Smart Grid and Internet of Things. 4th EAI International Conference, SGIoT 2020, TaiChung, Taiwan, December 5–6, 2020, Proceedings

Research Article

Survey of Routing Metric in Wireless Mesh Networks

Download
62 downloads
  • @INPROCEEDINGS{10.1007/978-3-030-69514-9_25,
        author={Yunlong Wang and Zhongjiang Yan and Mao Yang and Bo Li},
        title={Survey of Routing Metric in Wireless Mesh Networks},
        proceedings={Smart Grid and Internet of Things. 4th EAI International Conference, SGIoT 2020, TaiChung, Taiwan, December 5--6, 2020, Proceedings},
        proceedings_a={SGIOT},
        year={2021},
        month={7},
        keywords={Wireless Mesh Networks Routing metric NS3},
        doi={10.1007/978-3-030-69514-9_25}
    }
    
  • Yunlong Wang
    Zhongjiang Yan
    Mao Yang
    Bo Li
    Year: 2021
    Survey of Routing Metric in Wireless Mesh Networks
    SGIOT
    Springer
    DOI: 10.1007/978-3-030-69514-9_25
Yunlong Wang1, Zhongjiang Yan1, Mao Yang1, Bo Li1
  • 1: Northwestern Polytechnical University

Abstract

As an important technology in the construction of the next generation wireless communication system, Wireless Mesh Networks (WMNs) has the advantages of high bandwidth, flexible networking, wide coverage and low investment risk. Routing metrics have a great impact on network. Appropriate routing metrics can reduce intra-stream and inter-stream interference, improve throughput and reliability, achieve load balancing and eliminate network hot spots. At present, research on routing metrics for WMNs has made some progress. Relevant scholars have proposed various routing metrics, but no scholars have compared and classified these routing metrics. In this paper, the classical routing metrics in WMNs and the routing metrics proposed in the last ten years are studied. The following conclusions are drawn from these investigations. Firstly, delay, packet loss rate and bandwidth are the most commonly considered factors in routing metrics. Secondly, routing metrics separately describe the types of disturbances that lead to the introduction of variable constants. Thirdly, routing metrics often ignore the choice of gateway nodes. Finally, delay is the most important parameter of routing metrics. For example, the introduction of bandwidth and bottleneck channels is for more accurate calculation of delay. NS3 is used to simulate Hop Routing Metric (HOP) and Distance Routing Metric. The simulation results show that in a small network, Distance Routing Metric can effectively reduce the delay and increase the network throughput.