Energy-Efficient Cluster-based Routing Protocol in Internet of Things Using Swarm Intelligence

Energy conservation is a difficult challenge, because the Internet of Things (IoT) connects limited resource devices. Clustering is an efficient method for energy saving in network nodes. The existing clustering algorithms have problems with the short lifespan of a network, an unbalanced load among...

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Bibliographic Details
Published in:2020 IEEE Symposium Series on Computational Intelligence (SSCI) pp. 219 - 224
Main Authors: Sankar, Sennan, Ramasubbareddy, Somula, Chen, Fang, Gandomi, Amir H.
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2020
Subjects:
Clustering algorithms
Delays
Euclidean distance
Internet of Things
Optimization
Routing protocols
Sailfish optimization Algorithm
Swarm Intelligence
Wireless sensor networks
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Summary:Energy conservation is a difficult challenge, because the Internet of Things (IoT) connects limited resource devices. Clustering is an efficient method for energy saving in network nodes. The existing clustering algorithms have problems with the short lifespan of a network, an unbalanced load among the network nodes and increased end-to-end delays. This paper proposes a new Cluster Head (CH) selection and cluster formation algorithm to overcome these issues. The process has two phases. First, the CH is selected using a Swarm Intelligence Algorithm called Sailfish optimization Algorithm (SOA). Second, the cluster is formed by the Euclidean distance. The simulation is conducted using the NS2 simulator. The efficacy of the SOA is compared to Improved Ant Bee Colony optimization-based Clustering (IABCOCT), Enhanced Particle Swarm optimization Technique (EPSOCT) and Hierarchical Clustering-based CH Election (HCCHE). The final results of the simulation show that the proposed SOA improves network life and decreases node-to-sink delays.
DOI:10.1109/SSCI47803.2020.9308609