A Distributed Energy-aware Trust Topology Control Algorithm for Service-Oriented Wireless Mesh Networks

2010 ◽  
pp. 276-282 ◽  
Author(s):  
Chuanchuan You ◽  
Tong Wang ◽  
BingYu Zhou ◽  
Hui Dai ◽  
Baolin Sun
Keyword(s):  
Wireless Mesh Networks ◽  
Topology Control ◽  
Control Algorithm ◽  
Mesh Networks ◽  
Distributed Energy ◽  
Energy Aware ◽  
Wireless Mesh ◽  
Service Oriented

Topology control for service-oriented wireless mesh networks

2009 ◽  
Vol 16 (4) ◽  
pp. 64-71 ◽  
Author(s):  
Tao Zhang ◽  
Kun Yang ◽  
Hsiao-Hwa Chen
Keyword(s):  
Wireless Mesh Networks ◽  
Topology Control ◽  
Mesh Networks ◽  
Wireless Mesh ◽  
Service Oriented

scholarly journals A Stackelberg-Game-Based Power Control Algorithm for Wireless Mesh Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yanbing Liu ◽  
Tao Wu ◽  
Jun Huang ◽  
Shousheng Jia
Keyword(s):  
Power Control ◽  
Wireless Mesh Networks ◽  
Control Algorithm ◽  
Large Scale ◽  
Mesh Networks ◽  
Stackelberg Game ◽  
Noncooperative Game ◽  
Destination Node ◽  
Wireless Mesh ◽  
Power Control Algorithm

Wireless mesh networks (WMNs) are a promising networking paradigm for next generation wireless networking system. Power control plays a vital role in WMNs and is realized to be a crucial step toward large-scale WMNs deployment. In this paper, we address the problem of how to allocate the power for both optimizing quality of service (QoS) and saving the power consumption in WMNs based on the game theory. We first formulate the problem as a noncooperative game, in which the QoS attributes and the power of each node are defined as a utility function, and all the nodes attempt to maximize their own utility. In such game, we correlate all the interfering nodes to be an interfering object and the receiving node to be the interfering object's virtual destination node. We then present an equilibrium solution for the noncooperative game using Stackelberg model, and we propose an iterative, distributed power control algorithm for WMNs. Also, we conduct numeric experiments to evaluate the system performance, our results show that the proposed algorithm can balance nodes to share the limited network resources and maximize total utility, and thus it is efficient and effective for solving the power control problem in WMNs.

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