Energy-Efficiency Enhancement Using a Novel CCA Protocol Based on Clustering in WSNs Wildfire Application

Abstract

Automated industrial management, Distant ecological observation, and Targeted tracing are a
few of the multiple uses for "Wireless Sensor Networks (WSNs)". An identical approach is
showing potential as a means for observing and detecting wildfires in actual environments.
There are many tiny nodes installed in distant and unreachable forest settings or huge
geographic regions as part of a WSN enabling wildfire environmental monitoring. Across a
networked infrastructure, a "Cluster-Head (CH)" node receives reports from a huge series of
smaller nodes about changes in the environment (temperature/humidity, for example).
Minimal power capabilities are a huge problem for sensor nodes within those networks,
making them less effective in detecting wildfires. The use of the proposed "Clustering based
Compression-Aggregation (CCA) protocol", could improve the WSN wildfire application's
overall energy efficiency. Data redundancies may be greatly reduced in WSNs by using the
"Data-Aggregation (DA)" paradigm, which also ensures energy efficiency. Gathering,
sorting, and combining data gathered from various network nodes, significantly lowers the
energy consumption of communication while reducing the frequency of duplicated data. In
WSNs, this method is a revolutionary way to data compressing which minimizes
transmission costs without requiring sophisticated calculations or transmission management.
Through compressed sensing, the proposed solution assures the WSN's long-term energy
efficiency. The CCA proposed protocol was compared and analyzed with the "Tunicate
Swarm Algorithm (TSA)" existing protocol in regards to its "Energy-Efficiency", "Packet
Delivery Ratio (PDR)", "Throughput", and "Routing Overhead" in the WSN.