9th International Conference on Communications and Networking in China

Research Article

A Bat-inspired Algorithm for Router Node Placement with Weighted Clients in Wireless Mesh Networks

  • @INPROCEEDINGS{10.4108/icst.chinacom.2014.256366,
        author={Chun-Cheng Lin and Yan-Sing Li and Der-Jiunn Deng},
        title={A Bat-inspired Algorithm for Router Node Placement with Weighted Clients in Wireless Mesh Networks},
        proceedings={9th International Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2015},
        month={1},
        keywords={wireless mesh network; bat-inspired algorithm; dynamic router node placement},
        doi={10.4108/icst.chinacom.2014.256366}
    }
    
  • Chun-Cheng Lin
    Yan-Sing Li
    Der-Jiunn Deng
    Year: 2015
    A Bat-inspired Algorithm for Router Node Placement with Weighted Clients in Wireless Mesh Networks
    CHINACOM
    IEEE
    DOI: 10.4108/icst.chinacom.2014.256366
Chun-Cheng Lin1, Yan-Sing Li1, Der-Jiunn Deng2,*
  • 1: National Chiao Tung University
  • 2: National Changhua University of Education
*Contact email: djdeng@cc.ncue.edu.tw

Abstract

This paper considers the problem of the dynamic router node placement (dynRNP) with weighted clients in wireless mesh networks (WMNs), in which both mesh clients and mesh router have mobility, and mesh clients can switch on or off their network access at different times. The main objective of the conventional dynRNP problem is to maximize network connectivity and client coverage, i.e., the size of the greatest subgraph component of the WMN topology and the number of the clients within radio coverage of mesh routers, respectively. This paper considers a more complicated dynRNP problem in WMNs, in which each client is associated with a weighted value (i.e., the mesh clients with higher weights values are served with larger priority), so that the two objective measures are redefined with consideration of clients' weights. Furthermore, the weighted problem is solved by a bat-inspired algorithm (BA) with a dynamic local search selection scheme, which simulates the echolocation of bats to find the optimal solution. Finally, the performance of the proposed BA is compared with the original BA and PSO, and the effects of weights are analyzed.