position_x == start_node.position_x and path.position_y == start_node.position_y:
break
path_dist = path_dist + path.parent_dist
path_list.append(path.parent)
path = path.parent
# Draw path
for node in path_list:
def initializationCode(mazeWidth, mazeHeight, mazeMap, timeAllowed,
playerLocation, opponentLocation, coins):
global route
routingTable = algo.dijkstra(mazeMap, playerLocation)
route = u.way_width(routingTable, playerLocation, (0, mazeWidth - 1))
def initializationCode (mazeWidth, mazeHeight, mazeMap, timeAllowed, playerLocation, opponentLocation, coins) :
global route
routingTable = algo.dijkstra(mazeMap, playerLocation)
route = u.way_width(routingTable, playerLocation, (0, mazeWidth - 1))
def test_regular(self):
with open(os.path.join(base_path, 'data/regular.json')) as graph_file:
graph = Graph(graph_file)
distance, path = dijkstra(graph, "1", "2")
self.assertEqual(path, ['1', '3', '4', '5', '2'])
self.assertEqual(distance, 5)
def gen_data(number_of_flow, net, start_node):
all_node = [] #所有节点 []
all_node_alone = [] #每个路径的所有节点 [[][]]
all_edge = [] #所有边 []
all_edge_alone = [] #每个路径的所有边 [[][]]
source = []
terminal = []
source_random = []
terminal_random = []
one_edge = []
one_node = []
source_tmp = []
source_number = len(start_node)
for i in range(0, source_number - 1):
source_tmp.extend([i for jj in range(0, source_number - 1 - i)])
#0...0 1...1 2...2
terminal_tmp = []
for i in range(0, source_number - 1):
terminal_tmp.extend(range(source_number - 1, i, -1))
#128...1 128...2 128...3
random.shuffle(source_tmp)
random.shuffle(terminal_tmp)
# print source_tmp
# print terminal_tmp
# exit()
count = 0
source_random = []
terminal_random = []
while count < number_of_flow:
s = random.choice(source_tmp)
d = random.choice(terminal_tmp)
while s == d:
s = random.choice(source_tmp)
d = random.choice(terminal_tmp)
source_random.append(s) #源节点的索引
terminal_random.append(d) #目的节点的索引
count += 1
source = [
start_node[source_random[i]] for i in range(0, len(source_random))
] #6000
terminal = [
start_node[terminal_random[i]] for i in range(0, len(terminal_random))
] #6000
number_of_bigflow = len(source_random) / 4
number_of_smallflow = len(source_random) - number_of_bigflow
for sr in range(0, len(source_random)):
main_path_all = []
one_source_edge = []
one_source_node = []
path = dijkstra(g, source[sr], terminal[sr])
main_path = path.get('path')
#每条流的路径
for i in range(0, len(main_path)):
main_path[i] = main_path[i].encode(CODEC)
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
switch1 = toInt(main_path[f + 1])
switch2 = toInt(main_path[f + 2])
if switch1 < switch2:
one_edge = main_path[f + 1] + main_path[f + 2]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
if one_edge not in all_edge:
all_edge.append(one_edge)
one_source_edge.append(one_edge)
all_edge_alone.append(one_source_edge)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
#path2
one_source_edge = []
one_source_node = []
path = dijkstra2(g, source[sr], terminal[sr], main_path_all)
main_path = path.get('path')
# 每条流的路径
for i in range(0, len(main_path)):
main_path[i] = main_path[i].encode(CODEC)
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
switch1 = toInt(main_path[f + 1])
switch2 = toInt(main_path[f + 2])
if switch1 < switch2:
one_edge = main_path[f + 1] + main_path[f + 2]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
if one_edge not in all_edge:
all_edge.append(one_edge)
one_source_edge.append(one_edge)
all_edge_alone.append(one_source_edge)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
#path3
one_source_edge = []
one_source_node = []
path = dijkstra3(g, source[sr], terminal[sr], main_path_all)
main_path = path.get('path')
# 每条流的路径
for i in range(0, len(main_path)):
main_path[i] = main_path[i].encode(CODEC)
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
switch1 = toInt(main_path[f + 1])
switch2 = toInt(main_path[f + 2])
if switch1 < switch2:
one_edge = main_path[f + 1] + main_path[f + 2]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
if one_edge not in all_edge:
all_edge.append(one_edge)
one_source_edge.append(one_edge)
all_edge_alone.append(one_source_edge)
#print all_edge_alone
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
#print all_node_alone
# print main_path_all
# print all_edge
# print all_node
#all_node 所有出现的节点 all_edge 所有出现的边 all_node_alone 一个list中为一条路径中出现的节点 all_edge_alone 一个list中为一条路径中出现的边
pickle.dump(
all_node_alone,
open(
"./paper_data2/all_node_alone" + "_" + str(number_of_flow) +
".dat", "wb"), True)
pickle.dump(
all_edge_alone,
open(
"./paper_data2/all_edge_alone" + "_" + str(number_of_flow) +
".dat", "wb"), True)
pickle.dump(
source_random,
open(
"./paper_data2/source_random" + "_" + str(number_of_flow) + ".dat",
"wb"), True)
pickle.dump(
terminal_random,
open(
"./paper_data2/terminal_random" + "_" + str(number_of_flow) +
".dat", "wb"), True)
pickle.dump(
all_node,
open("./paper_data2/all_node" + "_" + str(number_of_flow) + ".dat",
"wb"), True)
pickle.dump(
all_edge,
open("./paper_data2/all_edge" + "_" + str(number_of_flow) + ".dat",
"wb"), True)
if node is False:
continue
v = node
way = []
while v != -1:
way.append(v)
v = prev[v]
last = way[-1]
s = 'd={}: ({})'.format(dist[node], last + 1)
for v in reversed(way[:-1]):
s += '-{}->({})'.format(int(g_mat[last][v]), v + 1)
last = v
print s
TASK1_START = 0
print '-' * 35 + '\ntask1 - shortest ways from ({})\n'.format(TASK1_START +
1) + '-' * 35
g_list, g_mat = read_graph_list('task1.in')
dist, prev, table = dijkstra(g_list, TASK1_START)
user_interaction(prev, dist, g_mat)
write_debug_table('task1.out.md', table)
print '\n' + '-' * 35 + '\ntask2\n' + '-' * 35
os.remove('task2.out.md')
g_mat = read_graph_matrix('task2.in')
dist, path = floyd(g_mat)
vnf.append(I)
for i in range(0,10):
P="P"+str(i+1)
vnf.append(P)
for i in range(0,10):
D="D"+str(i+1)
vnf.append(D)
for i in range(0,10):
W="W"+str(i+1)
vnf.append(W)
times = 0
for i in switch:
print i
for j in vnf:
#print j
path = dijkstra(g, i, j)
main_path = path.get('path')
main_cost = path.get('cost')
file.write(str(main_path) + '\n')
times +=1
#print (main_path)
#sleep(30)
for k in host:
path = dijkstra(g,i,k)
main_path = path.get('path')
#for i in range(0,len(main_path)):
# main_path[i] = main_path[i].encode(CODEC)
# print "main_path",main_path[i]
file.write(str(main_path) + '\n')
times += 1
print times,"Finished"
def determineNextMove(playerLocation, opponentLocation, coins):
global route, currentcoin
if coinsNumber != len(coins):
routingTable = algo.dijkstra(mazeMap, playerLocation)
route = u.way_width(routingTable, playerLocation, coins[0])
return u.direction(playerLocation, route.pop(0))
for i in range(0, len(terminal_random)):
terminal.append(start_node[int(terminal_random[i])])
number_of_bigflow = 3980
number_of_smallflow = len(
source_random
) - number_of_bigflow #the number of elephant flow and mice flow, they obey 2-8 distribute
#print"start SR" ,weight
for sr in range(0, len(source_random)):
if sr % 1000 == 0:
print "source is ", sr
main_path_all = []
one_source_edge = []
one_source_node = []
path = dijkstra(g, source[sr], terminal[sr])
main_path = path.get('path')
for i in range(0, len(main_path)):
main_path[i] = main_path[i].encode(CODEC)
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
siwtch1 = int(main_path[f + 1][1])
siwtch2 = int(main_path[f + 2][1])
if len(main_path[f + 1]) == 3:
siwtch1 = siwtch1 * 10 + int(main_path[f + 1][2])
if len(main_path[f + 1]) == 4:
siwtch1 = siwtch1 * 100 + int(main_path[f + 1][2]) * 10 + int(
main_path[f + 1][3])
if len(main_path[f + 2]) == 3:
siwtch2 = siwtch2 * 10 + int(main_path[f + 2][2])
if len(main_path[f + 2]) == 4:
def get_route_alg1(file_path):
all_node = []
all_node_alone = []
all_edge = []
all_edge_alone = []
all_edge_alone_order = []
one_edge = []
one_edge1 = []
one_edge_order = []
one_node = []
source = []
terminal = []
weight = []
fd = file_path + '/alg1_path_segment.txt'
if os.path.exists(fd):
os.remove(fd)
fd = file_path + '/alg2_path_segment.txt'
if os.path.exists(fd):
os.remove(fd)
fd = file_path + '/alg1_path.txt'
if os.path.exists(fd):
os.remove(fd)
fd = file_path + '/alg2_path.txt'
if os.path.exists(fd):
os.remove(fd)
fd = file_path + '/flows.txt'
if os.path.exists(fd):
os.remove(fd)
fd = file_path + '/paths.txt'
if os.path.exists(fd):
os.remove(fd)
for line in open(file_path + "/flow_vnf.txt"):
flow_path = txt_wrap_by("'", "'", line, 0)
#print flow_path,flow_path[0]
for i in range(0, len(flow_path) - 2):
#print flow_path[i],flow_path[i+1]
source.append(flow_path[i])
terminal.append(flow_path[i + 1])
weight.append(flow_path[len(flow_path) - 1])
# The above is to randomly generate the stream and the stream bandwidth, that is, generate soure[], terminal[], weight[], as the input of the next part of the code routing.
