Centralized Lifetime Maximizing Tree For Wireless Sensor Networks

TL;DR

This paper introduces a centralized tree structure called CLMT for wireless sensor networks that maximizes the lifetime of data sources by optimizing data aggregation routes and reducing reconstruction frequency.

Contribution

It proposes a novel centralized algorithm to construct a lifetime-maximizing tree with bottleneck node identification, improving energy efficiency and prolonging network lifetime.

Findings

Reduces frequency of tree reconstruction

Maximizes source node lifetime

Minimizes energy consumption during data aggregation

Abstract

To enable data aggregation among the event sources in wireless sensor networks and to reduce the communication cost there is a need to establish a coveraged tree structure inside any given event region to allow data reports to be aggregated at a single processing point prior to transmission to the network. In this paper we propose a novel technique to create one such tree which maximizes the lifetime of the event sources while they are constantly transmitting for data aggregation. We use the term Centralized Lifetime Maximizing Tree (CLMT) to denote this tree. CLMT features with identification of bottleneck node among the given set of nodes. This node collects the data from every other node via routes with the highest branch energy subject to condition loop is not created. By constructing tree in such a way, protocol is able to reduce the frequency of tree reconstruction, minimize the delay and maximize the functional lifetime of source nodes by minimizing the additional energy involved in tree reconstruction.