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Studies of Routing Strategy on Complex Networks

Author: WangXianPeng
Tutor: LuHongTao
School: Shanghai Jiaotong University
Course: Computer Software and Theory
Keywords: complex network local information congestion control routing strategy
CLC: N941.4
Type: Master's thesis
Year: 2009
Downloads: 188
Quote: 4
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Abstract


In the information-determined modern society, communication network has become a necessary tool for a successful life. People living with complex networks suffer from the congestion caused by plenty of simultaneous information. Thus, more and more researchers have focused on the analysis and control of network congestion. There have been many previous studies to understand and control traffic congestion on networks, with a basic assumption that the network has a homogeneous structure. However, many real-life communication networks, such as the Internet and the World-Wide-Web, display scale-free degree distribution, thus it is of great interest to study the traffic flow on scale-free networks. At present, great progress has been made in routing strategy. Also there are still many problems to be solved in this field.The primary contributions of this thesis are listed as follows.1) The network model we selected is close to real world network systems. The delivering capability of each node in our model is varied and not the same as previous studies that set this value as a constant.2) Consider the deficiency of current routing strategies, we propose a new local information based routing strategy on a scale-free network. This routing strategy uses only local information of each node for routing and it also incorporates dynamic information of network. All above improvements make our routing strategy can select a properly routing path according to current traffic statues. Simulating results show that our routing strategy outperforms previous local information based routing strategies.Extensive numerical experiments have been done to test the algorithms proposed in this thesis on both computer-simulated networks. The results prove that these algorithms can better solve the problems proposed in this thesis and get more satisfied results.

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CLC: > SCIENCE AND > Journal of Systems Science > Systems,modern systems theory > Large scale system theory
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