Transmission energy consumption analysis using ridge regression in wireless sensor nodes. (16th March 2023)

• Record Type: Journal Article
• Authors: Devi, B. Rajesh Shyamala; Sureshkumar, K.; Anand, J.V.
• Is Part Of: International journal of powertrains. Volume 12:Number 1(2023)
• Page Start: 15
• Page End: 24
• Publication Date: 2023-03-16
• Subjects: ridge regression -- energy conservation; Motor vehicles -- Power trains -- Periodicals; 629.25
• Languages: English
• ISSNs: 1742-4267

Abstract

Wireless sensor nodes and its constitution of energy consumption in transferring sensory data to sink node results in a linear relationship. However, the quasi state of sensors makes over and under estimates of the communicating sensor data. This work proposes a 'ridge regression wireless data transfer rate' (RRWDTR) to interpret the energy analysis incorporating optimum route and its energy constituents, which relies on underlying resources. Since nodes are collocated to provide multi-hop communication, the independent variables of event generation are forwarding to a central node associated with sink results in multi-colinearity. The model thus deflates, leading to inaccurate estimates of prediction. RRWDTR uses structural relationship of the node and its resources using ridge regression incorporating characteristics of variance. Simulation of RRWDTR work has been done with penalty coefficient to predict near accurate estimates. Finally, comparison of RRWDTR has been done with linear regression wireless data transfer rate (LRWDTR).