Extended shortest path selection for package routing of complex networks

Fan Ye, Lei Zhang (), Bing-Hong Wang (), Lu Liu () and Xing-Yi Zhang ()
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Fan Ye: Department of Computer Science, Anhui University, Hefei, P. R. China
Lei Zhang: Department of Computer Science, Anhui University, Hefei, P. R. China
Bing-Hong Wang: #x2020;Department of Modern Physics and Nonlinear Science Center, University of Science and Technology of China, Hefei, P. R. China
Lu Liu: #x2225;Computing and Mathematics Department, College of Engineering and Technology, University of Derby, UK
Xing-Yi Zhang: Department of Computer Science, Anhui University, Hefei, P. R. China

International Journal of Modern Physics C (IJMPC), 2017, vol. 28, issue 11, 1-12

Abstract: The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency.

Keywords: Routing algorithm; traffic flow; optimization algorithm; complex network (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1142/S0129183117501297

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