| # -*- Mode:python; c-file-style:"gnu"; indent-tabs-mode:nil -*- */ |
| # |
| # Copyright (C) 2015-2020, The University of Memphis |
| # |
| # This file is part of Mini-NDN. |
| # See AUTHORS.md for a complete list of Mini-NDN authors and contributors. |
| # |
| # Mini-NDN is free software: you can redistribute it and/or modify |
| # it under the terms of the GNU General Public License as published by |
| # the Free Software Foundation, either version 3 of the License, or |
| # (at your option) any later version. |
| # |
| # Mini-NDN is distributed in the hope that it will be useful, |
| # but WITHOUT ANY WARRANTY; without even the implied warranty of |
| # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| # GNU General Public License for more details. |
| # |
| # You should have received a copy of the GNU General Public License |
| # along with Mini-NDN, e.g., in COPYING.md file. |
| # If not, see <http://www.gnu.org/licenses/>. |
| |
| # IMPORTANT! This feature is in highly experimental phase and may go several changes |
| # in future |
| |
| ''' |
| This module will compute link state, hyperbolic and geohyperbolic |
| routes and their costs from the given Mini-NDN topology |
| ''' |
| |
| import sys |
| import heapq |
| from math import sin, cos, sinh, cosh, acos, acosh |
| import json |
| import operator |
| from collections import defaultdict |
| from tqdm import tqdm |
| from joblib import Parallel, delayed |
| |
| from mininet.log import info, debug, error, warn |
| from minindn.helpers.nfdc import Nfdc as nfdc |
| |
| UNKNOWN_DISTANCE = -1 |
| HYPERBOLIC_COST_ADJUSTMENT_FACTOR = 1000 |
| |
| def dijkstra(graph, start, end, ignoredNode=None): |
| """ |
| Compute shortest path and cost from a given source to a destination |
| using Dijkstra algorithm |
| |
| :param Graph graph: given network topology/graph |
| :param Start start: source node in a given network graph/topology |
| :end End end: destination node in a given network graph/topology |
| :param Node ignoredNode: node to ignore computing shortest path from |
| """ |
| queue = [(0, start, [])] |
| seen = set() |
| while True: |
| (cost, v, path) = heapq.heappop(queue) |
| if v not in seen: |
| path = path + [v] |
| seen.add(v) |
| if v == end: |
| debug("Distance from {} to {} is {}".format(start, end, cost)) |
| return cost, path |
| for (_next, c) in graph[v].items(): |
| if _next != ignoredNode: # Ignore path going via ignoreNode |
| heapq.heappush(queue, (cost + c, _next, path)) |
| |
| if not queue: # return if no path exist from source - destination except via ignoreNode |
| debug("Distance from {} to {} is {}".format(start, end, cost)) |
| return cost, None |
| |
| def calculateAngularDistance(angleVectorI, angleVectorJ): |
| """ |
| For hyperbolic/geohyperbolic routing algorithm, this function computes angular distance between |
| two nodes. A node can have two or more than two angular coordinates. |
| |
| :param AngleVectorI angleVectorI: list of angular coordinate of a give node I |
| :param AngleVectorJ angleVectorJ: list of angular coordinate of a give node J |
| |
| ref: https://en.wikipedia.org/wiki/N-sphere#Spherical_coordinates |
| |
| """ |
| innerProduct = 0.0 |
| if len(angleVectorI) != len(angleVectorJ): |
| error("Angle vector sizes do not match") |
| return UNKNOWN_DISTANCE |
| |
| # Calculate x0 of the vectors |
| x0i = cos(angleVectorI[0]) |
| x0j = cos(angleVectorJ[0]) |
| |
| # Calculate xn of the vectors |
| xni = sin(angleVectorI[len(angleVectorI) - 1]) |
| xnj = sin(angleVectorJ[len(angleVectorJ) - 1]) |
| |
| # Do the aggregation of the (n-1) coordinates (if there is more than one angle) |
| # i.e contraction of all (n-1)-dimensional angular coordinates to one variable |