flow_number = len(source)
print "flow_number", flow_number
for sr in range(0, flow_number):
if sr % 1000 == 0:
print "source is ", sr, source[sr], terminal[sr]
main_path_all = []
one_source_edge = []
one_source_edge_order = []
one_source_node = []
path = dijkstra(g, source[sr], terminal[sr])
main_path = path.get('path')
for i in range(0, len(main_path)):
main_path[i] = main_path[i].encode(CODEC)
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
siwtch1 = int(main_path[f + 1][1])
siwtch2 = int(main_path[f + 2][1])
one_edge_order = main_path[f + 1] + main_path[f + 2]
if len(main_path[f + 1]) == 3:
siwtch1 = siwtch1 * 10 + int(main_path[f + 1][2])
if len(main_path[f + 1]) == 4:
siwtch1 = siwtch1 * 100 + int(main_path[f + 1][2]) * 10 + int(
main_path[f + 1][3])
if len(main_path[f + 2]) == 3:
siwtch2 = siwtch2 * 10 + int(main_path[f + 2][2])
if len(main_path[f + 2]) == 4:
siwtch2 = siwtch2 * 100 + int(main_path[f + 2][2]) * 10 + int(
main_path[f + 2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f + 1] + main_path[f + 2]
one_edge1 = main_path[f + 2] + main_path[f + 1]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
one_edge1 = main_path[f + 1] + main_path[f + 2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
one_source_edge_order = []
one_source_node = []
one_source_edge = []
path = dijkstra2(g, source[sr], terminal[sr], main_path_all)
main_path = path.get('path')
for i in range(0, len(main_path)):
main_path[i] = main_path[i].encode(CODEC)
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
siwtch1 = int(main_path[f + 1][1])
siwtch2 = int(main_path[f + 2][1])
one_edge_order = main_path[f + 1] + main_path[f + 2]
if len(main_path[f + 1]) == 3:
siwtch1 = siwtch1 * 10 + int(main_path[f + 1][2])
if len(main_path[f + 1]) == 4:
siwtch1 = siwtch1 * 100 + int(main_path[f + 1][2]) * 10 + int(
main_path[f + 1][3])
if len(main_path[f + 2]) == 3:
siwtch2 = siwtch2 * 10 + int(main_path[f + 2][2])
if len(main_path[f + 2]) == 4:
siwtch2 = siwtch2 * 100 + int(main_path[f + 2][2]) * 10 + int(
main_path[f + 2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f + 1] + main_path[f + 2]
one_edge1 = main_path[f + 2] + main_path[f + 1]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
one_edge1 = main_path[f + 1] + main_path[f + 2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
one_source_node = []
one_source_edge = []
one_source_edge_order = []
path = dijkstra3(g, source[sr], terminal[sr], main_path_all)
main_path = path.get('path')
for i in range(0, len(main_path)):
main_path[i] = main_path[i].encode(CODEC)
main_path_all.append(main_path[i])
for f in range(0, len(main_path) - 3):
siwtch1 = int(main_path[f + 1][1])
siwtch2 = int(main_path[f + 2][1])
one_edge_order = main_path[f + 1] + main_path[f + 2]
if len(main_path[f + 1]) == 3:
siwtch1 = siwtch1 * 10 + int(main_path[f + 1][2])
if len(main_path[f + 1]) == 4:
siwtch1 = siwtch1 * 100 + int(main_path[f + 1][2]) * 10 + int(
main_path[f + 1][3])
if len(main_path[f + 2]) == 3:
siwtch2 = siwtch2 * 10 + int(main_path[f + 2][2])
if len(main_path[f + 2]) == 4:
siwtch2 = siwtch2 * 100 + int(main_path[f + 2][2]) * 10 + int(
main_path[f + 2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f + 1] + main_path[f + 2]
one_edge1 = main_path[f + 2] + main_path[f + 1]
else:
one_edge = main_path[f + 2] + main_path[f + 1]
one_edge1 = main_path[f + 1] + main_path[f + 2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0, len(main_path) - 2):
one_node = main_path[f + 1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
weight[sr] = int(weight[sr])
for flow_traffic in range(1, 2):
alg0 = 0
alg1 = 0
alg2 = 0
alg3 = 0
for randome_time in range(0, 1):
for entries in range(31, 32): #300-4200
entries = entries * 10000
ce = 10000
#print entries
for alg in range(0, 1):
if alg == 0:
x_e = defaultdict(lambda: (defaultdict(lambda: (
defaultdict(lambda: None)))))
x_v = defaultdict(lambda: (defaultdict(lambda: (
defaultdict(lambda: None)))))
x = [
[0 for col in range(3)]
for row in range(flow_number)
] #3 is the number of path that each flow can choose
for i in range(0, flow_number):
for j in range(
0, 3
): #3 is the number of path that each flow can choose
x[i][j] = "x"
if flow_number < 100000:
if i < 10:
x[i][j] = x[i][j] + "0000"
elif i < 100:
x[i][j] = x[i][j] + "000"
elif i < 1000:
x[i][j] = x[i][j] + "00"
elif i < 10000:
x[i][j] = x[i][j] + "0"
x[i][j] = x[i][j] + str(i) + str(j)
z = []
for i in range(0, flow_number):
z.append("z" + str(i))
temp = []
for i in range(0, flow_number):
for j in range(
0, 3
): #3 si the number of path that each flow can choose
temp.append(x[i][j])
for i in range(0, flow_number):
temp.append(z[i])
prob = LpProblem('lptest', LpMinimize)
r = LpVariable('r', lowBound=0)
xx = LpVariable.dicts("", temp, lowBound=0, upBound=1)
prob += r
for i in range(0, flow_number):
prob += lpSum([xx[j] for j in x[i]]) == xx[z[
i]] #that means, x[i][0]+x[i][1]....+x[i][len(x[i])-1] = 1
prob += xx[z[i]] == 1
print "len(all_edge_alone)", len(all_edge_alone)
for i in range(0, len(all_edge_alone)):
for j in range(
0, len(all_edge_alone[i])
): #for example, all_edge_alone[i][j] = v1v2
length_x_e = len(x_e[all_edge_alone[i][j]])
#print "length_x_e",length_x_e,all_edge_alone[i],all_edge_alone[i][j],i,j
x_e[all_edge_alone[i][j]][length_x_e][0] = x[
i / 3][i % 3]
x_e[all_edge_alone[i]
[j]][length_x_e][1] = weight[i / 3]
print "222"
for h in all_edge:
prob += lpSum(x_e[h][i][1] * xx[x_e[h][i][0]]
for i in x_e[h]) <= ce * r
for i in range(0, len(all_node_alone)):
for j in range(0, len(all_node_alone[i])):
length_x_v = len(x_v[all_node_alone[i][j]])
if i % 3 == 0:
x_v[all_node_alone[i][j]][length_x_v][
1] = 0 #choose dijstra path do not need extra entries
x_v[all_node_alone[i]
[j]][length_x_v][0] = x[i / 3][i % 3]
else:
x_v[all_node_alone[i]
[j]][length_x_v][0] = x[i / 3][i % 3]
if j == len(all_node_alone[i]) - 1:
x_v[all_node_alone[i][j]][length_x_v][
1] = 0 #the last hop do not need extra entries
else:
x_v[all_node_alone[i]
[j]][length_x_v][1] = 1
print "333"
for v in all_node:
prob += lpSum(x_v[v][i][1] * xx[x_v[v][i][0]]
for i in x_v[v]) <= entries
GLPK().solve(prob)
print 'objective_sr =', value(prob.objective)
p1 = file_path + "/alg0.json"
fd = open(p1, 'w')
fd.write(json.dumps(value(prob.objective)))
fd.close()
i = 0
j = 0
l = 0
for v in prob.variables():
l = l + 1
if l < flow_number * 3 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 2:
j = j + 1
else:
i = i + 1
j = 0
lambda1 = 0
used_ce = defaultdict(lambda: None)
for e in all_edge:
used_ce[e] = 0
flows_add = {}
for i in range(0, flow_number):
k = 0
choose = 0
choosed_path = []
for j in range(0, 3):
if x[i][j] >= k:
choose = j
k = x[i][j]
for n in range(0,
len(all_edge_alone[3 * i +
choose])):
used_ce[all_edge_alone[3 * i + choose]
[n]] = used_ce[all_edge_alone[
3 * i + choose][n]] + weight[i]
if used_ce[all_edge_alone[3 * i + choose]
[n]] / float(ce) > lambda1:
lambda1 = used_ce[all_edge_alone[
3 * i + choose][n]] / float(ce)
choosed_path.append(source[i])
for j in range(0,
len(all_node_alone[3 * i +
choose])):
choosed_path.append(all_node_alone[3 * i +
choose][j])
choosed_path.append(terminal[i])
choosed_path.append(str(weight[i]))
fd = open(file_path + '/alg1_path_segment.txt',
'a')
fd.write(str(choosed_path) + '\n')
fd.close()
num_add_flow = 0
for key in range(
0,
