Optimization of transport protocols with path-length constraints in complex networks

Abstract

We propose a protocol optimization technique that is applicable to both weighted or unweighted graphs. Our aim is to explore by how much a small variation around the Shortest Path or Optimal Path protocols can enhance protocol performance. Such an optimization strategy can be necessary because even though some protocols can achieve very high traffic tolerance levels, this is commonly done by enlarging the path-lengths, which may jeopardize scalability. We use ideas borrowed from Extremal Optimization to guide our algorithm, which proves to be an effective technique. Our method exploits the degeneracy of the paths or their close-weight alternatives, which significantly improves the scalability of the protocols in comparison to Shortest Paths or Optimal Paths protocols, keeping at the same time almost intact the length or weight of the paths. This characteristic ensures that the optimized routing protocols are composed of paths that are quick to traverse, avoiding negative effects in data communication due to path-length increases that can become specially relevant when information losses are present.

Effective usage of global dynamic information for network traffic

“…The routing strategy can be divided into a static strategy and a dynamic strategy. Static strategies [20][21][22][23][24] usually use static information of networks, for example the degree of nodes. One of the most successful static strategies is proposed by Yan et al [25].…”

Maximum transport capacity of a network

“…Path optimization and congestion control are at the core of several communication and logistics applications. In recent years, scientists have explored some efficient routing strategies that can significantly enhance the transport capacity of networks [24][25][26][27].…”

A model to identify urban traffic congestion hotspots in complex networks

“…The Gipps' model and other car-following models [6,7] have evidenced the necessity of modeling traffic flows to improve road network efficiency and also have shown how congestion severely affects the traffic flows. Since ten years ago also the complex networks' community has proposed stylized models to analyze the problem of traffic congestion in networks and design optimal topologies to avoid it [8][9][10][11][12][13][14][15][16][17][18][19][20][21]. The focus of attention of the previous works was the onset of congestion, which corresponds to a critical point in a phase transition, and how it depends on the topology of the network and the routing strategies used.…”