def nearest_simulation(system_end_time, MEC_resource, device_num,
device_allocation_method, path_w):
# ---
# MECの準備
df = pd.read_csv(
"/Users/sugimurayuuki/Desktop/mecsimulator/CloudletSimulator/base_station/kddi_okayama_city2.csv",
dtype={
'lon': 'float',
'lat': 'float'
})
server_type = "LTE"
cover_range = 500
n = len(df)
print("Number of MEC server:", n)
mec = [MEC_server(0, 00, " ", 00.00, 00.00, 0, 0)] * n
for index, series in df.iterrows():
mec[index] = MEC_server(MEC_resource, index + 1, server_type,
series["lon"], series["lat"], cover_range,
system_end_time)
#mec = delete_mec(mec)
mec_num = len(mec)
print("MECs", mec_num)
# 集約局を対応するMECに設定する
set_aggregation_station(mec)
# 到着順
if device_allocation_method == 0:
d = open(
'/Users/sugimurayuuki/Desktop/mecsimulator/CloudletSimulator/dataset/device.clone_binaryfile',
'rb')
devices = pickle.load(d)
devices = devices[0:device_num]
num = len(devices)
sum = 0
for i in range(num):
devices[i].startup_time = float(
devices[i].plan[0].time) # 各デバイスの起動時間を設定する
devices[i].set_congestion_status(system_end_time)
devices[i].set_MEC_distance(len(df))
devices[i]._first_flag = True
devices[i]._allocation_plan = [None] * system_end_time
sum = sum + devices[i].use_resource
print(sum)
# 順序をシャッフル
random.shuffle(devices)
sorted_devices = [devices] * system_end_time
for t in range(system_end_time):
random.shuffle(devices)
sorted_devices[t] = devices
# リソース順
elif device_allocation_method == 1:
d = open(
'/Users/sugimurayuuki/Desktop/mecsimulator/CloudletSimulator/dataset/device.congestion_binaryfile_500',
'rb')
devices = pickle.load(d)
devices = devices[0:device_num]
num = len(devices)
devices = reverse_resource_sort(devices)
for i in range(num):
devices[i].startup_time = float(
devices[i].plan[0].time) # 各デバイスの起動時間を設定する
devices[i].set_congestion_status(system_end_time)
devices[i].set_MEC_distance(len(df))
devices[i]._first_flag = True
sorted_devices = [devices] * system_end_time
# 混雑度順
else:
# 混雑度計算
# traffic_congestion(mec, devices, system_end_time, 1000)
cd = open(
'/Users/sugimurayuuki/Desktop/mecsimulator/CloudletSimulator/dataset/congestion_checked_devices.binaryfile',
'rb')
cd = pickle.load(cd)
devices = cd
num = len(devices)
print("device_num", num)
# 混雑度順で毎秒ごとのdevicesをソートする
sorted_devices = devices_congestion_sort(devices, system_end_time)
# ---
# ここからメインの処理
for t in range(system_end_time):
print("[TIME:", t, "]")
# ある時刻tのMECに割り当てらえたデバイスを一時的に保存する用の変数
save_devices = [None] * mec_num
for i in range(num):
print("---new device---", sorted_devices[t][i].name)
# plan_indexがデバイスの稼働時間外なら処理をスキップ
if (check_plan_index(sorted_devices[t][i].plan_index,
len(sorted_devices[t][i].plan)) == False):
print("skip")
continue
# plan_indexが稼働時間内なら処理開始
if check_between_time(sorted_devices[t][i], t) == True:
print(sorted_devices[t][i].plan_index)
# 最近傍割り当て処理
device_flag, allocation_MEC_name = nearest_search2(
sorted_devices[t][i], mec, sorted_devices[t][i].plan_index,
cover_range, t)
# 最近傍割り当てが成功したら表示する
if device_flag == True:
# deviceが直前で割り当てたMECを取得
mec_index = search_mec_index(mec, allocation_MEC_name)