| for k in range(0, len(angleVectorI)-1): |
| xni *= sin(angleVectorI[k]) |
| xnj *= sin(angleVectorJ[k]) |
| |
| innerProduct += (x0i * x0j) + (xni * xnj) |
| |
| if len(angleVectorI) > 1: |
| for m in range(1, len(angleVectorI)): |
| # Calculate euclidean coordinates given the angles and assuming R_sphere = 1 |
| xmi = cos(angleVectorI[m]) |
| xmj = cos(angleVectorJ[m]) |
| for l in range(0, m): |
| xmi *= sin(angleVectorI[l]) |
| xmj *= sin(angleVectorJ[l]) |
| |
| innerProduct += xmi * xmj |
| |
| # ArcCos of the inner product gives the angular distance |
| # between two points on a d-dimensional sphere |
| angularDist = acos(innerProduct) |
| debug("Angular distance from {} to {} is {}".format(angleVectorI, angleVectorJ, angularDist)) |
| return angularDist |
| |
| def getHyperbolicDistance(sourceNode, destNode): |
| """ |
| Return hyperbolic or geohyperbolic distance between two nodes. The distance is computed |
| on the basis of following algorithm/mathematics |
| ref: https://en.wikipedia.org/wiki/Hyperbolic_geometry |
| """ |
| r1 = [key for key in sourceNode][0] |
| r2 = [key for key in destNode][0] |
| zeta = 1.0 |
| dtheta = calculateAngularDistance(sourceNode[r1], destNode[r2]) |
| hyperbolicDistance = (1./zeta) * acosh(cosh(zeta * r1) * cosh(zeta * r2) -\ |
| sinh(zeta * r1) * sinh(zeta * r2) * cos(dtheta)) |
| |
| debug("Distance from {} to {} is {}".format(sourceNode, destNode, hyperbolicDistance)) |
| return hyperbolicDistance |
| |
| class _CalculateRoutes(object): |
| """ |
| Creates a route calculation object, which is used to compute routes from a node to |
| every other nodes in a given topology topology using hyperbolic or geohyperbolic |
| routing algorithm |
| |
| :param NetObject netObj: Mininet net object |
| :param RoutingType routingType: (optional) Routing algorithm, link-state or hr etc |
| """ |
| def __init__(self, netObj, routingType): |
| self.adjacenctMatrix = defaultdict(dict) |
| self.nodeDict = defaultdict(dict) |
| self.routingType = routingType |
| self.isHrConfigValid = True |
| for host in netObj.hosts: |
| if 'radius' in host.params['params']: |
| radius = float(host.params['params']['radius']) |
| else: |
| self.isHrConfigValid = False |
| radius = 0.0 |
| if 'angle' in host.params['params']: |
| angles = [float(x) for x in host.params['params']['angle'].split(',')] |
| else: |
| self.isHrConfigValid = False |
| angles = [0.0] |
| self.nodeDict[host.name][radius] = angles |
| for link in netObj.topo.links(withInfo=True): |
| linkDelay = int(link[2]['delay'].replace("ms", "")) |
| self.adjacenctMatrix[link[0]][link[1]] = linkDelay |
| self.adjacenctMatrix[link[1]][link[0]] = linkDelay |
| |
| def getNestedDictionary(self): |
| return defaultdict(self.getNestedDictionary) |
| |
| def getRoutes(self, nFaces): |
| resultMatrix = self.getNestedDictionary() |
| routes = defaultdict(list) |
| |
| if self.routingType == "link-state": |
| if nFaces == 1: |
| resultMatrix = self.computeDijkastra() # only best routes. |
| else: |
| resultMatrix = self.computeDijkastraAll() # all possible routes |
| elif self.routingType == "hr": |
| if self.isHrConfigValid == True: |
| # Note: For hyperbolic, only way to find the best routes is by |
| # computing all possible routes and getting the best one. |
| resultMatrix = self.computeHyperbolic() |
| else: |
| warn('Hyperbolic coordinates in topology file are either missing or misconfigured.\n') |
| warn('Check that each node has one radius value and one or two angle value(s).\n') |
| return None |
| |
| for node in resultMatrix: |
| for destinationNode in resultMatrix[node]: |
| # Sort node - destination via neighbor based on their cost |
