Consensus based distributed joint power and routing optimization in wireless sensor networks

This paper proposes a fast distributed optimization algorithm for total transmit power minimization in single-sink data gathering wireless sensor networks. Many of the existing decentralized optimization algorithms addressing cross-layer design over the physical and network layer are based on dual decomposition. Our design includes joint power and routing optimization with given source rates by using consensus mechanism in conjunction with alternating direction method of multipliers (ADMM). Thus, the problem is decoupled across the nodes via introducing local copies of the variables, which are then iteratively driven into consensus with the ADMM. By the numerical experiments, the proposed distributed algorithm is shown to converge significantly faster to near optimal solutions with a small amount of local variable exchange as compared to the existing methods based on the dual decomposition.