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"""Module Graph of kytos/pathfinder Kytos Network Application.""" |
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from kytos.core import log |
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try: |
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import networkx as nx |
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from networkx.exception import NodeNotFound, NetworkXNoPath |
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except ImportError: |
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PACKAGE = 'networkx>=2.2' |
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log.error(f"Package {PACKAGE} not found. Please 'pip install {PACKAGE}'") |
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from itertools import combinations |
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class Filter: |
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def __init__(self, filter_type, filter_function): |
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self._filter_type = filter_type |
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self._filter_fun = filter_function |
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def run(self,value, items): |
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if isinstance(value, self._filter_type): |
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fun0 = self._filter_fun(value) |
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return filter(fun0, items) |
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else: |
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raise TypeError(f"Expected type: {self._filter_type}") |
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class KytosGraph: |
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"""Class responsible for the graph generation.""" |
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def __init__(self): |
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self.graph = nx.Graph() |
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self._filter_fun_dict = {} |
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def filterLEQ(metric):# Lower values are better |
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return lambda x: (lambda y: y[2].get(metric,x) <= x) |
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def filterGEQ(metric):# Higher values are better |
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return lambda x: (lambda y: y[2].get(metric,x) >= x) |
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def filterEEQ(metric):# Equivalence |
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return lambda x: (lambda y: y[2].get(metric,x) == x) |
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self._filter_fun_dict["ownership"] = Filter(str,filterEEQ("ownership")) |
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self._filter_fun_dict["bandwidth"] = Filter((int,float),filterGEQ("bandwidth")) |
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self._filter_fun_dict["priority"] = Filter((int,float),filterGEQ("priority")) |
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self._filter_fun_dict["reliability"] = Filter((int,float),filterGEQ("reliability")) |
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self._filter_fun_dict["utilization"] = Filter((int,float),filterLEQ("utilization")) |
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self._filter_fun_dict["delay"] = Filter((int,float),filterLEQ("delay")) |
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self._path_fun = nx.all_shortest_paths |
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def set_path_fun(self, path_fun): |
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self._path_fun = path_fun |
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def clear(self): |
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"""Remove all nodes and links registered.""" |
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self.graph.clear() |
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def update_topology(self, topology): |
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"""Update all nodes and links inside the graph.""" |
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self.graph.clear() |
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self.update_nodes(topology.switches) |
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self.update_links(topology.links) |
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def update_nodes(self, nodes): |
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"""Update all nodes inside the graph.""" |
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for node in nodes.values(): |
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try: |
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self.graph.add_node(node.id) |
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for interface in node.interfaces.values(): |
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self.graph.add_node(interface.id) |
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self.graph.add_edge(node.id, interface.id) |
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except AttributeError: |
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pass |
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def update_links(self, links): |
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"""Update all links inside the graph.""" |
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keys = [] |
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for link in links.values(): |
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if link.is_active(): |
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self.graph.add_edge(link.endpoint_a.id, link.endpoint_b.id) |
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for key, value in link.metadata.items(): |
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keys.append(key) |
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endpoint_a = link.endpoint_a.id |
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endpoint_b = link.endpoint_b.id |
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self.graph[endpoint_a][endpoint_b][key] = value |
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def get_metadata_from_link(self, endpoint_a, endpoint_b): |
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"""Return the metadata of a link.""" |
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return self.graph.edges[endpoint_a, endpoint_b] |
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@staticmethod |
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def _remove_switch_hops(circuit): |
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"""Remove switch hops from a circuit hops list.""" |
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for hop in circuit['hops']: |
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if len(hop.split(':')) == 8: |
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circuit['hops'].remove(hop) |
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def shortest_paths(self, source, destination, parameter=None): |
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"""Calculate the shortest paths and return them.""" |
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try: |
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paths = list(self._path_fun(self.graph, |
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source, destination, parameter)) |
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except (NodeNotFound, NetworkXNoPath): |
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return [] |
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return paths |
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def constrained_flexible_paths(self, source, destination, metrics, flexible_metrics, flexible = None): |
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default_edge_list = self.graph.edges(data=True) |
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default_edge_list = self._filter_edges(default_edge_list,**metrics) |
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default_edge_list = list(default_edge_list) |
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length = len(flexible_metrics) |
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if flexible is None: |
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flexible = length |
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flexible = max(0,flexible) |
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flexible = min(length,flexible) |
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results = [] |
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stop = False |
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for i in range(0,flexible+1): |
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if stop: |
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break |
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y = combinations(flexible_metrics.items(),length-i) |
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for x in y: |
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tempDict = {} |
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for k,v in x: |
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tempDict[k] = v |
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edges = self._filter_edges(default_edge_list,**tempDict) |
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edges = ((u,v) for u,v,d in edges) |
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res0 = self._constrained_shortest_paths(source,destination,edges) |
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if res0 != []: |
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results.append({"paths":res0, "metrics":{**metrics, **tempDict}}) |
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stop = True |
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return results |
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def _constrained_shortest_paths(self, source, destination, edges): |
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paths = [] |
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try: |
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paths = list(self._path_fun(self.graph.edge_subgraph(edges), |
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source, destination)) |
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except NetworkXNoPath: |
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pass |
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except NodeNotFound: |
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if source == destination: |
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if source in self.graph.nodes: |
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paths = [[source]] |
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return paths |
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def _filter_edges(self, edges, **metrics): |
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for metric, value in metrics.items(): |
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fil = self._filter_fun_dict.get(metric, None) |
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if fil != None: |
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try: |
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edges = fil.run(value,edges) |
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except TypeError as err: |
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raise TypeError(f"Error in {metric} filter: {err}") |
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return edges |
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