A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor Networks

INTRODUCTION: The lifetime of a sensor network completely relies on the potentialities of the utilized Cluster Head (CH) selection scheme that aids in building efficient Wireless Sensor Networks (WSNs). Most of the existing CH selection approaches use an impractical condition whic...

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Main Authors: Sengathir Janakiraman, M. Priya, S. Devi, G. Sandhya, G. Nivedhitha, S. Padmavathi
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2021-09-01
Series:EAI Endorsed Transactions on Energy Web
Subjects:
Online Access:https://eudl.eu/pdf/10.4108/eai.13-1-2021.168093
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spelling doaj-b377c62379274ba8a9d287e018a939622021-09-29T07:04:46ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Energy Web2032-944X2021-09-0183510.4108/eai.13-1-2021.168093A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor NetworksSengathir Janakiraman0M. Priya1S. Devi2G. Sandhya3G. Nivedhitha4S. Padmavathi5Department of Information Technology, CVR College of Engineering, Mangalpally, Vastunagar, Hyderabad, Telangana, IndiaDepartment of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamilnadu, IndiaDepartment of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamilnadu, IndiaDepartment of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamilnadu, IndiaDepartment of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamilnadu, IndiaDepartment of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamilnadu, IndiaINTRODUCTION: The lifetime of a sensor network completely relies on the potentialities of the utilized Cluster Head (CH) selection scheme that aids in building efficient Wireless Sensor Networks (WSNs). Most of the existing CH selection approaches use an impractical condition which mainly emphasizes that the nodes that are trustworthy and highly energy competitive have better likelihood of being selected as CHs.OBJECTIVES: In this paper, a Markov Process-based Opportunistic Trust Factor Estimation Mechanism (MPOTFEM) is proposed for achieving optimal CH selection that enhances the possibility of maintaining network lifetime and energy stability in the network. METHODS: MPOTFEM is proposed for ensuring efficient CH selection and thereby enhancing the lifetime of WSNs. The proposed MPOTFEM incorporates the merits of Markov process for computing the Opportunistic and Trust factors that assesses the maximum likelihood of nodes with the possibility of being selected as the CH by exploring multiple transition states of nodes in the networks. RESULTS: The results of the propounded MPOTFEM confirm to be significant in improving the network longevity by 39.21% with minimized energy consumption of 34.82% when compared to the baseline CH election mechanisms taken for analysis.CONCLUSION: The results prove that MPOTFEM is better when compared to the benchmarked CH selection schemes in terms of network lifespan and energy stability.https://eudl.eu/pdf/10.4108/eai.13-1-2021.168093markov process opportunistic factor trust factor cluster head selection network lifetime maximum likelihood probability
collection DOAJ
language English
format Article
sources DOAJ
author Sengathir Janakiraman
M. Priya
S. Devi
G. Sandhya
G. Nivedhitha
S. Padmavathi
spellingShingle Sengathir Janakiraman
M. Priya
S. Devi
G. Sandhya
G. Nivedhitha
S. Padmavathi
A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor Networks
EAI Endorsed Transactions on Energy Web
markov process
opportunistic factor
trust factor
cluster head selection
network lifetime
maximum likelihood probability
author_facet Sengathir Janakiraman
M. Priya
S. Devi
G. Sandhya
G. Nivedhitha
S. Padmavathi
author_sort Sengathir Janakiraman
title A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor Networks
title_short A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor Networks
title_full A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor Networks
title_fullStr A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor Networks
title_full_unstemmed A Markov Process-based Opportunistic Trust Factor Estimation Mechanism for Efficient Cluster Head Selection and Extending the Lifetime of Wireless Sensor Networks
title_sort markov process-based opportunistic trust factor estimation mechanism for efficient cluster head selection and extending the lifetime of wireless sensor networks
publisher European Alliance for Innovation (EAI)
series EAI Endorsed Transactions on Energy Web
issn 2032-944X
publishDate 2021-09-01
description INTRODUCTION: The lifetime of a sensor network completely relies on the potentialities of the utilized Cluster Head (CH) selection scheme that aids in building efficient Wireless Sensor Networks (WSNs). Most of the existing CH selection approaches use an impractical condition which mainly emphasizes that the nodes that are trustworthy and highly energy competitive have better likelihood of being selected as CHs.OBJECTIVES: In this paper, a Markov Process-based Opportunistic Trust Factor Estimation Mechanism (MPOTFEM) is proposed for achieving optimal CH selection that enhances the possibility of maintaining network lifetime and energy stability in the network. METHODS: MPOTFEM is proposed for ensuring efficient CH selection and thereby enhancing the lifetime of WSNs. The proposed MPOTFEM incorporates the merits of Markov process for computing the Opportunistic and Trust factors that assesses the maximum likelihood of nodes with the possibility of being selected as the CH by exploring multiple transition states of nodes in the networks. RESULTS: The results of the propounded MPOTFEM confirm to be significant in improving the network longevity by 39.21% with minimized energy consumption of 34.82% when compared to the baseline CH election mechanisms taken for analysis.CONCLUSION: The results prove that MPOTFEM is better when compared to the benchmarked CH selection schemes in terms of network lifespan and energy stability.
topic markov process
opportunistic factor
trust factor
cluster head selection
network lifetime
maximum likelihood probability
url https://eudl.eu/pdf/10.4108/eai.13-1-2021.168093
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