scholarly journals Distributed Gateway Placement for Cost Minimization in Wireless Mesh Networks

Author(s):  
XiaoHua Xu ◽  
ShaoJie Tang ◽  
Xufei Mao ◽  
Xiang-Yang Li
Author(s):  
Huyao Dac-Nhuong Le ◽  
Nhu Gia Nguyen ◽  
Nghia Huu Dinh ◽  
Nguyen Dang Le ◽  
Vinh Trong Le

2008 ◽  
Vol 13 (1-2) ◽  
pp. 198-211 ◽  
Author(s):  
Fan Li ◽  
Yu Wang ◽  
Xiang-Yang Li ◽  
Ashraf Nusairat ◽  
Yanwei Wu

2013 ◽  
Vol 284-287 ◽  
pp. 2751-2755
Author(s):  
Chuan Gang Liu ◽  
Chi Hui Chiang ◽  
Ya Wen Liao

Wireless mesh networks are expected to provide wireless broadband access to Internet. In such networks, gateway placement is an important topic, which usually dominates the overall wireless performance, and hence there have been lots of the related works. However, recent paper even discovers that the starvation of TCP flows usually occurs near wireless gateways. Some TCP flows will starve just due to TCP flows of the node next to the gateway. Hence, possible ways to improve this critical issue should be developed urgently. However, until now, there have not been the feasible ways without modifying MAC and TCP mechanisms. Hence, in this paper, we plan the gateways placement under the consideration of this issue. To the best of our knowledge, this paper is the first work to plan gateway placement under considering the starvation of TCP flows. Our work also provides a new view in the field of planning wireless mesh networks.


Author(s):  
Shivan Qasim Ameen ◽  
Ravie Chandren Muniyandi

Wireless Mesh Networks (WMN) consists of wireless stations that are connected with each other in a semi-static configuration. Depending on the configuration of a WMN, different paths between nodes offer different levels of efficiency. One areas of research with regard to WMN is cost minimization. A Modified Binary Particle Swarm Optimization (MBPSO) approach was used to optimize cost. However, minimized cost does not guarantee network performance. This paper thus, modified the minimization function to take into consideration the distance between the different nodes so as to enable better performance while maintaining cost balance. The results were positive with the PDR showing an approximate increase of 17.83% whereas the E2E delay saw an approximate decrease of 8.33%.


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