len(all_edge_alone_order[3 * i + choose])):
if all_edge_alone_order[3 * i + choose][
key] not in all_edge_alone_order[3 *
i]:
#['v2v9', 'v9v7', 'v7v1']->['', '2', '9']['', '9', '7']['', '7', '1']
add_flow_key = str(all_edge_alone_order[
3 * i + choose][key]).split('s')
for num_i in range(0, 3):
add_flow_key[num_i] = 's' + str(
add_flow_key[num_i])
#print add_flow_key[1]
#If the node is not in the dictionary, vi=1, if the dictionary is in the dictionary, flows_add[vi] = flows_add[vi]+1
if add_flow_key[1] not in flows_add:
flows_add[add_flow_key[1]] = 1
else:
flows_add[add_flow_key[1]] = flows_add[
add_flow_key[1]] + 1
#print add_flow_key
#print "-------------->",all_node
for key_all in all_node:
if key_all not in flows_add:
flows_add[key_all] = 0
p11 = file_path + "/alg1_entries.json" # rounding
fd = open(p11, 'w')
fd.write(json.dumps(flows_add, indent=1))
fd.close()
alg1_max_entries = 0
for j in flows_add:
if alg1_max_entries < flows_add[j]:
alg1_max_entries = flows_add[j]
p11 = file_path + "/alg1_max_entries.json" # rounding
fd = open(p11, 'w')
fd.write(json.dumps(alg1_max_entries))
fd.close()
file_object = open(file_path +
'/alg1_path_segment.txt')
try:
data = file_object.read()
finally:
file_object.close()
print "data", data
data = data.replace("]", "],")
data_len = len(data) - 2
data = '[' + data[:data_len] + ']'
data_list = list(eval(data))
print "data_list", data_list, len(data_list)
stack = []
new_path = []
for i in range(0, len(data_list)):
if len(stack) == 0:
stack.append(data_list[i])
else:
if 'h' not in data_list[i][len(data_list[i]) -
2]:
stack.append(data_list[i])
else:
#If the last host is found, merge this link
this_path = []
for len_stack in range(0, len(stack)):
a = stack.pop()
this_path.append(a)
one_path = []
#print this_path
for t in range(0, len(this_path)):
index = len(this_path) - t - 1
#If it is the last list of this path, take the first four values
if index == (len(this_path) - 1):
for w in range(
0,
(len(this_path[index]) - 1)):
one_path.append(
this_path[index][w])
else:
for w in range(
1,
(len(this_path[index]) - 1)):
one_path.append(
this_path[index][w])
for w in range(1, len(data_list[i])):
one_path.append(data_list[i][w])
print "one_path", one_path
fd = open(file_path + '/alg1_path.txt',
'a')
fd.write(str(one_path) + '\n')
fd.close()
p1 = file_path + "/alg1_ce.json" #rounding
fd = open(p1, 'w')
alg1_ce = {}
for e in all_edge:
alg1_ce[e] = float(used_ce[e]) / float(ce)
fd.write(json.dumps(alg1_ce, indent=1))
fd.close()
print lambda1
p1 = file_path + "/alg1_lambda.json" #rounding
fd = open(p1, 'w')
fd.write(json.dumps(lambda1))
fd.close()
if alg == 2: #heuristic algorithm ,ospf need entries
used_ce = defaultdict(lambda: None)
used_entries = defaultdict(lambda: None)
for v in all_node:
used_entries[v] = 0
for e in all_edge:
used_ce[e] = 0
lambda1 = 0
temp2 = 0
for i in range(0, flow_number):
temp = [[0 for col in range(2)]
for row in range(3)]
for row in range(0, 3):
for col in range(0, 2):
temp[row][col] = 0
for j in range(0, 3):
for n in range(0,
len(all_node_alone[3 * i + j])):
if used_entries[all_node_alone[3 * i + j]
[n]] + 1 > entries * 10000:
temp[j][0] = 1
for n in range(0,
len(all_edge_alone[3 * i + j])):
if temp[j][1] < (used_ce[all_edge_alone[
3 * i + j][n]] +
weight[i]) / float(ce):
temp[j][1] = (used_ce[all_edge_alone[
3 * i + j][n]] +
weight[i]) / float(ce)
temp1 = 10000
k = 0 #Indicate which of several feasible paths is selected
for j in range(0, 3):
if temp[j][0] != 1:
if temp[j][
1] < temp1: #Select the feasible path that meets the flow table constraints and has the lightest load.
k = j
temp1 = temp[j][1]
for n in range(
0, len(all_edge_alone[3 * i + k])
): #Select one of the feasible paths (Article k), and use link capacity and flow entries.
used_ce[all_edge_alone[3 * i + k]
[n]] = used_ce[all_edge_alone[
3 * i + k][n]] + weight[i]
if used_ce[all_edge_alone[3 * i + k]
[n]] / float(ce) > lambda1:
lambda1 = used_ce[
all_edge_alone[3 * i + k][n]] / float(
ce) #Record the largest lambda
for n in range(0, len(all_node_alone[3 * i + k])):
used_entries[all_node_alone[
3 * i + k][n]] = used_entries[
all_node_alone[3 * i + k][n]] + 1
#print lambda1,all_edge_alone[3*i+k]
alg2_choosed_path = []
alg2_choosed_path.append(source[i])
for j in range(0, len(all_node_alone[3 * i + k])):
alg2_choosed_path.append(all_node_alone[3 * i +
k][j])
alg2_choosed_path.append(terminal[i])
alg2_choosed_path.append(weight[i])
fd = open(file_path + '/alg2_path_segment.txt',
'a')
fd.write(str(alg2_choosed_path) + '\n')
fd.close()
file_object = open(file_path +
'/alg2_path_segment.txt')
try:
data = file_object.read()
finally:
file_object.close()
data = data.replace("]", "],")
data_len = len(data) - 2
data = '[' + data[:data_len] + ']'
data_list = list(eval(data))
print data_list
stack = []
new_path = []
for i in range(0, len(data_list)):
if len(stack) == 0:
stack.append(data_list[i])
else:
if 'h' not in data_list[i][len(data_list[i]) -
2]:
stack.append(data_list[i])
else:
this_path = []
for len_stack in range(0, len(stack)):
a = stack.pop()
this_path.append(a)
one_path = []
print this_path
for t in range(0, len(this_path)):
index = len(this_path) - t - 1
if index == (len(this_path) - 1):
for w in range(
0,
(len(this_path[index]) - 1)):
one_path.append(
this_path[index][w])
else:
for w in range(
1,
(len(this_path[index]) - 1)):
one_path.append(
this_path[index][w])
for w in range(1, len(data_list[i])):
one_path.append(data_list[i][w])
print one_path
fd = open(file_path + '/alg2_path.txt',
'a')
fd.write(str(one_path) + '\n')
fd.close()
p1 = file_path + "/alg2_entries.json" #rounding
fd = open(p1, 'w')
fd.write(json.dumps(used_entries, indent=1))
fd.close()
p1 = file_path + "/alg2_ce.json" #rounding
fd = open(p1, 'w')
alg2_ce = {}
for e in all_edge:
alg2_ce[e] = float(used_ce[e]) / float(ce)
fd.write(json.dumps(alg2_ce, indent=1))
fd.close()
print "greedy", lambda1
p1 = file_path + "/alg2_lambda.json"
fd = open(p1, 'w')
fd.write(json.dumps(lambda1))
fd.write(json.dumps("/"))
fd.close()
alg2 = alg2 + lambda1
if alg == 3: #ospf
lambda1 = 0
used_ce = defaultdict(lambda: None)
used_entries = defaultdict(lambda: None)
for v in all_node:
used_entries[v] = 0
for e in all_edge:
used_ce[e] = 0
for i in range(0, flow_number):
for n in range(0, len(all_edge_alone[3 * i])):
#print n
used_ce[all_edge_alone[3 * i][n]] = used_ce[
all_edge_alone[3 * i][n]] + weight[i]
if used_ce[all_edge_alone[3 * i][n]] / float(
ce) > lambda1:
#print "hhhhh"
lambda1 = used_ce[all_edge_alone[3 * i]
[n]] / float(ce)
#print weight[i],source[i],terminal[i],lambda1,all_edge_alone[3*i+choose]
print "ospf", lambda1
p1 = file_path + "/alg3_lambda.json" #rounding
fd = open(p1, 'w')
fd.write(json.dumps(lambda1))
fd.write(json.dumps("/"))
fd.close()
alg3 = alg3 + lambda1
p1 = file_path + "/alg3_ce.json" #rounding
fd = open(p1, 'w')
alg3_ce = {}
for e in all_edge:
alg3_ce[e] = float(used_ce[e]) / float(ce)
fd.write(json.dumps(alg3_ce, indent=1))
fd.close()
print "Alg1 Finished"
def get_targets(g, s, ranks):
_, distances = dijkstra(g, s)
distances = distances.items()
distances.sort(key=lambda (x,y): y)
targets = [ (distances[r][0], r) for r in ranks]
return targets
for row in rows:
GMaster.add_edge(row[0], row[1], row[2])
for irow in interrows:
GMaster.add_edge(irow[0], irow[1], irow[2])
print "Calculate Routes..."
