def geocast_knn(data, t):
# find all workers in MTD
# find all workers in the query
MTD_RECT = np.array([[t[0] - Params.ONE_KM * Params.MTD, t[1] - Params.ONE_KM * Params.MTD],
[t[0] + Params.ONE_KM * Params.MTD, t[1] + Params.ONE_KM * Params.MTD]])
locs = rect_query_points(data, MTD_RECT).transpose()
locs = sorted(locs, key=lambda loc: distance(loc[0], loc[1], t[0], t[1]))
u, dist, found = 0, 0, False
workers = np.zeros(shape=(2, 0))
for loc in locs:
workers = np.concatenate([workers, np.array([[loc[0]], [loc[1]]])], axis=1)
_dist = distance(loc[0], loc[1], t[0], t[1])
u_c = acc_rate(Params.MTD, _dist)
u = 1 - (1 - u) * (1 - u_c)
if is_performed(u_c):
if not found:
found = True
dist = _dist
if u >= Params.U:
break
# simulation
isPerformed, worker, dist_fcfs = performed_tasks(workers, Params.MTD, t, True)
hops_count, coverage, hops_count2 = hops_expansion(t, workers.transpose(), Params.NETWORK_DIAMETER)
if isPerformed: # the task is performed
return workers.shape[1], True, dist, dist_fcfs, hops_count, coverage, hops_count2
return workers.shape[1], False, None, None, hops_count, coverage, hops_count2
def get(self, geocast_id):
"""
Override the standard GET
"""
global all_data, eps
parts = geocast_id.split('/')
dataset = parts[0]
print parts
t = map(float, parts[1].split(','))
print dataset, t
# if task not in region
if not is_rect_cover(all_data[dataset][1], t):
self.write(json.dumps({"error": "invalid task"}))
return
q, q_log = geocast(all_data[dataset][0], t, float(eps))
no_workers, workers, Cells, no_hops, coverage, no_hops2 = post_geocast(t, q, q_log)
performed, worker, dist = performed_tasks(workers, Params.MTD, t, True)
x_min, y_min, x_max, y_max = [], [], [], []
worker_counts, utilities, distances, compactnesses, areas = [], [], [], [], []
if worker is not None:
worker = worker.tolist()
corner_points = Set([])
for cell in Cells:
x_min.append(cell[0].n_box[0][0])
y_min.append(cell[0].n_box[0][1])
x_max.append(cell[0].n_box[1][0])
y_max.append(cell[0].n_box[1][1])
worker_counts.append(cell[0].n_count)
utilities.append([cell[2][1], cell[2][2]])
compactnesses.append(cell[2][3])
distances.append(float("%.3f" % distance_to_rect(t[0], t[1], cell[0].n_box)))
distances.append(float("%.3f" % distance_to_rect(t[0], t[1], cell[0].n_box)))
areas.append(float("%.3f" % rect_area(cell[0].n_box)))
corner_points = corner_points | rect_vertex_set(cell[0].n_box)
points = list(corner_points)
x = make_circle(points)
if x is not None:
cx, cy, r = x
print cx, cy, r
else:
cx, cy, r = 0, 0, 0
no_hops2 = math.ceil(no_hops2)
if performed:
self.write(
json.dumps({"is_performed": performed,
"notified_workers": {"no_workers": no_workers,
"x_coords": workers[0].tolist(),
"y_coords": workers[1].tolist()},
"geocast_query": {"no_cell": len(Cells),
"compactness": q_log[-1][3],
"x_min_coords": x_min,
"y_min_coords": y_min,
"x_max_coords": x_max,
"y_max_coords": y_max,
"worker_counts": worker_counts,
"utilities": utilities,
"compactnesses": compactnesses,
"distances": distances,
"areas": areas},
"spatial_task": {"location": t},
"volunteer_worker": {"location": worker,
"distance": dist},
"hop_count": no_hops2,
"bounding_circle": [cx, cy, r]},
sort_keys=False)
)
else:
self.write(
json.dumps({"is_performed": False,
"notified_workers": {"no_workers": no_workers,
"x_coords": workers[0].tolist(),
"y_coords": workers[1].tolist()},
"geocast_query": {"no_cell": len(Cells),
"x_min_coords": x_min,
"y_min_coords": y_min,
"x_max_coords": x_max,
"y_max_coords": y_max,
"worker_counts": worker_counts,
"utilities": utilities,
"compactnesses": compactnesses,
"distances": distances,
"areas": areas},
"spatial_task": {"location": t},
"volunteer_worker": {"location": worker,
"distance": dist},
"hop_count": no_hops2,
"bounding_circle": [cx, cy, r]},
sort_keys=False)
)
# logging
if Params.GEOCAST_LOG:
info = GeocastInfo(int(performed), t, Cells)
log_str = str(info.logging()) + "\n"
geocast_log("geocast_server", log_str, eps)