| tempDict = resultMatrix[node][destinationNode] |
| shortedTempDict = sorted(tempDict.items(), key=operator.itemgetter(1)) |
| # nFaces option gets n-best faces based on shortest distance, default is all |
| if nFaces == 0: |
| for item in shortedTempDict: |
| viaNeighbor = item[0] |
| cost = item[1] |
| routes[node].append([destinationNode, str(cost), viaNeighbor]) |
| else: |
| for index, item in enumerate(shortedTempDict): |
| if index >= nFaces: |
| break |
| viaNeighbor = item[0] |
| cost = item[1] |
| routes[node].append([destinationNode, str(cost), viaNeighbor]) |
| |
| debug("-routes----", routes) |
| return routes |
| |
| def getNodeNames(self): |
| return [k for k in self.nodeDict] |
| |
| def computeHyperbolic(self): |
| paths = self.getNestedDictionary() |
| nodeNames = self.getNodeNames() |
| for node in self.nodeDict: |
| neighbors = [k for k in self.adjacenctMatrix[node]] |
| for viaNeighbor in neighbors: |
| others = [x for x in nodeNames if x not in [viaNeighbor, node]] |
| paths[node][viaNeighbor][viaNeighbor] = 0 |
| # Compute distance from neighbors to no-neighbors |
| for destinationNode in others: |
| hyperbolicDistance = getHyperbolicDistance(self.nodeDict[viaNeighbor], |
| self.nodeDict[destinationNode]) |
| hyperbolicCost = int(HYPERBOLIC_COST_ADJUSTMENT_FACTOR \ |
| * round(hyperbolicDistance, 6)) |
| paths[node][destinationNode][viaNeighbor] = hyperbolicCost |
| debug("Shortest Distance Matrix: {}".format(json.dumps(paths))) |
| return paths |
| |
| def computeDijkastra(self): |
| """ |
| Dijkstra computation: Compute all the shortest paths from nodes to the destinations. |
| And fills the distance matrix with the corresponding source to destination cost |
| """ |
| distanceMatrix = self.getNestedDictionary() |
| nodeNames = self.getNodeNames() |
| for node in nodeNames: |
| others = [x for x in nodeNames if x not in [node]] |
| for destinationNode in others: |
| cost, path = dijkstra(self.adjacenctMatrix, node, destinationNode) |
| viaNeighbor = path[1] |
| distanceMatrix[node][destinationNode][viaNeighbor] = cost |
| |
| debug("Shortest Distance Matrix: {}".format(json.dumps(distanceMatrix))) |
| return distanceMatrix |
| |
| def computeDijkastraAll(self): |
| """ |
| Multi-path Dijkastra computation: Compute all the shortest paths from nodes to the |
| destinations via all of its neighbors individually. And fills the distanceMatrixViaNeighbor |
| with a corresponding source to its destination cost |
| |
| Important: distanceMatrixViaNeighbor represents the shortest distance from a source to a |
| destination via specific neighbors |
| """ |
| distanceMatrixViaNeighbor = self.getNestedDictionary() |
| nodeNames = self.getNodeNames() |
| for node in nodeNames: |
| neighbors = [k for k in self.adjacenctMatrix[node]] |
| for viaNeighbor in neighbors: |
| directCost = self.adjacenctMatrix[node][viaNeighbor] |
| distanceMatrixViaNeighbor[node][viaNeighbor][viaNeighbor] = directCost |
| others = [x for x in nodeNames if x not in [viaNeighbor, node]] |
| for destinationNode in others: |
| nodeNeighborCost = self.adjacenctMatrix[node][viaNeighbor] |
| # path variable is not used for now |
| cost, path = dijkstra(self.adjacenctMatrix, viaNeighbor, destinationNode, node) |
| if cost != 0 and path != None: |
| totalCost = cost + nodeNeighborCost |
| distanceMatrixViaNeighbor[node][destinationNode][viaNeighbor] = totalCost |
| |
| debug("Shortest Distance Matrix: {}".format(json.dumps(distanceMatrixViaNeighbor))) |
| return distanceMatrixViaNeighbor |
| |
| class NdnRoutingHelper(object): |
| """ |
| This module is a helper class which helps to create face and register routes |
| to NFD from a given node to all of its neighbors. |
