Node-Alive Index Driven Redundancy Elimination for Energy-Efficient Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) generate correlated and redundant data. This redundancy increases energy consumption during transmission and aggregation, which reduces the network lifespan. Eliminating data redundancy using appropriate data aggregation mechanisms in the dynamic environment is challenging. To address these issues, we designed the Data Aggregation with Redundancy Removal (DARR) protocol and implemented it in two phases. In Phase I, the DARR protocol identifies redundant nodes by calculating the spatial distance between the adjacent nodes. Over time, nodes may run out of energy and stop working after continuously sensing, aggregating, and transmitting the data. The dead nodes can obstruct data forwarding to intermediate nodes, so it is important to check periodically whether the nodes are alive or dead. The periodic time check identifies the status of each node, allowing the protocol to focus only on active nodes. It sets redundant nodes to sleep, which conserves network energy. In Phase II, the protocol reduces data redundancy at the source nodes using temporal correlation between data measurements. We enhanced the DARR protocol by incorporating a High Compression Temporal (HCT) mechanism, which further reduces data redundancy. Simulations show that the DARR protocol reduces data transmissions by 24% and lowers network energy consumption by up to 31% by eliminating redundant data at both the network and node levels.