Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

Some recent researches have shown that the energy consumption problem caused by data collection in a wireless sensor network (WSN) based on a static data collector is a main threat to the network lifetime. However, with the progress of the mobile terminal technology, the implementation of mobile dat...

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Main Authors: Rahma Gantassi, Zaki Masood, Yonghoon Choi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9783176/
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author Rahma Gantassi
Zaki Masood
Yonghoon Choi
author_facet Rahma Gantassi
Zaki Masood
Yonghoon Choi
author_sort Rahma Gantassi
collection DOAJ
description Some recent researches have shown that the energy consumption problem caused by data collection in a wireless sensor network (WSN) based on a static data collector is a main threat to the network lifetime. However, with the progress of the mobile terminal technology, the implementation of mobile data collectors (MDCs) has become more popular in large-scale WSNs, but it remains a big problem to improve the Quality of Service (QoS) criteria and minimize the energy consumption at the same time. However, most existing systems based on MDCs do not successfully strike a balance between routing energy consumption and QoS. In addition, most WSN protocols fail to maintain their impact when the network topology changes. Thus, for a dynamic WSN, it is important to support an intelligent MDC to continue data propagation despite the inevitable changes in the WSN topology. Considering all the above challenges, we propose a new intelligent MDC based on the traveling salesman problem (TSP) to determine the optimal path traveled by the MDC for energy efficiency and latency. Specifically, our proposed Mobile Data Collectors-Traveling Salesman Problem-Low Energy Adaptive Clustering Hierarchy-K-Means (MDC-TSP-LEACH-K) protocol uses K-Means and Grid clustering algorithm to decrease energy consumption in the cluster head (CH) election phase. Additionally, MDC is utilized as an intermediate between CH and the sink to further enhance the QoS of WSNs, to reduce delays while collecting data, and improve the transmission phase of the LEACH protocol.
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spelling doaj.art-bf1a8dbf735c43e09497e08a2b9ecf2a2022-12-22T00:38:23ZengIEEEIEEE Access2169-35362022-01-0110581995821110.1109/ACCESS.2022.31784349783176Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH ProtocolRahma Gantassi0https://orcid.org/0000-0001-5833-3914Zaki Masood1https://orcid.org/0000-0002-3189-3943Yonghoon Choi2https://orcid.org/0000-0002-5218-4513Department of Electrical Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Electrical Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Electrical Engineering, Chonnam National University, Gwangju, South KoreaSome recent researches have shown that the energy consumption problem caused by data collection in a wireless sensor network (WSN) based on a static data collector is a main threat to the network lifetime. However, with the progress of the mobile terminal technology, the implementation of mobile data collectors (MDCs) has become more popular in large-scale WSNs, but it remains a big problem to improve the Quality of Service (QoS) criteria and minimize the energy consumption at the same time. However, most existing systems based on MDCs do not successfully strike a balance between routing energy consumption and QoS. In addition, most WSN protocols fail to maintain their impact when the network topology changes. Thus, for a dynamic WSN, it is important to support an intelligent MDC to continue data propagation despite the inevitable changes in the WSN topology. Considering all the above challenges, we propose a new intelligent MDC based on the traveling salesman problem (TSP) to determine the optimal path traveled by the MDC for energy efficiency and latency. Specifically, our proposed Mobile Data Collectors-Traveling Salesman Problem-Low Energy Adaptive Clustering Hierarchy-K-Means (MDC-TSP-LEACH-K) protocol uses K-Means and Grid clustering algorithm to decrease energy consumption in the cluster head (CH) election phase. Additionally, MDC is utilized as an intermediate between CH and the sink to further enhance the QoS of WSNs, to reduce delays while collecting data, and improve the transmission phase of the LEACH protocol.https://ieeexplore.ieee.org/document/9783176/Energy consumptionlarge-scale wireless sensor networksoptimal pathQoS
spellingShingle Rahma Gantassi
Zaki Masood
Yonghoon Choi
Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol
IEEE Access
Energy consumption
large-scale wireless sensor networks
optimal path
QoS
title Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol
title_full Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol
title_fullStr Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol
title_full_unstemmed Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol
title_short Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol
title_sort enhancing qos and residual energy by using of grid size clustering k means and tsp algorithms with mdc in leach protocol
topic Energy consumption
large-scale wireless sensor networks
optimal path
QoS
url https://ieeexplore.ieee.org/document/9783176/
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AT zakimasood enhancingqosandresidualenergybyusingofgridsizeclusteringkmeansandtspalgorithmswithmdcinleachprotocol
AT yonghoonchoi enhancingqosandresidualenergybyusingofgridsizeclusteringkmeansandtspalgorithmswithmdcinleachprotocol