Distributed Lifetime Optimization in Wireless Sensor Networks using Alternating Direction Method of Multipliers

TL;DR

This paper introduces a distributed ADMM-based algorithm to optimize energy consumption and extend the lifetime of wireless sensor networks, emphasizing low overhead, fast convergence, and scalability.

Contribution

It presents a novel distributed iterative algorithm using ADMM for lifetime maximization in sensor networks, with proven convergence and efficiency advantages.

Findings

The algorithm converges rapidly with fewer iterations.

It reduces message passing overhead compared to existing methods.

Performance improves with larger network sizes.

Abstract

Due to the limited energy of sensor nodes in wireless sensor networks, extending the networks lifetime is a major challenge that can be formulated as an optimization problem. In this paper, we propose a distributed iterative algorithm based on Alternating Direction Method of Multipliers (ADMM) with the aim of maximizing sensor network lifetime. The features of this algorithm are use of local information, low overhead of message passing, low computational complexity, fast convergence, and consequently reduced energy consumption. In this study, we present the convergence results and the number of iterations required to achieve the stopping criterion. Furthermore, the impact of problem size (number of sensor nodes) on the solution and constraints violation is studied and finally, the proposed algorithm is compared to one of the well-known subgradient-based algorithms.