# print("device:", sorted_devices[t][i].name, ", use_resource:", sorted_devices[t][i].use_resource, "--->", "MEC_ID:", mec[mec_index].name, ", index:", i)
# print(sorted_devices[t][i].mec_name, mec[mec_index].resource)
# print(mec_index, len(save_devices))
# なぜindexがmec_indexなの？ <- mec用のリストだから
if save_devices[mec_index] == None:
save_devices[mec_index] = [sorted_devices[t][i].name]
else:
save_devices[mec_index].append(
sorted_devices[t][i].name)
# ---
# print(t, mec_index, index)
# 実行時間外の時
else:
# デバイスがMECを見つけられないかった時
print(devices[i].name)
print("NOT FIND")
# plan_indexをインクリメント
sorted_devices[t][
i]._plan_index = sorted_devices[t][i]._plan_index + 1
else:
# デバイスの稼働時間を超えた時の処理
# 前回割り当てたMECのリソースをリカバリーする。
if sorted_devices[t][i].mec_name != [] and sorted_devices[t][
i]._lost_flag == False:
previous_index = search_mec_index(
mec, sorted_devices[t][i].mec_name)
print("DECREASE")
sorted_devices[t][i].set_mode = "decrease"
print(sorted_devices[t][i].mec_name)
mec[previous_index].custom_resource_adjustment(
sorted_devices[t][i], t)
mec[previous_index].save_resource(t)
sorted_devices[t][i].set_mode = "add"
sorted_devices[t][i]._lost_flag = True
# ある時刻tのMECに一時的に保存していた割り当てたデバイスをコピーする。
copy_to_mec(mec, save_devices, t)
#-----
# リソース消費量がそれぞれで違う時のテスト用関数を作成する
# 各秒でMECが持っているデバイスのインデックスと数がわかるものとする
sum = 0
mec_sum = 0
having_device_resource_sum = 0
for t in range(system_end_time):
# print("time:", t)
for m in range(mec_num):
mec_sum = mec_sum + mec[m]._resource_per_second[t]
if mec[m]._having_devices[t] is not None:
# print("check", mec[m]._having_devices[t])
device_index = device_index_search(sorted_devices[t],
mec[m]._having_devices[t])
# print(mec[m]._having_devices[t], device_index)
having_device_resource_sum = having_device_resource_sum + device_resource_calc(
sorted_devices[t], device_index)
check_allocation(t, mec_num, MEC_resource, having_device_resource_sum,
mec_sum)
print((mec_num * MEC_resource - having_device_resource_sum), mec_sum)
having_device_resource_sum = 0
sum = 0
mec_sum = 0
# print(sum, (150*100-sum), mec_sum)
# print("resource",resource_sum)
print("system_time: ", system_end_time)
print("MEC_num: ", mec_num)
print("device_num: ", num)
sorted_devices = sorted_devices[0:system_end_time]
maximum = max_hop_search(sorted_devices[-1])
print("max_hop: ", maximum)
minimum = min_hop_search(sorted_devices[-1])
print("min_hop: ", minimum)
average_hop = average_hop_calc(sorted_devices[-1])
print("average_hop: ", average_hop)
reboot_rate = application_reboot_rate(mec, system_end_time)
print("AP reboot rate:", reboot_rate)
max_distance = max_distance_search(sorted_devices[-1])
print("max_distance:", max_distance)
min_distance = min_distance_search(sorted_devices[-1])
print("min_distance:", min_distance)
average_distance = average_distance_calc(sorted_devices[-1])
print("average_distance: ", average_distance)
# for d in range(device_num):
# print(devices[d].hop)
result = [system_end_time]
result.append(mec_num)
result.append(MEC_resource)
result.append(num)
result.append(maximum)
result.append(minimum)
result.append(average_hop)
result.append(reboot_rate)
result.append(max_distance)
