From de0560d538d8a1936bc42f4bfdf8793c1832b0f6 Mon Sep 17 00:00:00 2001 From: Marcin Kostrzewski Date: Tue, 21 Jun 2022 17:00:18 +0200 Subject: [PATCH] Add weighted star experiment --- network_attack_propagation.py | 93 +++++++++++++++++++++++------------ 1 file changed, 62 insertions(+), 31 deletions(-) diff --git a/network_attack_propagation.py b/network_attack_propagation.py index a069a1c..9631f63 100644 --- a/network_attack_propagation.py +++ b/network_attack_propagation.py @@ -51,6 +51,9 @@ class Graph: nodes.add(edge.node_b) return nodes + def get_edges_with_node(self, node: Node): + return filter(lambda ed: ed.has_node(node), self.edges) + def clear_attacked(self) -> None: for edge in self.edges: edge.node_a.under_attack = False @@ -61,7 +64,7 @@ class Graph: :param node: Node to search for :return: An array of tuples (node, weight) """ - edges_with_node = filter(lambda ed: ed.has_node(node), self.edges) + edges_with_node = self.get_edges_with_node(node) nodes = set() for e in edges_with_node: if e.node_a is node: @@ -164,7 +167,7 @@ def bus_network(n=30, infected_idx=0) -> tuple[Graph, float, int]: return network, degree_avg(edges), n -def star_network(cluster_count=5, starsize=6) -> tuple[Graph, float, int]: +def star_network(cluster_count=5, starsize=6, use_weights=False) -> tuple[Graph, float, int]: node_count = cluster_count + cluster_count * starsize + 1 nodes = [Node() for _ in range(node_count)] nodes[starsize-1].is_infected = True @@ -172,7 +175,8 @@ def star_network(cluster_count=5, starsize=6) -> tuple[Graph, float, int]: edges = [] for x in range(cluster_count): center_node = x * starsize + x - edges += [Edge(nodes[center_node], nodes[i], 1.0) for i in range(center_node + 1, center_node + starsize + 1)] + vulnerability = 1.0 if not use_weights else max(1.0, starsize) + edges += [Edge(nodes[center_node], nodes[i], vulnerability) for i in range(center_node + 1, center_node + starsize + 1)] edges.append(Edge(nodes[-1], nodes[center_node], 1.0)) network = Graph() @@ -201,48 +205,75 @@ def summary(average_degrees: list[float], propagation_speeds: list[float]) -> No plt.show() -def experiment(network, avg_degree, node_count, iteration): +def bus_experiment(): degrees = [] speeds = [] - do_graph_animation(f'bus{iteration}.gif', network, 90, nx.spiral_layout) - speeds.append(node_count / network.rounds_survived) - degrees.append(avg_degree) - print(f"\n{node_count} NODE BUS") - print(f"average degree = {avg_degree}") - print(f"propagation speed = {round(speeds[-1], 2)}") - print(f"bus_{iteration} rounds survived = {network.rounds_survived + 1}") + sizes = [0, 8, 15] + for i in sizes: + bus, bus_avg_degree, node_count = bus_network(20 + i) + do_graph_animation('bus{i}.gif', bus, 90, nx.spring_layout) + speeds.append(bus.rounds_survived / node_count) + degrees.append(bus_avg_degree) + print(f"\n{node_count} NODE bus") + print(f"average degree = {bus_avg_degree}") + print(f"propagation speed = {round(speeds[-1], 2)}") + print(f"bus{i} rounds survived = {bus.rounds_survived + 1}") + + summary(degrees, speeds) + +def ring_experiment(): + degrees = [] + speeds = [] + sizes = [0, 8, 15] + for i in sizes: + ring, ring_avg_degree, node_count = ring_network(20 + i) + do_graph_animation('bus{i}.gif', ring, 90, nx.circular_layout) + speeds.append(ring.rounds_survived / node_count) + degrees.append(ring_avg_degree) + print(f"\n{node_count} NODE ring") + print(f"average degree = {ring_avg_degree}") + print(f"propagation speed = {round(speeds[-1], 2)}") + print(f"ring{i} rounds survived = {ring.rounds_survived + 1}") + +def star_experiment(): + degrees = [] + speeds = [] + sizes = range(0, 8, 2) + for i in sizes: + star, star_avg_degree, node_count = star_network(cluster_count=3 + i, starsize=3 + i) + do_graph_animation(f'star{i}.gif', star, 120, nx.kamada_kawai_layout) + speeds.append(star.rounds_survived / node_count) + degrees.append(star_avg_degree) + print(f"\n{node_count} NODE STAR") + print(f"average degree = {star_avg_degree}") + print(f"propagation speed = {round(speeds[-1], 2)}") + print(f"star{i} rounds survived = {star.rounds_survived + 1}") summary(degrees, speeds) -def bus_experiment(): - sizes = [0, 8, 15] - for i in sizes: - bus, bus_avg_degree, node_count = bus_network(20 + i) - experiment(bus, bus_avg_degree, node_count, i) - - -def ring_experiment(): - sizes = [0, 8, 15] - for i in sizes: - ring, ring_avg_degree, node_count = ring_network(20 + i) - experiment(ring, ring_avg_degree, node_count, i) - - -def star_experiment(): - sizes = [0, 8, 15] - for i in sizes: - star, star_avg_degree, node_count = star_network(cluster_count=3 + i, starsize=3 + i) - experiment(star, star_avg_degree, node_count, i) - def weighted_star_experiment(): + degrees = [] + speeds = [] + sizes = range(0, 8, 2) + for i in sizes: + star, star_avg_degree, node_count = star_network(cluster_count=3 + i, starsize=3 + i, use_weights=True) + do_graph_animation(f'star_weighted{i}.gif', star, 120, nx.kamada_kawai_layout) + speeds.append(star.rounds_survived / node_count) + degrees.append(star_avg_degree) + print(f"\n{node_count} NODE STAR") + print(f"average degree = {star_avg_degree}") + print(f"propagation speed = {round(speeds[-1], 2)}") + print(f"star{i} rounds survived = {star.rounds_survived + 1}") + summary(degrees, speeds) def main(): bus_experiment() ring_experiment() star_experiment() + weighted_star_experiment() if __name__ == "__main__":