Distributed Spiral Optimization in Wireless Sensor Networks without Fusion Centers

TL;DR

This paper introduces a distributed spiral algorithm for wireless sensor networks that improves convergence speed and reduces communication costs without sacrificing estimation accuracy.

Contribution

It presents a novel spiral message passing scheme that eliminates the need for fusion centers, enhancing efficiency in distributed optimization.

Findings

Converges with lower total transport cost than traditional methods.

Maintains estimation accuracy and convergence speed.

Effective in wireless sensor network scenarios.

Abstract

A distributed spiral algorithm for distributed optimization in WSN is proposed. By forming a spiral-shape message passing scheme among clusters, without loss of estimation accuracy and convergence speed, the algorithm is proved to converge with a lower total transport cost than the distributed in-cluster algorithm.