result.append(min_distance)
result.append(average_distance)
# 結果をcsvへ書き込み
write_csv(path_w, result)
return average_hop, reboot_rate
def nearest_simulation(system_end_time, MEC_resource, device_num,
device_allocation_method, path_w, how_compare):
# ---
# MECの準備
df = pd.read_csv(
"/home/tomokishiraga/PycharmProjects/simulation/CloudletSimulator/base_station/okayama_kddi.csv",
dtype={
'lon': 'float',
'lat': 'float'
})
server_type = "LTE"
cover_range = 500
n = len(df)
print("Number of MEC server:", n)
mec = [MEC_server(0, 00, " ", 00.00, 00.00, 0, 0)] * n
#MECインスタンスをCSVを元に生成
data_length = len(df)
for index, series in df.iterrows():
mec[index] = MEC_server(MEC_resource, index + 1, server_type,
series["lon"], series["lat"], cover_range,
system_end_time)
#mec = delete_mec(mec)
#MECサーバにAPの情報を付与(乱数を取得し実行可能なAPを設定する)
count = 1
for t in range(data_length):
if count == 1:
mec[t]._app_ver = [1, 2]
count = 2
elif count == 2:
mec[t]._app_ver = [1, 3]
count = 3
else:
mec[t]._app_ver = [2, 3]
count = 1
mec_num = len(mec)
#print("MECs", mec_num)
# 集約局を対応するMECに設定する
set_aggregation_station(mec)
# 到着順
if device_allocation_method == 0:
if how_compare == "hop":
d = open(
'/home/tomokishiraga/PycharmProjects/simulation/CloudletSimulator/dataset/device.clone_binaryfile2',
'rb')
else:
d = open(
'/home/tomokishiraga/PycharmProjects/simulation/CloudletSimulator/dataset/device.clone_binaryfile',
'rb')
devices = pickle.load(d)
devices = devices[0:device_num]
num = len(devices)
sum = 0
for i in range(num):
devices[i].startup_time = float(
devices[i].plan[0].time) # 各デバイスの起動時間を設定する
devices[i].set_congestion_status(system_end_time)
devices[i].set_MEC_distance(len(df))
devices[i]._first_flag = True
devices[i]._allocation_plan = [None] * system_end_time
sum = sum + devices[i].use_resource
#print(sum)
# 順序をシャッフル(各時間ごとに到着順をランダムで決める)
random.shuffle(devices)
sorted_devices = [devices] * system_end_time
for t in range(system_end_time):
random.shuffle(devices)
sorted_devices[t] = devices
# リソース順
elif device_allocation_method == 1:
if how_compare == "hop":
d = open(
'/home/tomokishiraga/PycharmProjects/simulation/CloudletSimulator/dataset/device.clone_binaryfile2',
'rb')
else:
d = open(
'/home/tomokishiraga/PycharmProjects/simulation/CloudletSimulator/dataset/device.clone_binaryfile',
'rb')
devices = pickle.load(d)
devices = devices[0:device_num]
num = len(devices)
devices = reverse_resource_sort(devices)
for i in range(num):
devices[i].startup_time = float(
devices[i].plan[0].time) # 各デバイスの起動時間を設定する
devices[i].set_congestion_status(system_end_time)
devices[i].set_MEC_distance(len(df))
devices[i]._first_flag = True
sorted_devices = [devices] * system_end_time #デバイスをリソース順にソートする
# 混雑度順
else:
# 混雑度計算
# traffic_congestion(mec, devices, system_end_time, 1000)
if how_compare == "hop":
cd = open(
'/home/tomokishiraga/PycharmProjects/simulation/CloudletSimulator/script/normal/device_compare/congestion_checked_devices2.binaryfile',
'rb')
else:
cd = open(
'/home/tomokishiraga/PycharmProjects/simulation/CloudletSimulator/script/normal/device_compare/congestion_checked_devices1.binaryfile',
'rb')
