Adaptive Energy Aware Data Aggregation Tree for Wireless Sensor Networks

TL;DR

This paper introduces an adaptive energy-aware data aggregation tree for wireless sensor networks that optimizes energy use, extends network lifetime, and improves data delivery efficiency through dynamic node selection and sleep-wake strategies.

Contribution

It proposes a novel adaptive tree structure that selects high-energy nodes as aggregators and employs sleep-wake technology to conserve energy and enhance network longevity.

Findings

Increases network lifetime significantly.

Reduces energy consumption during data transmission.

Maintains high data delivery ratio with lower delay.

Abstract

To meet the demands of wireless sensor networks (WSNs) where data are usually aggregated at a single source prior to transmitting to any distant user, there is a need to establish a tree structure inside to aggregate data. In this paper, an adaptive energy aware data aggregation tree (AEDT) is proposed. The proposed tree uses the maximum energy available node as the data aggregator node. The tree incorporates sleep and awake technology where the communicating node and the parent node are only in awake state rest all the nodes go to sleep state saving the network energy and enhancing the network lifetime. When the traffic load crosses the threshold value, then the packets are accepted adaptively according to the communication capacity of the parent node. The proposed tree maintains a memory table which stores the value of each selected path. Path selection is based on shortest path algorithm where the node with highest available energy is always selected as forwarding node. By simulation results, we show that our proposed tree enhances network lifetime minimizes energy consumption and achieves good delivery ratio with reduced delay.