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Probabilistic Based Optimized Adaptive Clustering Scheme for Energy-Efficiency in Sensor Networks


Affiliations
1 Department of Computer Science Engineering, Banasthali Vidyapith, Rajasthan, India
 

The key factor affecting the life span of the sensor network when node battery capacity is constrained is communication energy utilization. Although these networks are commonly used, they still require research to make full use of their outstanding features in communication. The utilization of energy is a major issue for which an optimization strategy to minimize energy usage and enhance the service life of the network is recommended. It was achieved by cultivating the energy balance of all Sensor Nodes (SNs) in clusters to reduce the dissipation of energy during data transmission. The aim of this paper is to implement an optimized refined probabilistic methodology to address the issue of how to conserve energy, maintain a balanced system throughput, and extend the lifespan of sensor network. The suggested scheme strengthens the Cluster Head (CH) selection threshold by taking into account the node's residual power, distance between the node, Base Station (BS), node dormancy mechanism and CH Re-election process. The proposed technique employs clustering with set time frame for transmission, which minimizes count of nodes involved in actual data transfer and will increase the lifespan. The proposed methodology helps to choose energy-aware CHs based on a fitness feature that takes SN's remaining energy and the neighboring SN's energy number. Furthermore, the proposed protocol L-DDRI’s (LEACH -Distance Degree Residual Index) efficiency is measured against other common contemporary routing protocols such as Low-energy adaptive clustering hierarchy (LEACH), Uneven Clustering Strategy (UCS) and Distributed Energy-Efficient Clustering (DEEC). Analytical research and extensive simulation demonstrate shows improvement of proposed protocol L-DDRI in terms of lifespan, number of CHs, energy utilization, performance and overall reliability of the network and number of packets sent to Base station other existing technique.

Keywords

Energy Efficiency, Cluster Head Selection, Distance Degree Residual Index (DDRI), Threshold.
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  • Probabilistic Based Optimized Adaptive Clustering Scheme for Energy-Efficiency in Sensor Networks

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Authors

Vasudha
Department of Computer Science Engineering, Banasthali Vidyapith, Rajasthan, India
Anoop Kumar
Department of Computer Science Engineering, Banasthali Vidyapith, Rajasthan, India

Abstract


The key factor affecting the life span of the sensor network when node battery capacity is constrained is communication energy utilization. Although these networks are commonly used, they still require research to make full use of their outstanding features in communication. The utilization of energy is a major issue for which an optimization strategy to minimize energy usage and enhance the service life of the network is recommended. It was achieved by cultivating the energy balance of all Sensor Nodes (SNs) in clusters to reduce the dissipation of energy during data transmission. The aim of this paper is to implement an optimized refined probabilistic methodology to address the issue of how to conserve energy, maintain a balanced system throughput, and extend the lifespan of sensor network. The suggested scheme strengthens the Cluster Head (CH) selection threshold by taking into account the node's residual power, distance between the node, Base Station (BS), node dormancy mechanism and CH Re-election process. The proposed technique employs clustering with set time frame for transmission, which minimizes count of nodes involved in actual data transfer and will increase the lifespan. The proposed methodology helps to choose energy-aware CHs based on a fitness feature that takes SN's remaining energy and the neighboring SN's energy number. Furthermore, the proposed protocol L-DDRI’s (LEACH -Distance Degree Residual Index) efficiency is measured against other common contemporary routing protocols such as Low-energy adaptive clustering hierarchy (LEACH), Uneven Clustering Strategy (UCS) and Distributed Energy-Efficient Clustering (DEEC). Analytical research and extensive simulation demonstrate shows improvement of proposed protocol L-DDRI in terms of lifespan, number of CHs, energy utilization, performance and overall reliability of the network and number of packets sent to Base station other existing technique.

Keywords


Energy Efficiency, Cluster Head Selection, Distance Degree Residual Index (DDRI), Threshold.

References





DOI: https://doi.org/10.22247/ijcna%2F2021%2F209187