cd = pickle.load(cd)
devices = cd
num = len(devices)
#print("device_num", num)
# 混雑度順で毎秒ごとのdevicesをソートする
sorted_devices = devices_ap_congestion_sort(devices, system_end_time)
# ----------------------------------------------------------------------------------------------------------------------------------
# ここからメインの処理
for t in range(system_end_time):
#print("[TIME:", t, "]")
# ある時刻tのMECに割り当てらえたデバイス名を一時的に保存する用の変数
save_devices = [None] * mec_num
for i in range(num):
#print("---new device---", sorted_devices[t][i].name)
# plan_indexがデバイスの稼働時間外なら処理をスキップ
if (check_plan_index(sorted_devices[t][i].plan_index,
len(sorted_devices[t][i].plan)) == False):
#print("skip")
continue
# plan_indexが稼働時間内なら処理開始
if check_between_time(sorted_devices[t][i], t) == True:
#print(sorted_devices[t][i].plan_index)
# 最近傍割り当て処理
device_flag, allocation_MEC_name = nearest_search(
sorted_devices[t][i], mec, sorted_devices[t][i].plan_index,
cover_range, t)
# 最近傍割り当てが成功したら表示する
if device_flag == True:
# deviceが直前で割り当てたMECのインデックスを取得
mec_index = search_mec_index(mec, allocation_MEC_name)
# print("device:", sorted_devices[t][i].name, ", use_resource:", sorted_devices[t][i].use_resource, "--->", "MEC_ID:", mec[mec_index].name, ", index:", i)
# print(sorted_devices[t][i].mec_name, mec[mec_index].resource)
# print(mec_index, len(save_devices))
# なぜindexがmec_indexなの？ <- mec用のリストだから
if save_devices[
mec_index] == None: #ある時刻tにMECに割り当てたデバイス名を保存
save_devices[mec_index] = [sorted_devices[t][i].name]
else:
save_devices[mec_index].append(
sorted_devices[t][i].name) #デバイス名を追加
# ---
# print(t, mec_index, index)
# 実行時間外の時
#else:
#デバイスがMECを見つけられないかった時
#print(devices[i].name)
#print("NOT FIND")
# plan_indexをインクリメント
sorted_devices[t][i]._plan_index = sorted_devices[t][
i]._plan_index + 1 #sorted_devicesのインスタンスのplan_indexをインクリメント
else:
# デバイスの稼働時間を超えた時の処理(デバイスが移動し終わって消滅した場合)
# 前回割り当てたMECのリソースをリカバリする。
if sorted_devices[t][i].mec_name != [] and sorted_devices[t][
i]._lost_flag == False: #deviceを割り当てていたMECの名前が空でなく、lost_flag == False(割り当て完了の意味)
previous_index = search_mec_index(
mec, sorted_devices[t]
[i].mec_name) #deviceを割り当ててているMECの名前からインデックスを取得
#print("DECREASE")
sorted_devices[t][
i].set_mode = "decrease" #移動し終わったデバイスのmodeを変更
#print(sorted_devices[t][i].mec_name)
mec[previous_index].custom_resource_adjustment(
sorted_devices[t][i], t) #MECのリソースを調整(増やす)
mec[previous_index].save_resource(
t
) #時刻tにおけるリソースの状態を保存するメソッド:resource_per_second[time]に保存
sorted_devices[t][i].set_mode = "add" #初期値に更新
sorted_devices[t][i]._lost_flag = True #初期値に更新
# ある時刻tのMECに一時的に保存していた割り当てたデバイスをコピーする。
copy_to_mec(mec, save_devices,
t) #having_devicesに(time,save_devices[])を追加
#-----------------------------------------------------------------------------------------------------------------
# リソース消費量がそれぞれで違う時のテスト用関数を作成する
# 各秒でMECが持っているデバイスのインデックスと数がわかるものとする
sum = 0
mec_sum = 0 #mecのリソース容量の合計
having_device_resource_sum = 0 #
for t in range(system_end_time):
# print("time:", t)
#1つ目のMECから順に
for m in range(mec_num):
mec_sum = mec_sum + mec[m]._resource_per_second[
t] #resource_per_second[t]は時刻tにおけるリソースの状態
if mec[m]._having_devices[t] is not None: #時刻tに割り当てたデバイスが空でなければ
