SSFSCE: Design of a Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN

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Published: Nov 2, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i10.8498
Keywords:
Wireless, Clustering, Destination, Source, PDR, GWO, Throughput, Energy, Delay, QoS

Main Article Content

Annaji M Kuthe, Sarika Khandelwal

Abstract

To enhance energy level in WSN is a research requirement, which assists in improving their lifetime over a series of communications. To achieve this target, a various variety of clustering & sleep scheduling models are discussed by researchers. Most of these models deploy static clustering & sleep scheduling operations, which limits their applicability & scalability levels. Moreover, dynamic clustering & scheduling models are highly complex, which reduces temporal QoS performance under real-time use cases. In order to reduce the probability of these issues, this text discusses design of the proposed Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN. The proposed model initially deploys a Grey Wolf Optimization (GWO) Method for dynamic sleep scheduling via temporal performance analysis. The GWO Method models a fitness function that combines temporal usage levels, temporal Quality of Service (QoS), and temporal energy levels. Based on this modelling process, nodes were categorized into wake & sleep nodes, which were further clustered via destination-aware Fan Shaped Clustering (FSC), that assisted in improving QoS performance under multiple scenarios. The FSC Model was combined with a QoS-aware routing model, that assisted in selection of routing paths that can achieve low delay, high throughput, and high packet delivery with higher energy efficiency levels. Efficiency of the model was tested on node & network conditions, and its QoS performance was checked in terms of communication delay, consumption of energy, level of throughput, and Packet Delivery Ratio (PDR) levels. On the basis of these comparative evaluations, it is observed that the new proposed model is able to enhance end-to-end delay by 8.5%, reduce level of energy by 15.5%, while increasing throughput by 8.3%, and PDR by 1.5%, thus making it useful for a different real-time conditions.

Article Details

How to Cite
Annaji M Kuthe, et al. (2023). SSFSCE: Design of a Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10), 360–368. https://doi.org/10.17762/ijritcc.v11i10.8498
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Vol. 11 No. 10 (2023): (Articles in Press)
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Articles
Author Biography

Annaji M Kuthe, Sarika Khandelwal

Annaji M Kuthe1,  Sarika Khandelwal2

1Research Scholar, Dept. of CSE, School of Engineering & Technology, G H Raisoni University, Amravati, India

annaji.kuthe@kdkce.edu.in

 2Associate Professor, Dept. of Computer Science & Engineering, G H Raisoni College of Engineering, Nagpur, India

sarika.khandelwal@raisoni.net

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