Multiple Parameter Based Energy Balanced and Optimized Clustering for WSN to Enhance the Lifetime Using MADM Approaches

Rajpoot, Prince; Dwivedi, Pragya

doi:10.1007/s11277-019-06192-6

Cited by 40 publications

(13 citation statements)

References 61 publications

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“…BS runs a cluster protocol based on GWO. The fitness function is just established based on 11 considered attributes as given [36], Coverage_of_CHs, CH_BS_Bearing, Avg_Eresidual, BS_Max_Distance, CHs_Avg_Distance, BS_Avg_Distance, Nodes_Energy, CH_Energy, CHs_Avg_lifetime, Avg_Eres_of_Conn_CH, Avg_Eres_of_Disconn_CH. The primary aim of the CH-GWO is to select the CHs in the network to extend the life of the network.…”

Section: Proposed Workmentioning

confidence: 99%

Multi-Objective Decision Making Approach based Load Balanced Clustering in WSNs to Increase The Lifetime of Network

Lekhraj

Kumar

2021

Preprint

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A network of wireless sensors (WSN) is an outstanding technology that can aid in the various applications. Batteries run the sensor nodes those are used in WSN. The battery is impossible to charge or repair, so the most valuable resource for wireless sensor networks is power. Over the years, several strategies have been invented and used to preserve this precious WSN resource. One of the most successful approach for this purpose has turned out to be clustering. The aim of this paper is to suggest an effective technique for choosing cluster heads in WSNs to increase the lifetime of the network. To accomplish this task, Grey Wolf Optimizer (GWO) technique has been used. The general GWO was updated in this paper to meet the particular purpose of cluster head selection in WSNs. In this article, we have considered eleven attributes in the fitness function for the proposed algorithm. The simulation is carried out under different conditions. The results obtained show that the proposed protocol is superior in terms of energy consumption and network lifetime by evaluating the proposed protocol (i.e. CH-GWO protocol) with some well-existing cluster protocols. The suggested protocol forms energy-efficient and scalable clusters.

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Section: Proposed Workmentioning

confidence: 99%

Multi-Objective Decision Making Approach based Load Balanced Clustering in WSNs to Increase The Lifetime of Network

Lekhraj

Kumar

2021

Preprint

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“…Increasing the network's lifespan is a great way of making the network more efficient. LEACH occupies more position in the field of WSN and most hierarchical routing protocols, which seek to extend the lifetime of networks are usually based on LEACH [13,14]. In the area of WSNs, Communication, Sensing and Computation are the three major aspects that consume a lot of energy.…”

Section: Aims and Objectivesmentioning

confidence: 99%

A Study of Energy Efficiency in Wireless Sensor Networks

Panful¹,

Xie²

2021

Proceedings of the 28th iSTEAMS Multidisciplinary &Amp; Inter-Tertiary Research Conference

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The wireless sensor networks (WSNs) field is one of the emerging and fast-growing fields in the scientific world. This has brought about the development of low-cost, and multifunctional sensor nodes for easy and secure dissemination of information. Nonetheless, the problem of sensor nodes running out of energy quickly has been an issue. Many energyefficient routing algorithms have been proposed to solve this problem and preserve the longevity of the network. Most of the recent papers have shown so many protocols mainly designed to minimize energy consumption in the network but there are some limitations with regards to the area of operation and the optimization decisions. This paper proposes an Energy Efficiency Hierarchical Routing Technique (EEHRT) which is based on LEACH protocol to extend the lifespan of a WSN. In this work, the proposed Energy Efficient Hierarchical Routing Technique selects cluster heads based on the prediction of transmission energy through the shortest distance to the base station. Our approach rotates the role of Cluster Heads (CHs), and optimizes the CH selection by the prediction of energy transmission in every round and aggregating data before transmission to the BS. The important features which include member nodes formation and rotation, cluster head selection and rotation, and cluster optimization of our proposed hierarchical routing technique in transmitting data to the base station are analyzed and emphasized. Keywords: Wireless Sensor Network, Base Station, Member Node, Clustering, LEACH, Hierarchy Proceedings Reference Format Benjamin Panful & Xie Zhibin (2021): Rural Women’s Access to Land and its Implications for Empowerment in Nigeria: The Case of Ilorin East Local Government Area, Kwara State, Nigeria. Proceedings of the 28th iSTEAMS Intertertiary Multidisciplinary Conference. American International University West Africa, The Gambia. Series 28, Vol 3 October 2021. Pp 105-120 www.isteams.net/gambia2021. DOI - https://doi.org/

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“…Optimal CH selection was extensively studied in several WSN for balancing energy constraint using multicriteria decision-making algorithm. In (Rajpoot & Dwivedi, 2019), optimal cluster head selection and ranking using MADM approaches called TOPSIS were designed. TOPSIS was well-known multicriteria-based decision-making approach that ranks the results.…”

Section: Related Workmentioning

confidence: 99%

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

Sinde

Begum

Njau³

et al. 2020

Cogent Engineering

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Network lifetime remains as a significant requirement in Wireless Sensor Network (WSN) exploited to prolong network processing. Deployment of low power sensor nodes in WSN is essential to utilize the energy efficiently. Clustering and sleep scheduling are the two major processes involved in improving network lifetime. However, abrupt and energy unaware selection of cluster head (CH) is nonoptimal in WSN which reflects in the drop of energy among sensor nodes. This paper addresses the twofold as utilization of sensor nodes to prolong the node's energy and network lifetime by LEACH-based cluster formation and Time Division Multiple Access scheduling (TDMA). Clusters are constructed by the design of an Enhanced-Low-Energy adaptive Clustering Hierarchy protocol (E-LEACH) that uses parallel operating optimization (Grey Wolf Optimization (GWO) and Discrete Particle Swarm Optimization (D-PSO)) for selecting an optimal CH and helper CH. The fitness values estimation from GWO and D-PSO is concatenated to prefer the best optimal CH. E-LEACH also manages the cluster size which is one of the conventional disadvantages in LEACH. CHs are responsible to perform energy-aware TDMA scheduling which segregates the coverage area into 24 sectors. Alternate sectors are assigned Ramadhani Sinde ABOUT THE AUTHOR Ramadhani Sinde works as an assistant lecturer in the School of Computational and Communication Sciences and Engineering at Nelson Mandela African Institution of Science and Technology (NM-AIST). Currently, he under Doctoral Environmental Management Information System project undertaking PhD studies in the field of Information and Communication of Science and Engineering. His research interests include Internet of Things (IoT) network, embedded systems, mobile computing, modelling and performance evaluation of wireless sensor networks, wireless and mobile communication. Mr. Sinde has co-authored more than 10 papers in internationally refereed journals and conferences. He is a Queen Elizabeth Scholarship -Advanced Scholars Program alumni.

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Multiple Parameter Based Energy Balanced and Optimized Clustering for WSN to Enhance the Lifetime Using MADM Approaches

Cited by 40 publications

References 61 publications

Multi-Objective Decision Making Approach based Load Balanced Clustering in WSNs to Increase The Lifetime of Network

Multi-Objective Decision Making Approach based Load Balanced Clustering in WSNs to Increase The Lifetime of Network

A Study of Energy Efficiency in Wireless Sensor Networks

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

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