Distributed Lifetime and Data Rate Optimization with Dynamic Approximation in Wireless Networks
In this paper, we study the problem of jointly maximizing network lifetime and data rate in wireless networks. For this problem, we introduce a general network utility maximization (NUM) cross-layer formulation that accommodates routing, scheduling and stream control from different layers of network with relevant constraints. In particular, based on both Lagrangian approach and Markov Chain Monte Carlo method, we extend our programming model to distributed algorithms that can dynamically approximate the optimal solution to this problem. Finally, we present computational results for the insight that can be gained from the cross-layer optimization and the distributed algorithms.
distributed algorithm cross-layer design csma approximation performance optimization