# Holds all routes in memory to aid filtering
fromToDict = {}
for stopFrom in fullStops:
print "Currently working on:", stopFrom
stA, t = spsl(stopFrom)
G = copy.deepcopy(GMaster)
distances, previous = algorithms.dijkstra(G, stopFrom)
for stopTo in fullStops:
stB, t = spsl(stopTo)
weight = distances[stopTo]
dKey = (stA, stB)
if (dKey not in fromToDict or fromToDict[dKey] > weight):
fromToDict[dKey] = weight
print "Saving Routes..."
with conn:
insStr = """INSERT INTO FULLROUTES (STATIONA, STATIONB, WEIGHT) VALUES (?, ?, ?) """
for stations, weightBB in fromToDict.iteritems():
def get_nfv_distribution(ratio, host_num, file_path):
CODEC = 'utf-8'
mynet = "8s9vnf.json"
g = DiGraph(mynet)
#自定义VNF的处理能力（1-10）
capacity = {
'F1': 10,
'F2': 10,
'F3': 10,
'I1': 10,
'I2': 10,
'I3': 10,
'P1': 10,
'P2': 10,
'P3': 10
}
each_NF_num = 3
#the number of 80 hosts
flowDic = get_flows(host_num, ratio)
flow_number = len(flowDic)
print "flow_number", flow_number
#Find out which streams of each type of NF have passed
flow = {}
flow['F'] = []
flow['I'] = []
flow['P'] = []
for key in flowDic:
if 'F' in str(flowDic[key][3]):
flow['F'].append(key)
if 'I' in str(flowDic[key][3]):
flow['I'].append(key)
if 'P' in str(flowDic[key][3]):
flow['P'].append(key)
#j stands for 9 processors, i stands for task (flow)
p = [([0] * len(flow) * 3) for i in range(len(flowDic))]
for j in capacity.keys():
#compute Pij= brand*distance(S-VNF-D) / processors
if 'F' in j:
if '1' in j:
row = 0
elif '2' in j:
row = 1
elif '3' in j:
row = 2
for i in flow['F']:
#src,vnf,dst
# print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print power
p[i - 1][row] = bandwidth * distance / power
#print i
#print p[i-1][row]
elif 'I' in j:
if '1' in j:
row = 3
elif '2' in j:
row = 4
elif '3' in j:
row = 5
for i in flow['I']:
#print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print power
p[i - 1][row] = bandwidth * distance / power
#print i
#print p[i-1][row]
elif 'P' in j:
if '1' in j:
row = 6
elif '2' in j:
row = 7
elif '3' in j:
row = 8
for i in flow['P']:
#print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print power
p[i - 1][row] = bandwidth * distance / power
#print i
#print p[i-1][row]
print "p", p
'''
Solving linear equation
'''
#x[i][j] ：Indicates that the ith stream passes through the jth vnf, and j(0-8) represents [F1, F2, F3, I1, I2, I3, P1, P2, P3]
'''Which F passed'''
x = [[0 for col in range(3)] for row in range(len(flowDic))]
#print x
for i in range(0, len(flowDic)):
for j in range(0, 3):
x[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x[i][j] = x[i][j] + "0000"
elif i < 100:
x[i][j] = x[i][j] + "000"
elif i < 1000:
x[i][j] = x[i][j] + "00"
elif i < 10000:
x[i][j] = x[i][j] + "0"
x[i][j] = x[i][j] + str(i) + str(j)
z = []
for i in range(0, len(flowDic)):
z.append("z" + str(i))
temp = []
for i in range(0, len(flowDic)):
for j in range(0,
3): # 3 si the number of path that each flow can choose
temp.append(x[i][j])
for i in range(0, len(flowDic)):
temp.append(z[i])
prob = LpProblem('lptest', LpMinimize)
r = LpVariable('r', lowBound=0)
xx = LpVariable.dicts("", temp, lowBound=0,
upBound=1) #,cat = pulp.LpInteger
print x[0]
#Add target equation
prob += r
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(3):
for j in range(len(flowDic)):
x_e[i][j][0] = x[j][i]
x_e[i][j][1] = p[j][i]
for i in range(0, 3):
prob += lpSum(xx[x_e[i][j][0]] * x_e[i][j][1] for j in x_e[i]) <= r
#Add constraints
for i in range(0, len(flowDic)):
prob += lpSum([xx[j] for j in x[i]]) == 1
#solve the question
GLPK().solve(prob)
print 'objective_sr =', value(prob.objective)
i = 0
j = 0
l = 0
for v in prob.variables():
l = l + 1
if l < flow_number * 3 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 2:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 3):
if x[i][j] >= k:
choose = j
k = x[i][j]
for j in range(0, 3):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('F' in str(flowDic[i + 1][3])):
for j in range(0, 3):
if x[i][j] == 1:
flowDic[i + 1].append(j)
'''which I'''
p_1 = [([0] * 3) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(3):
p_1[i][j] = p[i][j + 3]
x1 = [[0 for col in range(3)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 3):
x1[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x1[i][j] = x1[i][j] + "0000"
elif i < 100:
x1[i][j] = x1[i][j] + "000"
elif i < 1000:
x1[i][j] = x1[i][j] + "00"
elif i < 10000:
x1[i][j] = x1[i][j] + "0"
x1[i][j] = x1[i][j] + str(i) + str(j)
z1 = []
for i in range(0, len(flowDic)):
z1.append("z" + str(i))
temp1 = []
for i in range(0, len(flowDic)):
for j in range(0,
3): # 3 si the number of path that each flow can choose
temp1.append(x1[i][j])
for i in range(0, len(flowDic)):
temp1.append(z1[i])
prob1 = LpProblem('lptest1', LpMinimize)
r1 = LpVariable('r1', lowBound=0)
xx1 = LpVariable.dicts("", temp1, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
prob1 += r1
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e1 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(3):
for j in range(len(flowDic)):
x_e1[i][j][0] = x1[j][i]
x_e1[i][j][1] = p_1[j][i]
for i in range(0, 3):
prob1 += lpSum(xx1[x_e1[i][j][0]] * x_e1[i][j][1]
for j in x_e1[i]) <= r1
for i in range(0, len(flowDic)):
prob1 += lpSum([xx1[j] for j in x1[i]]) == 1
GLPK().solve(prob1)
print 'objective_sr =', value(prob1.objective)
i = 0
j = 0
l = 0
for v in prob1.variables():
l = l + 1
if l < flow_number * 3 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 2:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 3):
if x[i][j] >= k:
choose = j
k = x[i][j]
for j in range(0, 3):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('I' in str(flowDic[i + 1][3])):
for j in range(0, 3):
if x[i][j] == 1:
flowDic[i + 1].append(j)
'''which P'''
p_3 = [([0] * 3) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(3):
p_3[i][j] = p[i][j + 6]
print p_3
x3 = [[0 for col in range(3)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 3):
x3[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x3[i][j] = x3[i][j] + "0000"
elif i < 100:
x3[i][j] = x3[i][j] + "000"
elif i < 1000:
x3[i][j] = x3[i][j] + "00"
elif i < 10000:
x3[i][j] = x3[i][j] + "0"
x3[i][j] = x3[i][j] + str(i) + str(j)
z3 = []
for i in range(0, len(flowDic)):
z3.append("z3" + str(i))
temp3 = []
for i in range(0, len(flowDic)):
for j in range(0,
3): # 3 si the number of path that each flow can choose
temp3.append(x3[i][j])
for i in range(0, len(flowDic)):
temp3.append(z3[i])
prob3 = LpProblem('lptest3', LpMinimize)
r3 = LpVariable('r3', lowBound=0)
xx3 = LpVariable.dicts("", temp3, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
prob3 += r3
x_e3 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(3):
for j in range(len(flowDic)):
x_e3[i][j][0] = x3[j][i]
x_e3[i][j][1] = p_3[j][i]
for i in range(0, 3):
prob3 += lpSum(xx3[x_e3[i][j][0]] * x_e3[i][j][1]
for j in x_e3[i]) <= r3
for i in range(0, len(flowDic)):
prob3 += lpSum([xx3[j] for j in x3[i]]) == 1
GLPK().solve(prob3)
print 'objective_sr =', value(prob3.objective)
i = 0
j = 0
l = 0
for v in prob3.variables():
l = l + 1
if l < flow_number * 3 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 2:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 3):
if x[i][j] >= k:
choose = j
k = x[i][j]
for j in range(0, 3):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('P' in str(flowDic[i + 1][3])):
for j in range(0, 3):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
flow_vnf = file_path + '/flow_vnf.txt'
file = open(flow_vnf, 'w')
NF_load = (defaultdict(lambda: None))
for i in capacity:
NF_load[i] = 0
for t in flowDic:
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len,
0) # Find the index where the last comma is located
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
for i in range(1, sfc_len + 1):
#print flow_path[len(flow_path)-1]
