# -*- coding: utf-8 -*-
"""
Created on Wed Feb 26 11:19:38 2020
@author: ali nouruzi
"""
import numpy as np
import random
import sys
import os
import scipy
import networkx as nx
from collections import deque
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam
from matplotlib import pyplot as plt
from timeit import default_timer as timer
number_function=5
number_node=10
The demo data set consists the propagation path distances of AT & T North America Netowork Topology. The geographical node positions (latitude and longitude) along with the adjacency matrix has been found out from International Topology Zoo and the data set has been formed using the available data. This set has been used in Joint localization prolem of Controller and Hypervisor instances in vSDN enebled 5G Network.
This dataset accompanies a paper that discusses the advantages of a 3GPP-compliant service-based architecture platform that demonstrates the concept of cloud-native service orchestration and routing for a media vertical sector application. Cloud-native service orchestration and routing is a complete end-to-end approach that enables virtualisation and management of multiple layers in the OSI model, which provides considerable flexibility and control to achieve delivery of QoS to users in the face of varying demand, at reasonable cost.
