Statistical Analysis to Extract Effective Parameters on Overall Energy Consumption of Wireless Sensor Network (WSN)

TL;DR

This paper employs statistical methods to identify key parameters affecting the energy consumption of wireless sensor networks, using extensive simulation data and correlation analyses.

Contribution

It introduces a two-phase approach combining simulation profiling and statistical analysis to determine the most influential parameters on WSN energy use.

Findings

Identified the most impactful parameters on energy consumption.

Demonstrated the effectiveness of statistical tools in parameter analysis.

Provided insights for optimizing WSN energy efficiency.

Abstract

In this paper, we use statistical tools to analysis dependency between Wireless Sensor Network (WSN) parameters and overall Energy Consumption (EC). Our approach has two main phases: profiling, and effective parameter extraction. In former, a sensor network simulator is re-run 800 times with different values for eight WSN parameters to profile consumed energy in nodes; then in latter, three statistical analyses (p-value, linear and non-linear correlation) are applied to the outcome of profiling phase to extract the most effective parameters on WSN overall energy consumption.