This subfield focuses on the study and development of algorithms for optimizing network performance, such as routing protocols and network flow algorithms.
Graph theory: Understanding the mathematical structure that underlies networks and how to represent it using nodes and edges.
Shortest path algorithms: Finding the quickest route through a network, such as Dijkstra's algorithm or Floyd-Warshall algorithm.
Maximum flow algorithms: Determining the maximum amount of flow that can pass through a network, such as Ford-Fulkerson algorithm or Edmonds-Karp algorithm.
Minimum spanning tree algorithms: Finding the subgraph of a network that connects all nodes with minimum total weight, such as Kruskal's algorithm or Prim's algorithm.
Network optimization: Optimizing various network parameters, such as bandwidth or reliability, using algorithms such as the network simplex algorithm or swarm intelligence algorithms.
Network reliability: Analyzing and improving the resilience of networks to failures and attacks, using algorithms such as the Steiner tree algorithm or greedy algorithms.
Network routing: Finding the best path for data packets to travel through a network, using algorithms such as OSPF or BGP.
Network flow control: Managing the flow of data packets in a network to avoid congestion and improve performance, using algorithms such as TCP congestion control or random early detection.
Social network analysis: Analyzing the structure and behavior of social networks, using algorithms such as community detection or influence maximization.
Distributed algorithms: Algorithms that enable network nodes to communicate and coordinate their actions without centralized control, such as the Paxos algorithm or the MapReduce framework.
Dijkstra's algorithm: It is a graph traversal algorithm that finds the shortest path between nodes in a weighted graph.
A* algorithm: A heuristic algorithm that is designed to find the shortest path between two points in a graph or a grid system.
Bellman-Ford algorithm: Used in computing the shortest path between nodes in a weighted graph.
Floyd-Warshall algorithm: Algorithm that computes the shortest paths between all pairs of nodes in a weighted graph.
Prim's algorithm: A greedy algorithm used to find the minimum spanning tree of a connected weighted graph.
Kruskal's algorithm: Another greedy algorithm used to find the minimum spanning tree of a connected weighted graph.
Topological sorting algorithm: A sorting algorithm that sorts the nodes of a graph in a linear order such that for every directed edge from node A to node B, node A appears before node B in the sorted order.
Maximum flow algorithm: Used to find the maximum flow in a network flow graph.
Minimum cut algorithm: Used to find the minimum cut in a network flow graph.
Edmonds-Karp algorithm: A variation of the Ford-Fulkerson algorithm that uses the breadth-first search strategy to find the maximum flow in a network flow graph.
Hopcroft-Karp algorithm: A matching algorithm used to find the maximum cardinality matching in a bipartite graph.
Boyer-Moore algorithm: A string searching algorithm that finds the occurrence of a pattern string in a text string.
Rabin-Karp algorithm: A string searching algorithm that uses hashing to find the occurrence of a pattern string in a text string.
Shannon-Fano algorithm: A lossless data compression algorithm that encodes data by assigning variable-length codes to symbols based on their probability of occurrence.
Huffman coding algorithm: Another lossless data compression algorithm that assigns variable-length codes to symbols based on their frequency of occurrence.