Distributed optimal rate-reliability-lifetime tradeoff in time-varying wireless sensor networks

The transmission rate, delivery reliability, and network lifetime are three fundamental but conflicting design objectives in energy-constrained wireless sensor networks (WSNs). In this paper, based on stochastic network utility maximization framework, we address the optimal rate-reliability-lifetime tradeoff with time-varying channel capacity constraint, reliability constraint, and energy constraint. By introducing the weight parameters, we combine the optimization objectives of rate, reliability, and lifetime into a single objective to characterize the tradeoff among them. However, the optimization formulation of the rate-reliability-reliability tradeoff is neither separable nor convex. Through a series of transformations, a separable problem is derived, and an efficient distributed stochastic subgradient algorithm is proposed via dual decomposition and stochastic subgradient techniques. It is proved that the proposed algorithm can converge to the global optimum with probability one. Numerical examples confirm its convergence. In addition, numerical examples investigate the impact of weight parameters on the rate utility, reliability utility, and network lifetime, which provide guidance to properly set the value of weight parameters for a desired performance of WSNs according to the realistic application's requirements.