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TORM: Tunicate Swarm Algorithm-based Optimized Routing Mechanism in IoT-based Framework


Internet of Things (IoT)-based paradigm connects multitudinous IoT devices that operate in a wireless mode to gather information about various attributes from their surrounding. These IoT devices suffer from the limited energy resources and hence, these must be used in an optimized way to elongate network lifetime and to improve various performance metrics. A great magnitude of work is presented by the researchers to address the energy efficiency issue of the sensor node with use of various evolutionary algorithms, however, there is still scope for the improvement for the routing mechanism by using appropriate optimization method. To address this concern, in this paper, we present Tunicate Swarm Algorithm (TSA)-based Optimized Routing Mechanism (TORM) that addresses the problem of energy-efficiency of sensor nodes for IoT for longer sustainability. The rationale behind using recently proposed TSA optimization method is its faster convergence and high exploration abilities. The fitness function of TSA used for TORM, is computed by considering the various essential fitness parameters responsible for the selection of Cluster Head (CH) node. It is revealed through the simulation analysis that TORM outperform various state-of-the-art algorithms used for optimized selection of CH.

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This work was supported by King Saud University, Riyadh, Saudi Arabia, under Researchers Supporting Project number RSP-2021/18.

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Correspondence to Shalli Rani.

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Dogra, R., Rani, S., Verma, S. et al. TORM: Tunicate Swarm Algorithm-based Optimized Routing Mechanism in IoT-based Framework. Mobile Netw Appl (2021).

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  • Cluster head (CH)
  • IoT-based WSN
  • Intelligent routing
  • TORM
  • Tunicate swarm algorithm (TSA)