4th International IEEE Conference on Broadband Communications, Networks, Systems

Research Article

Cross-layer Optimization Made Practical

  • @INPROCEEDINGS{10.1109/BROADNETS.2007.4550507,
        author={Ajit Warrier and Long Le and Injong Rhee},
        title={Cross-layer Optimization Made Practical},
        proceedings={4th International IEEE Conference on Broadband Communications, Networks, Systems},
  • Ajit Warrier
    Long Le
    Injong Rhee
    Year: 2010
    Cross-layer Optimization Made Practical
    DOI: 10.1109/BROADNETS.2007.4550507
Ajit Warrier1, Long Le1, Injong Rhee1
  • 1: Department of Computer Science, North Carolina State University.


Limited resources and time-varying nature of wireless ad hoc networks demand optimized use of resources across layers. Cross-layer optimization (CLO) for wireless networks, an approach that coordinates protocol behaviors at different layers with a goal to maximize a utility function, has received considerable attention lately. However, most existing work remains as theory and no practical CLO based on utility optimization exists today. The main difficulties in implementing theoretical CLO designs arise often from impractical assumptions about the characteristics of the wireless medium and also from computational and communication overhead of proposed solutions to achieve or approximate the optimality. In contrast, many existing practical approaches for CLO (not necessarily utility optimization) are rather ad hoc in nature and developed mostly based on intuitions. Thus, a clear gap between theory and practice in CLO exists. This paper addresses this dichotomy to close the gap by taking an optimal solution from utilitybased CLO and applying practical approximation to enable a practical implementation in a wireless mesh network where nodes are statically positioned in an ad hoc fashion. We focus on the utility of maximizing throughput. We identify the impractical or computationally-intensive components of a theoretically-derived optimal throughput-maximizing solution and then propose, in most cases, practical approximation with O(1) complexity for MAC, scheduling, routing and congestion control. The result is a practical CLO solution that approximates the theoreticallyderived optimal solution, but achieves much improved performance over existing practical CLO implementations.