Distance-Based Routing Strategy for Traffic Transport in Spatial Networks

Wei Huang,Xi Yang,Xiang Pan,Jianhua Zhang

doi:10.1155/2013/879651

Abstract

It is well known that routing strategies based on global topological information is not a good choice for the enhancement of traffic throughput in large-scale networks due to the heavy communication cost. On the contrary, acquiring spatial information, such as spatial distances among nodes, is more feasible. In this paper, we propose a novel distance-based routing strategy in spatial scale-free networks, called LDistance strategy. The probability of establishing links among nodes obeys the power-law in the spatial network under study. Compared with the LDegree strategy (Wang et al., 2006) and the mixed strategy (a strategy combining both greedy routing strategy and random routing strategy), results show that our proposed LDistance strategy can further enhance traffic capacity. Besides, the LDistance strategy can also achieve a much shorter delivering time than the LDegree strategy. Analyses reveal that the superiority of our strategy is mainly due to the interdependent relationship between topological and spatial characteristics in spatial scale-free networks. Furthermore, along transporting path in the LDistance strategy, the spatial distance to destination decays more rapidly, and the degrees of routers are higher than those in the LDegree strategy.

Highlights

In the last few years, the analysis and modelling of dynamics in networked systems have attracted much attention in the field of theoretic physics [1,2,3]
The main motivation of this work stems from the scalability difficulty encountered in real large-size communication networks such as the Internet and the high-way network
We propose a novel routing strategy, called the LDistance strategy, which is based on the information of spatial distances among nodes

Summary

Introduction

In the last few years, the analysis and modelling of dynamics in networked systems have attracted much attention in the field of theoretic physics [1,2,3]. In [24], the authors pointed out that the greedy searching in scale-free networks with strong clustering and power-law node degree distribution γ < 3 find its path with the average scaling as ln ln N, which is the same as the shortest path length These reports validate that the information of spatial distance can effectively improve searching efficiency in spatial scale-free networks. In this paper, we propose a novel routing strategy based on the information of spatial distance, to enhance transport efficiency in spatial scale-free networks.

Model Description

Discussion