# print("check", mec[m]._having_devices[t])
device_index = device_index_search(
sorted_devices[t],
mec[m]._having_devices[t]) #割り当てたデバイスのインデックスを取得
# print(mec[m]._having_devices[t], device_index)
having_device_resource_sum = having_device_resource_sum + device_resource_calc(
sorted_devices[t], device_index) #要求リソース量の和を計算
#ある時刻tのMECへの割り当てができているかを確認するメソッド
check_allocation(t, mec_num, MEC_resource, having_device_resource_sum,
mec_sum)
#print((mec_num * MEC_resource - having_device_resource_sum), mec_sum)
sum = 0
mec_sum = 0
having_device_resource_sum = 0
# print(sum, (150*100-sum), mec_sum)
# print("resource",resource_sum)
print("system_time: ", system_end_time)
print("MEC_num: ", mec_num)
print("device_num: ", num)
sorted_devices = sorted_devices[0:system_end_time]
maximum = max_hop_search(sorted_devices[-1])
print("max_hop: ", maximum)
minimum = min_hop_search(sorted_devices[-1])
print("min_hop: ", minimum)
average_hop = average_hop_calc(sorted_devices[-1])
print("average_hop: ", average_hop)
reboot_rate = application_reboot_rate(mec, system_end_time)
print("AP reboot rate:", reboot_rate)
max_distance = max_distance_search(sorted_devices[-1])
print("max_distance:", max_distance)
min_distance = min_distance_search(sorted_devices[-1])
print("min_distance:", min_distance)
average_distance = average_distance_calc(sorted_devices[-1])
print("average_distance: ", average_distance)
# for d in range(device_num):
# print(devices[d].hop)
result = [system_end_time]
result.append(mec_num)
result.append(MEC_resource)
result.append(num)
result.append(maximum)
result.append(minimum)
result.append(average_hop)
result.append(reboot_rate)
result.append(max_distance)
result.append(min_distance)
result.append(average_distance)
# 結果をcsvへ書き込み
write_csv(path_w, result)
return average_hop, reboot_rate
resource_sum = 0
having_device_resource_sum = 0
for t in range(system_end_time):
#print("time:", t)
for m in range(mec_num):
#if t == 97:
#print("MEC_ID:", mec[m].name, ", having devices:", mec[m]._having_devices[t], mec[m]._having_devices_count[t],
#", mec_resouce:", mec[m]._resource_per_second[t], ", current time:", t)
#resource_sum = resource_sum + mec[m]._having_devices_count[t]
#sum = sum + mec[m]._having_devices_count[t]
#mec_sum = mec_sum + mec[m]._resource_per_second[t]
#sum = sum + mec[m]._having_devices_count[t]
mec_sum = mec_sum + mec[m]._resource_per_second[t]
if mec[m]._having_devices[t] is not None:
#print("check", mec[m]._having_devices[t])
device_index = device_index_search(sorted_devices[t],
mec[m]._having_devices[t])
#print(mec[m]._having_devices[t], device_index)
having_device_resource_sum = having_device_resource_sum + device_resource_calc(
sorted_devices[t], device_index)
check_allocation(t, mec_num, MEC_resource, having_device_resource_sum,
mec_sum)
print((mec_num * MEC_resource - having_device_resource_sum), mec_sum)
having_device_resource_sum = 0
sum = 0
mec_sum = 0
#print(sum, (150*100-sum), mec_sum)
#print("resource",resource_sum)
print("system_time: ", system_end_time)
print("MEC_num: ", mec_num)
print("device_num: ", num)