Optimal Energy-Efficient Cluster Head Selection (OEECHS) for Wireless Sensor Network

Saranraj, G.; Selvamani, K.; Kanagachidambaresan, G. R.

doi:10.1007/s40031-019-00390-3

Cited by 9 publications

(3 citation statements)

References 19 publications

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“…The simulation experiments of SSMO-CS proved its predominance in terms of energy efficiency identified over time. Then, Saranraj et al [14] Furthermore, Dattatraya and Rao [17] planned a hybrid cluster head selection approach based on FruitFly and Glowwork Swarm Algorithm (HCSA-FGSA). The energy and alive node investigation were considered to be superior and the cost function is identified to be highly minimized on par with the existing clustering schemes.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Elephant Optimization Algorithm-based Cluster Head Selection to Extend Network Lifetime in Wireless Sensor Networks (WSNs)

Prahadeeshwaran¹,

Priscilla²

2018

EAI Endorsed Transactions on Energy Web

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Wireless Sensor Networks (WSNs) comprise of a number of sensor nodes that are capable of sensing and aggregating the data from the monitoring environment. However, the process of recharging the limited energy sensor node batteries are highly difficult during adverse situations. This limitation of sensor nodes greatly crumbles the network lifetime to a maximum degree and degrades the level of reliable data dissemination. In this paper, a Novel Individual Updating Strategies-based Hybrid Elephant Herding Optimization Algorithm (NIUS-HEHOA) is planned for facilitating energy balanced cluster head selection for the objective of extending the network lifetime. It included energy-aware optimization process during the clustering schemes, since it is considered as a solution to the significant NP complete optimization problem. It is propounded as a swarm intelligent algorithms are identified to be the most applicable candidate for energy optimization that leads to significant improvement in network lifetime. It is contributed to maintain the deviation between exploitation and exploration such that least potential sensor nodes are prevented from being chosen as cluster heads. The simulation experiments confirmed that the proposed NIUS-HEHOA scheme is better than the benchmarked schemes in terms of alive nodes, dead nodes, residual energy, network lifetime and throughput.

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Section: Related Workmentioning

confidence: 99%

A Hybrid Elephant Optimization Algorithm-based Cluster Head Selection to Extend Network Lifetime in Wireless Sensor Networks (WSNs)

Prahadeeshwaran¹,

Priscilla²

2018

EAI Endorsed Transactions on Energy Web

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“…To guard against malicious behavior, the network's nodes are authenticated and registered. There is a lack of registration or authentication procedure for network nodes in CHs, which transfer the detected data to BS 16 . The network might become exposed when malicious nodes infiltrate it.…”

Section: Introductionmentioning

confidence: 99%

“…There is a lack of registration or authentication procedure for network nodes in CHs, which transfer the detected data to BS. 16 The network might become exposed when malicious nodes infiltrate it. The performance of the network as a whole is impacted whenever a node malfunctions as a result of energy exhaustion.…”

mentioning

confidence: 99%

Blockchain‐enabled joint trust (RF‐AOA‐HTSA) algorithm‐based multiobjective clustering protocol for wireless sensor network

Meenakshi¹,

Karunkuzhali²,

Ali³

2023

Concurrency and Computation

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SummaryIn this article, blockchain‐enabled hybrid Red Fox optimization and arithmetic optimization approach‐based cluster head selection along Hazelnut tree search algorithm (HTSA)‐based optimal trust path selection is proposed to secure data transmission at wireless sensor network. The proposed BC‐Hyb‐RF‐AOA‐HTSA‐WSN method consists of two phases: (i) to find optimum cluster head (CH) and (ii) to find optimal trust path. Firstly, hybrid Red Fox optimization approach and arithmetic optimization algorithm are employed to select cluster head accurately. After CH selection, HTSA is used to find trust route from several routes, which is finalized optimally with the joint trust that depends on trust parameters. Finally, blockchain is provided with optimized, carefully chosen trust routes for communication. The proposed BC‐Hyb‐RF‐AOA‐HTSA‐WSN method is activated in NS2 tool. The proposed technique achieves lesser delays of 98.38%, 92.34%, and 97.45%, better delivery ratios of 89.34%, 83.12%, and 88.96%, and lower packet drops of 91.25%, 79.90%, and 92.88% compared with the existing techniques, such as BC‐FA‐ROA‐WSN, BC‐RDA‐WSN, and BC‐HRDSS‐WSN.

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Smart IoT‐Enabled Traffic Sign Recognition With High Accuracy (TSR‐HA) Using Deep Learning

Pradeep¹,

Jayanthi²,

Selvakumari³

2022

Machine Learning Paradigm for Internet of Things Applications

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Optimal Energy-Efficient Cluster Head Selection (OEECHS) for Wireless Sensor Network

Cited by 9 publications

References 19 publications

A Hybrid Elephant Optimization Algorithm-based Cluster Head Selection to Extend Network Lifetime in Wireless Sensor Networks (WSNs)

A Hybrid Elephant Optimization Algorithm-based Cluster Head Selection to Extend Network Lifetime in Wireless Sensor Networks (WSNs)

Blockchain‐enabled joint trust (RF‐AOA‐HTSA) algorithm‐based multiobjective clustering protocol for wireless sensor network

Smart IoT‐Enabled Traffic Sign Recognition With High Accuracy (TSR‐HA) Using Deep Learning

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