NF_load[flow_path[i]] = int(NF_load[flow_path[i]]) + int(
flow_path[len(flow_path) - 1])
file.closed
flow_vnf = file_path + '/alg1_NF_load.txt'
file = open(flow_vnf, 'w')
file.write(json.dumps(NF_load, indent=1))
file.closed
alg1_max_NF = 0
for i in NF_load:
if alg1_max_NF < NF_load[i]:
alg1_max_NF = NF_load[i]
fd = open(file_path + '/alg1_max_NF.txt', 'w')
fd.write(json.dumps(alg1_max_NF))
fd.closed
file = open(file_path + '/flow_feasible_vnf.txt', 'w')
for t in flowDic:
for n in range(0, 3):
for i in range(4, len(flowDic[t])):
flowDic[t][i] = random.randint(0, each_NF_num - 1)
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len, 0)
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
file.closed
print "NFV Distribution Finished"
def start():
"""menu func
"""
distance = 0
flag = False
g = None
path = None
shortest_path = None
file_path = None
temp = utils.load_graph() #DataFrame #default csv file
# temp = utils.load_graph(file_path = 'data/topo3.csv',
# start_position = 1, end_position = 2, weight_positon = 3)
while True:
print("welcome to tourism management system")
print("plz enter a number:")
print("1. input Scenic Spots graph or change graph")
print("2. show Scenic Spots graph")
print("3. show Tour guide Graph")
print("4. show circle road in guide Graph")
print("5. calculate shortest path and distance")
print("6. show road constraction plan")
print("7. search and sort Scenic Spots")
print("8. parking system")
print("9. algorithm compare")
print("0. exit")
line = raw_input("enter sth, seperate by space, 0 for exit\n")
if line.strip() == "1":
file_path = raw_input(
"enter file name, 0 for creating a new csv file to store your graph\n"
)
if file_path.strip() == "0":
director.input_TourSortGraph() #create csv file
flag = True
temp = utils.load_graph(file_path='data/graph1.csv',
start_position=0,
end_position=1,
weight_positon=2)
else:
try:
temp = utils.load_graph(file_path='data/' +
file_path.strip(),
start_position=1,
end_position=2,
weight_positon=3)
g = nxutil.load_csv_nx(file_path='data/' +
file_path.strip())
except:
print("file do not exist, try again")
continue
elif line.strip() == "2":
if flag:
g = nxutil.load_csv_nx(file_path='data/graph1.csv')
elif g == None:
if file_path != None:
g = nxutil.load_csv_nx(file_path='data/' +
file_path.strip())
else:
g = nxutil.load_csv_nx()
nxutil.show(g)
elif line.strip() == "3":
path, distance = director.CreatTourSortGraph(temp)
print("#" * 40)
for i in path:
print(i)
print("#" * 40)
print(u"total length:")
print(distance)
if g == None:
if file_path != None:
g = nxutil.load_csv_nx(file_path='data/' +
file_path.strip())
else:
g = nxutil.load_csv_nx()
nxutil.show(g)
elif line.strip() == "4":
if path == None:
print("plz show Tour guide Graph first, now input 3")
continue
circle_path = algorithms_edgearr.TopoSort(path)
if g == None:
g = nxutil.load_csv_nx()
nxutil.show(g, node_list=circle_path)
elif line.strip() == "5":
poi = raw_input(
"enter startpoint|endpoint, seperate by |, input -1 for a default value"
)
if len(poi.strip().split("|")) != 1:
# print chardet.detect(poi.strip().split("|")[0])
start = unicode(poi.strip().split("|")[0],
"GB2312") # for windows console
end = unicode(poi.strip().split("|")[1], "GB2312")
else:
# print(len(poi.strip().split("|")))
print(
u"wrong format! use default instead: start from 北门, end in 碧水亭"
)
start = u'北门'
end = u'碧水亭'
# print(temp.columns.values[0])
if (type(temp.columns.values[0]) != unicode):
start = int(start)
end = int(end)
# print type(end)
dist, shortest_path = algorithms.dijkstra(temp,
start=start,
end=end)
if shortest_path == None:
print("point do not exsit")
continue
shortest_path.insert(0, start)
shortest_path.append(end)
for x in shortest_path:
print(x)
if g == None:
g = nxutil.load_csv_nx()
nxutil.show(g, path_list=shortest_path)
elif line.strip() == "6":
dis_list, distance = algorithms.MST(temp)
print(u"------------修路------------------")
for e in dis_list:
print(e[0]),
print(" --> "),
print(e[1])
print(u"total length:")
print(distance)
if g == None:
g = nxutil.load_csv_nx()
nxutil.show(g, path_list=dis_list)
elif line.strip() == "7":
recommend.start(file_path=file_path)
elif line.strip() == "8":
parking.start()
elif line.strip() == "9":
compare()
elif line.strip() == "0":
break
else:
print("wrong input, try again")
continue
def test_non_connected(self):
with open(os.path.join(base_path, 'data/non_connected.json')) as graph_file:
graph = Graph(graph_file)
with self.assertRaises(InvalidPathError):
dijkstra(graph, "1", "2")
def plan_route_from_graph(name: str,
G,
orig_coords,
dest_coords,
show: bool = None):
"""Diese Funktion wendet einen Algorithmus (name) auf einen Graphen G an, um den besten Weg
von den Startkoordinaten (orig_coords) zu den Zielkoordinaten (dest_coords) zu ermitteln.
Steht show auf True, wird der Graph geplottet, ansonsten (auch bei weglassen), werden nur die Daten ausgegeben.
Zulässige name-Werte (Aufsteigend: ungefähre Laufzeit):
* a-star
* dijkstra
* bellman-ford
* floyd-warshall
"""
# fetch nodes and prepare fields
orig_node = ox.get_nearest_node(G, orig_coords)
dest_node = ox.get_nearest_node(G, dest_coords)
dist = {}
pred = {}
route = []
if show is None:
show = False
print(f"===== START {name}, ({orig_coords[2]} → {dest_coords[2]})")
if (name == "floyd-warshall"):
# call algorithm
dist, next, count = floyd_warshall(G)
# prepare route
u = orig_node
v = dest_node
while u != v:
route += [u]
u = next[u][v]
else:
# call algorithm
if (name == "dijkstra"):
dist, pred, count = dijkstra(G, orig_node)
elif (name == "a-star"):
dist, pred, count = a_star(G, orig_node, dest_node)
elif (name == "bellman-ford"):
dist, pred, count = bellman_ford(G, orig_node)
# prepare route
v = dest_node
while v is not None:
route = [v] + route
v = pred[v]
printInfos(G, dist, pred, count, route, dist[dest_node])
print(f"===== ENDE {name}")
nc = ['r' if x in dist.keys() else 'black' for x in G.nodes]
fig, ax = ox.plot_graph_route(G,
route,
node_size=24,
node_color=nc,
node_alpha=0.6,
route_color='b',
route_alpha=0.7,
show=show)
def get_route_compare_algs(file_path):
all_node = []
all_node_alone = []
all_edge = []
all_edge_alone = []
all_edge_alone_order = []
terminal_random = []
one_edge = []
one_edge1 = []
one_edge_order = []
one_node = []
source = []
terminal = []
weight = []
flow_sfc = []
capacity = {'F1':10,'F2':10,'F3':10,'F4':10,'F5':10,'F6':10,'F7':10,'F8':10,'F9':10,'F10':10,'I1':10,'I2':10,'I3':10,'I4':10,'I5':10,'I6':10,'I7':10,'I8':10,'I9':10,'I10':10,'P1':10,'P2':10,'P3':10,'P4':10,'P5':10,'P6':10,'P7':10,'P8':10,'P9':10,'P10':10,'D1':10,'D2':10,'D3':10,'D4':10,'D5':10,'D6':10,'D7':10,'D8':10,'D9':10,'D10':10,'W1':10,'W2':10,'W3':10,'W4':10,'W5':10,'W6':10,'W7':10,'W8':10,'W9':10,'W10':10}
fd=file_path+'/SIMPLE_path.txt'
if os.path.exists(fd):
os.remove(fd)
fd=file_path+'/PDA_path.txt'
if os.path.exists(fd):
os.remove(fd)
k = 0
for line in open(file_path+"/flow_feasible_vnf.txt"):
flow_path=txt_wrap_by("'","'",line,0)
flow_sfc.append(flow_path)
if k%3 == 0:
source.append(flow_path[0])
terminal.append(flow_path[len(flow_path)-2])
weight.append(flow_path[len(flow_path)-1])
k=k+1
print len(source),len(flow_sfc),k
flow_number = len(source)
print "flow_number",flow_number
for sr in range (0,flow_number):
if sr%100 == 0:
print"source is ",sr,source[sr], terminal[sr]
main_path_all = []
one_source_edge = []
one_source_edge_order = []
one_source_node = []
main_path =[]
for q in range(0,len(flow_sfc[3*sr])-2):
path = dijkstra(g, str(flow_sfc[3*sr][q]),str(flow_sfc[3*sr][q+1]))
main_path_seg = path.get('path')
for i in range(0,len(main_path_seg)):
main_path_seg[i] = main_path_seg[i].encode(CODEC)
for i in range(0,len(main_path_seg)-1):
main_path.append(main_path_seg[i])
if q == len(flow_sfc[3*sr])-3:
main_path.append(main_path_seg[len(main_path_seg)-1])
