An Algorithm to Determine Energy-aware Maximal Leaf Nodes Data Gathering Tree for Wireless Sensor Networks

TL;DR

This paper introduces the EMLN-DG algorithm that constructs energy-aware data gathering trees in wireless sensor networks, significantly extending network lifetime by maximizing leaf nodes and balancing energy consumption.

Contribution

The paper presents a novel energy-aware tree formation algorithm that improves network longevity by optimizing leaf nodes and energy distribution during data collection.

Findings

EMLN-DG extends network lifetime compared to LEACH and PEGASIS.

It reduces energy consumption and delay per data gathering round.

The algorithm maintains balanced energy levels across nodes.

Abstract

We propose an Energy-aware Maximal Leaf Nodes Data Gathering (EMLN-DG) algorithm for periodic data collection and transmission in wireless sensor networks. For each round of data gathering, an EMLN-DG tree spanning the entire sensor network is formed based on the residual energy level available at the nodes and the number of uncovered neighbors of a node during tree formation. Only nodes that have a relatively larger number of neighbors as well as a higher energy level are included as intermediate nodes in the EMLN-DG tree. By maximizing the number of leaf nodes in a DG tree and considering the energy level available at the nodes while forming the tree, we reduce energy consumption per round as well as balance the energy level across all the nodes in the network. This contributes to a significantly larger network lifetime, measured as the number of rounds before the first node failure due to exhaustion of battery charge. Performance comparison studies with the well-known data gathering algorithms such as LEACH and PEGASIS illustrate that EMLN-DG can help to sustain the network for a significantly larger number of rounds and at the same time incur a lower, or if not comparable, energy loss, delay and energy loss*delay per round of data gathering.