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Energy-Efficient and Reliable Clustering with Optimized Scheduling and Routing for Wireless Sensor Networks

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Abstract

A wireless sensor network is a group of sensors that can share data gathered from a monitored field across wireless networks in which clustering is an important phenomenon for achieving reliable data transmission hence various clustering techniques have been presented previously for the slow acknowledgment of beacon signal to the base station, causes some sensor nodes to remain unclustered. To overcome this issue, a novel “Reliable Clustering with Optimized Scheduling and Routing for Wireless Sensor Network” is proposed to provide an energy efficient and reliable clustering in which a novel GridCosins chain Clustering has been utilized that clusters the sensor nodes based on the GridCosins distance and also forms distance tree topology based chaining of sensor nodes in the cluster thereby it reduces the transmission range between the sensor nodes and increases network lifetime. To acquire data from the network's unclustered nodes, proper CH selection must be carried out. For this instance, a novel Turtle Search Algorithm- Desert Cat Swarm Optimization (TSA-DCSO) double CH selection is introduced in which the hybrid optimization improves the CH selection process that eliminates the steady-state phase's passive listening and inactivity. Furthermore, the energy consumption of this proposed clustering is maintained by the Robust Node Switching State Algorithm that eliminates the overload of CH with less energy depletion and also mitigates the increased energy depletion of sensor nodes during the transmission of data to the CH. However, the unexpected failure of sensor nodes occurs in the current methodologies as a result of channel congestion and mutual interference during data transmission to the sink node. Hence, a novel Decisive Scheduling Optimized communication cost Routing is proposed in which the decision-making process is based on the energy level and the round trip delay time to remove damaged nodes. The result obtained by the proposed model efficiently solved the data transmission problems with a high network lifetime, less energy consumption, and high throughput.

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Abbreviations

Gij :

GridCosins distance between two sensor nodes Si and Sj

Si and Sj :

Sensor nodes

n:

number of weak decision stump results

ri :

radius

Pi :

Current fitness

Fs :

Best Fitness

Xid :

Current position of the cat

Vid :

Velocity of the Desert cat in an M-dimensional solution space

WSN:

Wireless Sensor Network

CH:

Cluster Head

TSA:

Turtle Search Algorithm

DCSO:

Desert Cat Swarm Optimization

MBS:

Mobile Base Station

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Bhilai Institute of Technology, Durg, 491001, India

    Shiv Dutta Mishra

  2. Chhattisgarh Swami Vivekanand Technical University, Bhilai, India

    Dipti Verma

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Mishra, S.D., Verma, D. Energy-Efficient and Reliable Clustering with Optimized Scheduling and Routing for Wireless Sensor Networks. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18623-z

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  • DOI: https://doi.org/10.1007/s11042-024-18623-z

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