for i in range(0,len(main_path)):
main_path_all.append(main_path[i])
for f in range(0,len(main_path)-3):
siwtch1 = int(main_path[f+1][1])
siwtch2 = int(main_path[f+2][1])
one_edge_order = main_path[f+1] + main_path[f+2]
if len(main_path[f+1]) == 3:
siwtch1 = siwtch1*10 + int(main_path[f+1][2])
if len(main_path[f+1]) == 4:
siwtch1 = siwtch1*100 + int(main_path[f+1][2])*10 + int(main_path[f+1][3])
if len(main_path[f+2]) == 3:
siwtch2 = siwtch2*10 + int(main_path[f+2][2])
if len(main_path[f+2]) == 4:
siwtch2 = siwtch2*100 + int(main_path[f+2][2])*10 + int(main_path[f+2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f+1] + main_path[f+2]
one_edge1 = main_path[f+2] + main_path[f+1]
else:
one_edge = main_path[f+2] + main_path[f+1]
one_edge1 = main_path[f+1] + main_path[f+2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0,len(main_path)-2):
one_node = main_path[f+1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
one_source_edge_order = []
one_source_node = []
one_source_edge = []
main_path =[]
for q in range(0,len(flow_sfc[3*sr+1])-2):
path = dijkstra2(g, str(flow_sfc[3*sr+1][q]),str(flow_sfc[3*sr+1][q+1]),main_path_all)
main_path_seg = path.get('path')
for i in range(0,len(main_path_seg)):
main_path_seg[i] = main_path_seg[i].encode(CODEC)
for i in range(0,len(main_path_seg)-1):
main_path.append(main_path_seg[i])
if q == len(flow_sfc[3*sr+1])-3:
main_path.append(main_path_seg[len(main_path_seg)-1])
for i in range(0,len(main_path)):
main_path_all.append(main_path[i])
for f in range(0,len(main_path)-3):
siwtch1 = int(main_path[f+1][1])
siwtch2 = int(main_path[f+2][1])
one_edge_order = main_path[f+1] + main_path[f+2]
if len(main_path[f+1]) == 3:
siwtch1 = siwtch1*10 + int(main_path[f+1][2])
if len(main_path[f+1]) == 4:
siwtch1 = siwtch1*100 + int(main_path[f+1][2])*10 + int(main_path[f+1][3])
if len(main_path[f+2]) == 3:
siwtch2 = siwtch2*10 + int(main_path[f+2][2])
if len(main_path[f+2]) == 4:
siwtch2 = siwtch2*100 + int(main_path[f+2][2])*10 + int(main_path[f+2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f+1] + main_path[f+2]
one_edge1 = main_path[f+2] + main_path[f+1]
else:
one_edge = main_path[f+2] + main_path[f+1]
one_edge1 = main_path[f+1] + main_path[f+2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0,len(main_path)-2):
one_node = main_path[f+1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
one_source_node = []
one_source_edge = []
one_source_edge_order = []
main_path =[]
for q in range(0,len(flow_sfc[3*sr+2])-2):
path = dijkstra3(g, str(flow_sfc[3*sr+2][q]),str(flow_sfc[3*sr+2][q+1]),main_path_all)
main_path_seg = path.get('path')
for i in range(0,len(main_path_seg)):
main_path_seg[i] = main_path_seg[i].encode(CODEC)
for i in range(0,len(main_path_seg)-1):
main_path.append(main_path_seg[i])
if q == len(flow_sfc[3*sr+2])-3:
main_path.append(main_path_seg[len(main_path_seg)-1])
for i in range(0,len(main_path)):
main_path_all.append(main_path[i])
for f in range(0,len(main_path)-3):
siwtch1 = int(main_path[f+1][1])
siwtch2 = int(main_path[f+2][1])
one_edge_order = main_path[f+1] + main_path[f+2]
if len(main_path[f+1]) == 3:
siwtch1 = siwtch1*10 + int(main_path[f+1][2])
if len(main_path[f+1]) == 4:
siwtch1 = siwtch1*100 + int(main_path[f+1][2])*10 + int(main_path[f+1][3])
if len(main_path[f+2]) == 3:
siwtch2 = siwtch2*10 + int(main_path[f+2][2])
if len(main_path[f+2]) == 4:
siwtch2 = siwtch2*100 + int(main_path[f+2][2])*10 + int(main_path[f+2][3])
if siwtch1 < siwtch2:
one_edge = main_path[f+1] + main_path[f+2]
one_edge1 = main_path[f+2] + main_path[f+1]
else:
one_edge = main_path[f+2] + main_path[f+1]
one_edge1 = main_path[f+1] + main_path[f+2]
if one_edge not in all_edge:
if one_edge1 not in all_edge:
all_edge.append(one_edge)
else:
one_edge = one_edge1
one_source_edge.append(one_edge)
one_source_edge_order.append(one_edge_order)
all_edge_alone.append(one_source_edge)
all_edge_alone_order.append(one_source_edge_order)
for f in range(0,len(main_path)-2):
one_node = main_path[f+1]
if one_node not in all_node:
all_node.append(one_node)
one_source_node.append(one_node)
all_node_alone.append(one_source_node)
weight [sr] = int (weight[sr])
for flow_traffic in range(1,2):
alg0=0
alg1=0
alg2=0
alg3=0
for randome_time in range(0,1):
for entries in range(31,32): #300-4200
entries = entries *10000
ce = 10000
for alg in range(0,10):
if alg == 2: #SIMPLE alg, linke load balancing
used_ce = defaultdict(lambda:None)
used_entries = defaultdict(lambda:None)
for v in all_node:
used_entries[v] = 0
for e in all_edge:
used_ce[e] = 0
lambda1 = 0
max_entries = 0
temp2 = 0
for i in range(0,flow_number):
temp = [[0 for col in range(2)] for row in range(3)]
for row in range(0,3):
for col in range(0,2):
temp[row][col] = 0
for j in range(0,3):
for n in range(0,len(all_edge_alone[3*i+j])):
q=0
for m in range(0,len(all_edge_alone[3*i+j])):
if all_edge_alone[3*i+j][n] == all_edge_alone[3*i+j][m]:
q=q+1
if temp[j][1]<(used_ce[all_edge_alone[3*i+j][n]] + q*weight[i])/float(ce):
temp[j][1] = (used_ce[all_edge_alone[3*i+j][n]] + q*weight[i])/float(ce)
temp1 = 1000000
k = 0
for j in range(0,3):
if temp[j][1] < temp1:
k = j;
temp1 = temp[j][1];
for n in range(0,len(all_edge_alone[3*i+k])):
used_ce[all_edge_alone[3*i+k][n]] = used_ce[all_edge_alone[3*i+k][n]] + weight[i]
for n in range(0,len(all_node_alone[3*i+k])):
used_entries[all_node_alone[3*i+k][n]] = used_entries[all_node_alone[3*i+k][n]] + 1
alg2_choosed_path=[]
alg2_choosed_path.append(source[i])
for j in range (0,len(all_node_alone[3*i+k])):
alg2_choosed_path.append(all_node_alone[3*i+k][j])
alg2_choosed_path.append(terminal[i])
alg2_choosed_path.append(weight[i])
fd=open(file_path+'/SIMPLE_path.txt','a')
fd.write(str(alg2_choosed_path) + '\n')
fd.close()
alg2_entries ={}
for j in used_entries:
if 's' in str(j):
alg2_entries[j] = used_entries [j]
if max_entries < used_entries[j]:
max_entries = used_entries[j]
p1 = file_path+"/SIMPLE_entries.json" #rounding
fd = open(p1, 'w')
fd.write(json.dumps(alg2_entries, indent=1))
fd.close()
p1 = file_path+"/SIMPLE_ce.json" #rounding
p2 = file_path+"/SIMPLE_NF_load.json" # rounding
fd1 = open(p1, 'w')
fd2 = open(p2, 'w')
alg2_ce_link = {}
alg2_ce_middlebox = {}
for e in all_edge:
isMark = 0
for key in capacity:
if key in e:
alg2_ce_middlebox[key] = float(used_ce[e])/2
isMark = 1
if isMark == 0:
alg2_ce_link[e] = float(used_ce[e]) / float(ce)
fd1.write(json.dumps(alg2_ce_link, indent=1))
fd1.close()
fd2.write(json.dumps(alg2_ce_middlebox, indent=1))
fd2.close()
lambda1 = 0
for j in alg2_ce_link:
if lambda1 < alg2_ce_link[j]:
lambda1 = alg2_ce_link[j]
SIMPLE_max_NF=0
for j in alg2_ce_middlebox:
if SIMPLE_max_NF < alg2_ce_middlebox[j]:
SIMPLE_max_NF = alg2_ce_middlebox[j]
print "SIMPLE",lambda1,max_entries
p1 = file_path+"/SIMPLE_lambda.json"
fd = open(p1, 'w')
fd.write(json.dumps(lambda1))
fd.close()
p1 = file_path+"/SIMPLE_max_entries.json"
fd = open(p1, 'w')
fd.write(json.dumps(max_entries))
fd.close()
p1 = file_path+"/SIMPLE_max_NF.json"
fd = open(p1, 'w')
fd.write(json.dumps(SIMPLE_max_NF))
fd.close()
if alg == 3: #PDA alg
used_ce = defaultdict(lambda:None)
used_entries = defaultdict(lambda:None)
for v in all_node:
used_entries[v] = 0
for e in all_edge:
used_ce[e] = 0
lambda1 = 0
max_entries = 0
temp2 = 0
for i in range(0,flow_number):
temp = [[0 for col in range(2)] for row in range(3)]
for row in range(0,3):
for col in range(0,2):
temp[row][col] = 0
for j in range(0,3):
for n in range(0,len(all_node_alone[3*i+j])):
q=0
for m in range(0,len(all_node_alone[3*i+j])):
if all_node_alone[3*i+j][n] == all_node_alone[3*i+j][m]:
q=q+1
if temp[j][1]<used_entries[all_node_alone[3*i+j][n]] + q:
temp[j][1] = used_entries[all_node_alone[3*i+j][n]] + q
temp1 = 10000000
k = 0 #表示选几个可行路径中的哪一条
for j in range(0,3):
if temp[j][1] < temp1: #选择满足流表约束条件下的，负载最轻的那条可行路径.
