Energy Efficient Cluster Based Routing Protocol Using Charged System Harmony Search Algorithm in WSN

Nandhini, P.; Suresh, A.

doi:10.1007/s11277-021-08679-7

Cited by 17 publications

(3 citation statements)

References 20 publications

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“…However, it results in a hot‐spot problem 7,10 . As far as selecting the CH is concerned, researchers have used a variety of optimization techniques, including particle swarm optimization (PSO), 11 ACO, 12 genetic algorithm (GA), 2 BAT 13 algorithm and HBO 14 . However, the above‐mentioned meta‐heuristic algorithms still need to be improved in terms of energy stabilization and efficiency in order to improve the network's performance 15,16 .…”

Section: Introductionmentioning

confidence: 99%

Energy harvesting‐enabled energy‐efficient routing using spotted hyena optimization in wireless sensor network

Gupta,

Kumar Rout

2024

Int J Communication

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SummaryWith the continuous proliferation of sensing technology, it has become possible to utilize energy harvesting (EH)‐enabled sensor nodes for a variety of applications. However, conventional wireless sensor networks (WSNs), that is, those without EH‐enabled nodes, still have limited applicability due to their limited battery resources. Further, the utilization of EH‐enabled nodes in the network not only imposes a financial burden on the user but also limits its performance due to its dependence on environmental conditions. To address this concern, in this paper, we propose the EH‐enabled energy‐efficient routing (EHEER) technique for green communication in WSN. The predominant concern being addressed in this paper is the selection of cluster head (CH), which helps in gathering, aggregating and forwarding the data from the cluster‐based routing paradigm. We use the spotted hyena optimizer (SHO) algorithm for optimizing the fitness parameters for CH selection, namely, energy ratio, distance considerations, node density, load balancing and the network's average energy. We use EH‐enabled nodes in the network strategically so as to keep control over the costs incurred in the network. The simulation outcomes empirically prove the efficacy of the proposed work, as it effectively increases the network stability and operational period by a huge margin as compared to the existing techniques.

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Section: Introductionmentioning

confidence: 99%

Energy harvesting‐enabled energy‐efficient routing using spotted hyena optimization in wireless sensor network

Gupta,

Kumar Rout

2024

Int J Communication

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“…The cluster‐based routing provides a variety of benefits (such as data aggregation and a lower number of data transmissions, lowering communication overhead) for amelioration in network performance 6 . This performance boost is accomplished by assuring communication among the nodes and the BS, as well as enabling the WSN's overall security and, eventually, offering scalability 7 . Despite the aforementioned benefits of the clustering strategy, CH nodes are subjected to a large load (energy expenditure) that leads them to die prematurely, reducing the WSN's lifetime 5,8–10 .…”

Section: Introductionmentioning

confidence: 99%

“…6 This performance boost is accomplished by assuring communication among the nodes and the BS, as well as enabling the WSN's overall security and, eventually, offering scalability. 7 Despite the aforementioned benefits of the clustering strategy, CH nodes are subjected to a large load (energy expenditure) that leads them to die prematurely, reducing the WSN's lifetime. 5,[8][9][10] Apart from that, the mortality of CH nodes is far more harmful than the mortality of other nodes.…”

Section: Introductionmentioning

confidence: 99%

ROTEE: Remora Optimization and Tunicate swarm algorithm‐based Energy‐Efficient cluster‐based routing for EH‐enabled heterogeneous WSNs

Gupta

Rout

2022

Int J Communication

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Since the development of Wireless Sensor Networks (WSNs), the limited battery of the sensor nodes has been an unavoidable concern. Hence, to keep the WSNs operational for a longer possible duration, the recharging of node's battery through harvesting the ambient energy from surroundings (for an example, solar energy) has been proposed. In this work, we focus not only on utilizing the energy harvesting (EH)-enabled sensor nodes for routing purposes but also introduce a novel hybrid optimization ROATSA that uses Remora Optimization Algorithm (ROA) and Tunicate Swarm Algorithm (TSA) for energy-efficient cluster-based routing. The proposed work is termed as ROA and TSA-based Energy-Efficient Cluster-based Routing for EH-enabled WSN (ROTEE). Hybrid ROATSA is chosen due to enhanced convergence and exploitation capabilities. To reduce the financial burden on the network, we use only four EH-enabled nodes and locate them at each periphery of the network, equidistant to each other and the other nodes are 3-level energy heterogeneous sensor nodes. The selection of cluster head (CH) is optimized through ROATSA by considering profile index of each node by evaluating them at energy, distance, load balancing, node density, the delay involved, and network's average energy. The proposed work ROTEE shows supreme performance against the recently proposed clustering techniques.

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Energy and Trust Aware Cluster-Based Routing in WSN via Self-Improved Beluga Whale Optimization

Joshi,

Biradar,

Mathapathi

et al. 2024

Proceedings in Adaptation, Learning and Optimization

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Energy Efficient Cluster Based Routing Protocol Using Charged System Harmony Search Algorithm in WSN

Cited by 17 publications

References 20 publications

Energy harvesting‐enabled energy‐efficient routing using spotted hyena optimization in wireless sensor network

Energy harvesting‐enabled energy‐efficient routing using spotted hyena optimization in wireless sensor network

ROTEE: Remora Optimization and Tunicate swarm algorithm‐based Energy‐Efficient cluster‐based routing for EH‐enabled heterogeneous WSNs

Energy and Trust Aware Cluster-Based Routing in WSN via Self-Improved Beluga Whale Optimization

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