| |
| :param NetObject netObject: Mininet net object |
| :param FaceType faceType: UDP, Ethernet etc. |
| :param Routing routingType: (optional) Routing algorithm, link-state or hr etc |
| |
| """ |
| def __init__(self, netObject, faceType=nfdc.PROTOCOL_UDP, routingType="link-state"): |
| self.net = netObject |
| self.faceType = faceType |
| self.routingType = routingType |
| self.routes = [] |
| self.namePrefixes = {host_name.name: [] for host_name in self.net.hosts} |
| self.routeObject = _CalculateRoutes(self.net, self.routingType) |
| |
| def globalRoutingHelperHandler(self): |
| info('Creating faces and adding routes to FIB\n') |
| |
| res = Parallel(n_jobs=-1, require='sharedmem', |
| prefer="threads")(delayed(self.addNodeRoutes)(host) for host in tqdm(self.net.hosts)) |
| |
| info('Processed all the routes to NFD\n') |
| |
| def addNodeRoutes(self, node): |
| """ |
| Create faces to neighbors and add all routes for one node |
| |
| :param Node node: Node from net object |
| """ |
| neighborIPs = self.getNeighbor(node) |
| self.createFaces(node, neighborIPs) |
| self.routeAdd(node, neighborIPs) |
| |
| def addOrigin(self, nodes, prefix): |
| """ |
| Add prefix/s as origin on node/s |
| |
| :param Prefix prefix: Prefix that is originated by node/s (as producer) for this prefix |
| :param Nodes nodes: List of nodes from net object |
| """ |
| for node in nodes: |
| if not node.name in self.namePrefixes: |
| self.namePrefixes[node.name] = [] |
| self.namePrefixes[node.name] += prefix |
| |
| def calculateNPossibleRoutes(self, nFaces=0): |
| """ |
| By default, calculates all possible routes i.e. routes via all the faces of a node. |
| pass nFaces if want to compute routes via n number of faces. e.g. 2. For larger topology |
| the computation might take huge amount of time. |
| |
| :param int nFaces: (optional) number of faces to consider while computing routes. Default |
| i.e. nFaces = 0 will compute all possible routes |
| |
| """ |
| self.routes = self.routeObject.getRoutes(nFaces) |
| if self.routes is not None: |
| info('Route computation completed\n') |
| self.globalRoutingHelperHandler() |
| else: |
| warn('Route computation failed\n') |
| self.net.stop() |
| sys.exit(1) |
| |
| def calculateRoutes(self): |
| # Calculate shortest path for every node |
| self.calculateNPossibleRoutes(nFaces=1) |
| |
| def createFaces(self, node, neighborIPs): |
| for ip in neighborIPs.values(): |
| nfdc.createFace(node, ip, self.faceType) |
| |
| def routeAdd(self, node, neighborIPs): |
| """ |
| Add route from a node to its neighbors for each prefix/s advertised by destination node |
| |
| :param Node node: source node (Mininet net.host) |
| :param IP neighborIPs: IP addresses of neighbors |
| """ |
| neighbors = self.routes[node.name] |
| for route in neighbors: |
| destination = route[0] |
| cost = int(route[1]) |
| nextHop = route[2] |
| defaultPrefix = "/ndn/{}-site/{}".format(destination, destination) |
| prefixes = [defaultPrefix] + self.namePrefixes[destination] |
| for prefix in prefixes: |
| # Register routes to all the available destination name prefix/s |
| faceID = nfdc.createFace(node, neighborIPs[nextHop]) |
| nfdc.registerRoute(node, prefix, faceID, cost=cost) |
| @staticmethod |
| def getNeighbor(node): |
| # Nodes to IP mapping |
| neighborIPs = defaultdict() |
| for intf in node.intfList(): |
| link = intf.link |
| if link: |
| node1, node2 = link.intf1.node, link.intf2.node |
| |
| if node1 == node: |
| other = node2 |
| ip = other.IP(str(link.intf2)) |
| else: |
| other = node1 |
| ip = other.IP(str(link.intf1)) |
| |
| # Used later to create faces |
| neighborIPs[other.name] = ip |
| return neighborIPs |