k = j;
temp1 = temp[j][1];
for n in range(0,len(all_edge_alone[3*i+k])): #从可行路径中选择一条（第k条），需要使用链路容量和流表项
used_ce[all_edge_alone[3*i+k][n]] = used_ce[all_edge_alone[3*i+k][n]] + weight[i]
#if used_ce[all_edge_alone[3*i+k][n]]/float(ce) > lambda1:
#lambda1 = used_ce[all_edge_alone[3*i+k][n]]/float(ce) #记录最大的lambda
for n in range(0,len(all_node_alone[3*i+k])):
used_entries[all_node_alone[3*i+k][n]] = used_entries[all_node_alone[3*i+k][n]] + 1
alg3_choosed_path=[]
alg3_choosed_path.append(source[i])
for j in range (0,len(all_node_alone[3*i+k])):
alg3_choosed_path.append(all_node_alone[3*i+k][j])
alg3_choosed_path.append(terminal[i])
alg3_choosed_path.append(weight[i])
fd=open(file_path+'/PDA_path.txt','a')
fd.write(str(alg3_choosed_path) + '\n')
fd.close()
alg3_entries ={}
for j in used_entries:
if 's' in str(j):
alg3_entries[j] = used_entries [j]
if max_entries < used_entries[j]:
max_entries = used_entries[j]
p1 = file_path+"/PDA_entries.json" #rounding
fd = open(p1, 'w')
fd.write(json.dumps(alg3_entries, indent=1))
fd.close()
p1 = file_path+"/PDA_ce.json" #rounding
p2 = file_path+"/PDA_NF_load.json" # rounding
fd1 = open(p1, 'w')
fd2 = open(p2, 'w')
alg3_ce_link = {}
alg3_ce_middlebox = {}
for e in all_edge:
isMark = 0
#链路负载和midllebox负载
for key in capacity:
if key in e:
alg3_ce_middlebox[key] = float(used_ce[e])/2
isMark = 1
if isMark == 0:
alg3_ce_link[e] = float(used_ce[e]) / float(ce)
fd1.write(json.dumps(alg3_ce_link, indent=1))
fd1.close()
fd2.write(json.dumps(alg3_ce_middlebox, indent=1))
fd2.close()
lambda1 = 0
for j in alg3_ce_link:
if lambda1 < alg3_ce_link[j]:
lambda1 = alg3_ce_link[j]
PDA_max_NF=0
for j in alg3_ce_middlebox:
if PDA_max_NF < alg3_ce_middlebox[j]:
PDA_max_NF = alg3_ce_middlebox[j]
print "PDA",lambda1, max_entries
p1 = file_path+"/PDA_lambda.json"
fd = open(p1, 'w')
fd.write(json.dumps(lambda1))
fd.close()
p1 = file_path+"/PDA_max_entries.json"
fd = open(p1, 'w')
fd.write(json.dumps(max_entries))
fd.close()
p1 = file_path+"/PDA_max_NF.json"
fd = open(p1, 'w')
fd.write(json.dumps(PDA_max_NF))
fd.close()
print "Compare_algs Finished"
def get_nfv_distribution(ratio, host_num, file_path):
CODEC = 'utf-8'
mynet = "rocketfuel_87s174h50nf.json"
g = DiGraph(mynet)
#Custom VNF processing power (1-10)
capacity = {
'F1': 10,
'F2': 10,
'F3': 10,
'F4': 10,
'F5': 10,
'F6': 10,
'F7': 10,
'F8': 10,
'F9': 10,
'F10': 10,
'I1': 10,
'I2': 10,
'I3': 10,
'I4': 10,
'I5': 10,
'I6': 10,
'I7': 10,
'I8': 10,
'I9': 10,
'I10': 10,
'P1': 10,
'P2': 10,
'P3': 10,
'P4': 10,
'P5': 10,
'P6': 10,
'P7': 10,
'P8': 10,
'P9': 10,
'P10': 10,
'D1': 10,
'D2': 10,
'D3': 10,
'D4': 10,
'D5': 10,
'D6': 10,
'D7': 10,
'D8': 10,
'D9': 10,
'D10': 10,
'W1': 10,
'W2': 10,
'W3': 10,
'W4': 10,
'W5': 10,
'W6': 10,
'W7': 10,
'W8': 10,
'W9': 10,
'W10': 10
}
each_NF_num = 10
#Enter two functional chains
#Number of streams between 80 hosts
flowDic = get_flows(host_num, ratio)
flow_number = len(flowDic)
print "flow_number", flow_number
#print flowDic
#Find out which streams of each type of NF have passed
flow = {}
flow['F'] = []
flow['I'] = []
flow['P'] = []
flow['D'] = []
flow['W'] = []
for key in flowDic:
if 'F' in str(flowDic[key][3]):
flow['F'].append(key)
if 'I' in str(flowDic[key][3]):
flow['I'].append(key)
if 'P' in str(flowDic[key][3]):
flow['P'].append(key)
if 'D' in str(flowDic[key][3]):
flow['D'].append(key)
if 'W' in str(flowDic[key][3]):
flow['W'].append(key)
#j stands for 9 processors, i stands for task (flow)
p = [([0] * len(flow) * 10) for i in range(len(flowDic))]
#print len(p),len(p[0])
for j in capacity.keys():
print j
#Calculate the processing power of Pij = stream bandwidth * distance to the NF (S-VNF-D) / NF
if 'F' in j:
#print "F",j
if '1' in j and '10' not in j:
row = 0
elif '2' in j:
row = 1
elif '3' in j:
row = 2
elif '4' in j:
row = 3
elif '5' in j:
row = 4
elif '6' in j:
row = 5
elif '7' in j:
row = 6
elif '8' in j:
row = 7
elif '9' in j:
row = 8
elif '10' in j:
#print "F10",j
row = 9
for i in flow['F']:
# print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print "power",power
#p[i-1][row] = bandwidth * distance / power
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
#p[i-1][row] = bandwidth
#print i
#print p[i-1][row]
elif 'I' in j:
if '1' in j and '10' not in j:
row = 10
elif '2' in j:
row = 11
elif '3' in j:
row = 12
elif '4' in j:
row = 13
elif '5' in j:
row = 14
elif '6' in j:
row = 15
elif '7' in j:
row = 16
elif '8' in j:
row = 17
elif '9' in j:
row = 18
elif '10' in j:
row = 19
for i in flow['I']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
elif 'P' in j:
if '1' in j and '10' not in j:
row = 20
elif '2' in j:
row = 21
elif '3' in j:
row = 22
elif '4' in j:
row = 23
elif '5' in j:
row = 24
elif '6' in j:
row = 25
elif '7' in j:
row = 26
elif '8' in j:
row = 27
elif '9' in j:
row = 28
elif '10' in j:
row = 29
for i in flow['P']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
elif 'D' in j:
if '1' in j and '10' not in j:
row = 30
elif '2' in j:
row = 31
elif '3' in j:
row = 32
elif '4' in j:
row = 33
elif '5' in j:
row = 34
elif '6' in j:
row = 35
elif '7' in j:
row = 36
elif '8' in j:
row = 37
elif '9' in j:
row = 38
elif '10' in j:
row = 39
for i in flow['D']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
elif 'W' in j:
if '1' in j and '10' not in j:
row = 40
elif '2' in j:
row = 41
elif '3' in j:
row = 42
elif '4' in j:
row = 43
elif '5' in j:
row = 44
elif '6' in j:
row = 45
elif '7' in j:
row = 46
elif '8' in j:
row = 47
elif '9' in j:
row = 48
elif '10' in j:
row = 49
for i in flow['W']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
'''
Solving linear equation
'''
#x = [[0 for col in range(len(flowDic))] for row in range(3)]
#x[i][j] ：Indicates that the ith stream passes through the jth vnf, and j(0-8) represents [F1, F2, F3, I1, I2, I3, P1, P2, P3]
'''Which F is passed through?'''
