Abstract

Wireless technology is emerging as a key technology for the future networks. Wireless mesh networks (WMNs) have emerged as an indispensable technology for deployment of wireless services for various applications in personal, enterprise, and metropolitan areas. Researchers are working actively in different fields of WMNs for providing better services. Routing protocols play a vital role in WMNs to provide reliable configuration and maintenance of topology of the network. Designing a suitable cost metric for routing protocols to provide quality links for data transmission is the backbone of WMNs. Many cost metrics have been proposed for WMNs and is still an active research topic as new performance metrics need to be discovered due to the dynamics of this field. This paper considers the genetic algorithm-based routing technique for WMN.We have studied the existing cost metrics and proposed a genetic algorithm technique for routing in WMN. To evaluate the genetic algorithm, and to determine the relative performance of the genetic algorithm in the context of routing in WMN, we carry out experiments on two test systems. We have evaluated the quality of the results produced by our algorithm with the traditional hop count metric results. Our results show that routing in WMN using genetic algorithm produces better results as compared to traditional hop count metric results. Finally, we carry out a detailed analysis of results, which help us in gaining an insight into the suitability of genetic algorithm for routing in WMN.

Highlights

  • Wireless technology is emerging as new replacement of existing wired networking, but at the same time, many implementation challenges need to be addressed for the deployment of wireless technology

  • This paper investigates the routing technique in Wireless mesh networks (WMNs) which takes into account the dynamic behavior of traffic demands

  • This paper further identifies an optimization framework which finds an optimal path for routing in WMN

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Summary

Introduction

Wireless technology is emerging as new replacement of existing wired networking, but at the same time, many implementation challenges need to be addressed for the deployment of wireless technology. 4.2 Application of GA model 2 The parameters for GA model 2 are shown in Table 6 that are operated on “50 nodes WMN.” To acquire an optimal path for routing, the selection method Tournament with elitism is used.

Results
Conclusion
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