3rd International ICST Conference on Quality of Service in Heterogeneous Wired/Wireless Networks

Research Article

End-to-end rate allocation in multi-radio wireless mesh networks: cross-layer schemes

  • @INPROCEEDINGS{10.1145/1185373.1185380,
        author={Jian Tang and Guoliang Xue and Weiyi  Zhang},
        title={End-to-end rate allocation in multi-radio wireless mesh networks: cross-layer schemes},
        proceedings={3rd International ICST Conference on Quality of Service in Heterogeneous Wired/Wireless Networks},
        publisher={ACM},
        proceedings_a={QSHINE},
        year={2006},
        month={8},
        keywords={Wireless mesh network cross-layer design rate allocation channel assignment routing scheduling power control fairness QoS.},
        doi={10.1145/1185373.1185380}
    }
    
  • Jian Tang
    Guoliang Xue
    Weiyi Zhang
    Year: 2006
    End-to-end rate allocation in multi-radio wireless mesh networks: cross-layer schemes
    QSHINE
    ACM
    DOI: 10.1145/1185373.1185380
Jian Tang1, Guoliang Xue1, Weiyi Zhang1
  • 1: Department of Computer Science and Engineering at Arizona State University, Tempe.

Abstract

In this paper, we study rate allocation for a set of end-to-end communication sessions in multi-radio wireless mesh networks. We propose cross-layer schemes which can jointly solve rate allocation, channel assignment, routing, scheduling and power control problems in multiple layers. Specifically, a Linear Programming (LP) based scheme is presented to compute end-to-end rate allocation with the goal of maximizing network throughput. As simple throughput maximization may lead to a severe bias on rate allocation, we take fairness into consideration based on a parameter named Demand Satisfaction Factor (DSF), and two fairness models, a simplified max-min fairness model and the well-known proportional fairness model. We propose LP-based and Convex Programming (CP) based schemes to compute fair end-to-end rate allocation. Our schemes can provide upper bounds on achievable network throughput and max-min DSF values. Numerical results show that our proportional fair rate allocation scheme achieves a good tradeoff between throughput and fairness.