x = [[0 for col in range(10)] for row in range(len(flowDic))]
#print x
for i in range(0, len(flowDic)):
for j in range(0, 10):
x[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x[i][j] = x[i][j] + "0000"
elif i < 100:
x[i][j] = x[i][j] + "000"
elif i < 1000:
x[i][j] = x[i][j] + "00"
elif i < 10000:
x[i][j] = x[i][j] + "0"
x[i][j] = x[i][j] + str(i) + str(j)
z = []
for i in range(0, len(flowDic)):
z.append("z" + str(i))
temp = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp.append(x[i][j])
for i in range(0, len(flowDic)):
temp.append(z[i])
prob = LpProblem('lptest', LpMinimize)
r = LpVariable('r', lowBound=0)
xx = LpVariable.dicts("", temp, lowBound=0,
upBound=1) #,cat = pulp.LpInteger
#print temp
print "-------2222222-----"
#print x[0]
#Add the target equation
#0-28 flows
prob += r
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e[i][j][0] = x[j][i]
x_e[i][j][1] = p[j][i]
for i in range(0, 10):
prob += lpSum(xx[x_e[i][j][0]] * x_e[i][j][1] for j in x_e[i]) <= r
#Add constraints
for i in range(0, len(flowDic)):
prob += lpSum([xx[j] for j in x[i]]) == 1
GLPK().solve(prob)
print 'F_objective_sr =', value(prob.objective)
i = 0
j = 0
l = 0
for v in prob.variables():
#print v, v.varValue
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('F' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
#sleep(600)
'''Which I passed through'''
#P_1 refers to the cost of I function
p_1 = [([0] * 10) for i in range(len(flowDic))]
#print "hh",len(p_1),len(p_1[0])
for i in range(len(flowDic)):
for j in range(10):
#print i,j,
p_1[i][j] = p[i][j + 10]
x1 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x1[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x1[i][j] = x1[i][j] + "0000"
elif i < 100:
x1[i][j] = x1[i][j] + "000"
elif i < 1000:
x1[i][j] = x1[i][j] + "00"
elif i < 10000:
x1[i][j] = x1[i][j] + "0"
x1[i][j] = x1[i][j] + str(i) + str(j)
z1 = []
for i in range(0, len(flowDic)):
z1.append("z" + str(i))
temp1 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp1.append(x1[i][j])
for i in range(0, len(flowDic)):
temp1.append(z1[i])
prob1 = LpProblem('lptest1', LpMinimize)
r1 = LpVariable('r1', lowBound=0)
xx1 = LpVariable.dicts("", temp1, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
#print xx1
prob1 += r1
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e1 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e1[i][j][0] = x1[j][i]
x_e1[i][j][1] = p_1[j][i]
for i in range(0, 10):
prob1 += lpSum(xx1[x_e1[i][j][0]] * x_e1[i][j][1]
for j in x_e1[i]) <= r1
for i in range(0, len(flowDic)):
prob1 += lpSum([xx1[j] for j in x1[i]]) == 1
GLPK().solve(prob1)
print 'I_objective_sr =', value(prob1.objective)
i = 0
j = 0
l = 0
for v in prob1.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('I' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
'''Which P passed?'''
p_3 = [([0] * 10) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(10):
p_3[i][j] = p[i][j + 20]
x3 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x3[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x3[i][j] = x3[i][j] + "0000"
elif i < 100:
x3[i][j] = x3[i][j] + "000"
elif i < 1000:
x3[i][j] = x3[i][j] + "00"
elif i < 10000:
x3[i][j] = x3[i][j] + "0"
x3[i][j] = x3[i][j] + str(i) + str(j)
z3 = []
for i in range(0, len(flowDic)):
z3.append("z3" + str(i))
temp3 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp3.append(x3[i][j])
for i in range(0, len(flowDic)):
temp3.append(z3[i])
prob3 = LpProblem('lptest3', LpMinimize)
r3 = LpVariable('r3', lowBound=0)
xx3 = LpVariable.dicts("", temp3, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
x_e3 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e3[i][j][0] = x3[j][i]
x_e3[i][j][1] = p_3[j][i]
for i in range(0, 10):
prob3 += lpSum(xx3[x_e3[i][j][0]] * x_e3[i][j][1]
for j in x_e3[i]) <= r3
for i in range(0, len(flowDic)):
prob3 += lpSum([xx3[j] for j in x3[i]]) == 1
GLPK().solve(prob3)
print 'P_objective_sr =', value(prob3.objective)
i = 0
j = 0
l = 0
for v in prob3.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('P' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
'''Which D is passed through?'''
p_4 = [([0] * 10) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(10):
p_4[i][j] = p[i][j + 30]
x4 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x4[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x4[i][j] = x4[i][j] + "0000"
elif i < 100:
x4[i][j] = x4[i][j] + "000"
elif i < 1000:
x4[i][j] = x4[i][j] + "00"
elif i < 10000:
x4[i][j] = x4[i][j] + "0"
x4[i][j] = x4[i][j] + str(i) + str(j)
z4 = []
for i in range(0, len(flowDic)):
z4.append("z4" + str(i))
temp4 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp4.append(x4[i][j])
for i in range(0, len(flowDic)):
temp4.append(z4[i])
prob4 = LpProblem('lptest4', LpMinimize)
r4 = LpVariable('r4', lowBound=0)
xx4 = LpVariable.dicts("", temp4, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
prob4 += r4
x_e4 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e4[i][j][0] = x4[j][i]
x_e4[i][j][1] = p_4[j][i]
for i in range(0, 10):
prob4 += lpSum(xx4[x_e4[i][j][0]] * x_e4[i][j][1]
for j in x_e4[i]) <= r4
for i in range(0, len(flowDic)):
prob4 += lpSum([xx4[j] for j in x4[i]]) == 1
GLPK().solve(prob4)
print 'D_objective_sr =', value(prob4.objective)
i = 0
j = 0
l = 0
for v in prob4.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('D' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
'''Which W to solve'''
p_5 = [([0] * 10) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(10):
p_5[i][j] = p[i][j + 40]
x5 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x5[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x5[i][j] = x5[i][j] + "0000"
elif i < 100:
x5[i][j] = x5[i][j] + "000"
elif i < 1000:
x5[i][j] = x5[i][j] + "00"
elif i < 10000:
x5[i][j] = x5[i][j] + "0"
x5[i][j] = x5[i][j] + str(i) + str(j)
z5 = []
for i in range(0, len(flowDic)):
z5.append("z5" + str(i))
temp5 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp5.append(x5[i][j])
for i in range(0, len(flowDic)):
temp5.append(z5[i])
prob5 = LpProblem('lptest5', LpMinimize)
r5 = LpVariable('r5', lowBound=0)
xx5 = LpVariable.dicts("", temp5, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
#print xx3
prob5 += r5
x_e5 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e5[i][j][0] = x5[j][i]
x_e5[i][j][1] = p_5[j][i]
for i in range(0, 10):
prob5 += lpSum(xx5[x_e5[i][j][0]] * x_e5[i][j][1]
for j in x_e5[i]) <= r5
for i in range(0, len(flowDic)):
prob5 += lpSum([xx5[j] for j in x5[i]]) == 1
GLPK().solve(prob5)
print 'W_objective_sr =', value(prob5.objective)
i = 0
j = 0
l = 0
for v in prob5.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('W' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
flow_vnf = file_path + '/flow_vnf.txt'
file = open(flow_vnf, 'w')
NF_load = (defaultdict(lambda: None))
for i in capacity:
NF_load[i] = 0
for t in flowDic:
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len, 0)
#print "2222222222",line,k, txt_wrap_by(",","]",line,k)
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
for i in range(1, sfc_len + 1):
#print flow_path[len(flow_path)-1]
NF_load[flow_path[i]] = int(NF_load[flow_path[i]]) + int(
flow_path[len(flow_path) - 1])
file.closed
flow_vnf = file_path + '/alg1_NF_load.txt'
file = open(flow_vnf, 'w')
file.write(json.dumps(NF_load, indent=1))
file.closed
alg1_max_NF = 0
for i in NF_load:
if alg1_max_NF < NF_load[i]:
alg1_max_NF = NF_load[i]
fd = open(file_path + '/alg1_max_NF.txt', 'w')
fd.write(json.dumps(alg1_max_NF))
fd.closed
file = open(file_path + '/flow_feasible_vnf.txt', 'w')
for t in flowDic:
for n in range(0, 3):
for i in range(4, len(flowDic[t])):
flowDic[t][i] = random.randint(0, each_NF_num - 1)
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len, 0)
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
file.closed
print "NFV Distribution Finished"
