1st International ICST Conference on Robot Communication and Coordination

Research Article

Latency and Connectivity Analysis Tools fo Wireless Mesh Networks

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  • @INPROCEEDINGS{10.4108/ICST.ROBOCOMM2007.2121,
        author={Phoebus Chen and Shankar Sastry},
        title={Latency and Connectivity Analysis Tools fo Wireless Mesh Networks},
        proceedings={1st International ICST Conference on Robot Communication and Coordination},
        proceedings_a={ROBOCOMM},
        year={2010},
        month={5},
        keywords={},
        doi={10.4108/ICST.ROBOCOMM2007.2121}
    }
    
  • Phoebus Chen
    Shankar Sastry
    Year: 2010
    Latency and Connectivity Analysis Tools fo Wireless Mesh Networks
    ROBOCOMM
    ICST
    DOI: 10.4108/ICST.ROBOCOMM2007.2121
Phoebus Chen1,*, Shankar Sastry1,*
  • 1: Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, California 94720
*Contact email: phoebusc@eecs.berkeley.edu, sastry@eecs.berkeley.edu

Abstract

There has been a recent rise in interest in building networked control systems over a wireless network, whether they be for robot navigation, multi-robot systems, or traditional industrial automation. The wireless networks in these systems must deliver packets between the controller and the actuators/ sensors reliably and with low latency. Furthermore, they should be amenable to modeling and characterization so they can be designed as part of a complete control system. Mesh networks are particularly suited for control applications because they provide greater reliability through path diversity. This paper introduces tools for characterizing the end-toend connectivity of two points in a wireless mesh network as a function of latency. In particular, we use tools derived from Markov chain models to compare end-to-end connectivity in two routing protocols running on the Data Link/MAC layer provided by Dust Network’s Time Synchronized Mesh Protocol (TSMP): Directed Staged Flooding (DSF) and Dust Network’s Unicast Path Diversity (UPD). These models also allow us to calculate the traffic load, the sensitivity of end-to-end connectivity to link estimation error, and the robustness of the network to node failure. The paper gives an example of how these tools can be used to evaluate the feasibility of running control applications over sensor networks.