EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications

The Internet of Things (IoT) integrates different advanced technologies in which a wireless sensor network (WSN) with many smart micro-sensor nodes is an important portion of building various IoT applications such as smart agriculture systems, smart healthcare systems, smart home or monitoring envir...

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Main Authors: Nguyen Duy Tan, Duy-Ngoc Nguyen, Hong-Nhat Hoang, Thi-Thu-Huong Le
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Computers
Subjects:
Online Access:https://www.mdpi.com/2073-431X/12/5/103
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author Nguyen Duy Tan
Duy-Ngoc Nguyen
Hong-Nhat Hoang
Thi-Thu-Huong Le
author_facet Nguyen Duy Tan
Duy-Ngoc Nguyen
Hong-Nhat Hoang
Thi-Thu-Huong Le
author_sort Nguyen Duy Tan
collection DOAJ
description The Internet of Things (IoT) integrates different advanced technologies in which a wireless sensor network (WSN) with many smart micro-sensor nodes is an important portion of building various IoT applications such as smart agriculture systems, smart healthcare systems, smart home or monitoring environments, etc. However, the limited energy resources of sensors and the harsh properties of the WSN deployment environment make routing a challenging task. To defeat this routing quandary, an energy-efficient routing protocol based on grid cells (EEGT) is proposed in this study to improve the lifespan of WSN-based IoT applications. In EEGT, the whole network region is separated into virtual grid cells (clusters) at which the number of sensor nodes is balanced among cells. Then, a cluster head node (CHN) is chosen according to the residual energy and the distance between the sink and nodes in each cell. Moreover, to determine the paths for data delivery inside the cell with small energy utilization, the Kruskal algorithm is applied to connect nodes in each cell and their CHN into a minimum spanning tree (MST). Further, the ant colony algorithm is also used to find the paths of transmitting data packets from CHNs to the sink (outside cell) to reduce energy utilization. The simulation results show that the performance of EEGT is better than the three existing protocols, which are LEACH-C (low energy adaptive clustering hierarchy), PEGASIS (power-efficient gathering in sensor information systems), and PEGCP (maximizing WSN life using power-efficient grid-chain routing protocol) in terms of improved energy efficiency and extended the lifespan of the network.
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spelling doaj.art-033e30063af94083b6b57adc8d1a02502023-11-18T00:58:27ZengMDPI AGComputers2073-431X2023-05-0112510310.3390/computers12050103EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT ApplicationsNguyen Duy Tan0Duy-Ngoc Nguyen1Hong-Nhat Hoang2Thi-Thu-Huong Le3Faculty of Information Technology, Hung Yen University of Technology and Education, Hung Yen 160000, VietnamFaculty of Information Technology, Hung Yen University of Technology and Education, Hung Yen 160000, VietnamSchool of Computer Science and Engineering, Pusan National University, Busan 609735, Republic of KoreaFaculty of Information Technology, Hung Yen University of Technology and Education, Hung Yen 160000, VietnamThe Internet of Things (IoT) integrates different advanced technologies in which a wireless sensor network (WSN) with many smart micro-sensor nodes is an important portion of building various IoT applications such as smart agriculture systems, smart healthcare systems, smart home or monitoring environments, etc. However, the limited energy resources of sensors and the harsh properties of the WSN deployment environment make routing a challenging task. To defeat this routing quandary, an energy-efficient routing protocol based on grid cells (EEGT) is proposed in this study to improve the lifespan of WSN-based IoT applications. In EEGT, the whole network region is separated into virtual grid cells (clusters) at which the number of sensor nodes is balanced among cells. Then, a cluster head node (CHN) is chosen according to the residual energy and the distance between the sink and nodes in each cell. Moreover, to determine the paths for data delivery inside the cell with small energy utilization, the Kruskal algorithm is applied to connect nodes in each cell and their CHN into a minimum spanning tree (MST). Further, the ant colony algorithm is also used to find the paths of transmitting data packets from CHNs to the sink (outside cell) to reduce energy utilization. The simulation results show that the performance of EEGT is better than the three existing protocols, which are LEACH-C (low energy adaptive clustering hierarchy), PEGASIS (power-efficient gathering in sensor information systems), and PEGCP (maximizing WSN life using power-efficient grid-chain routing protocol) in terms of improved energy efficiency and extended the lifespan of the network.https://www.mdpi.com/2073-431X/12/5/103Internet of Thingswireless sensor networksenergy-efficientclustering routing protocolgrid-baseddata fusion
spellingShingle Nguyen Duy Tan
Duy-Ngoc Nguyen
Hong-Nhat Hoang
Thi-Thu-Huong Le
EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications
Computers
Internet of Things
wireless sensor networks
energy-efficient
clustering routing protocol
grid-based
data fusion
title EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications
title_full EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications
title_fullStr EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications
title_full_unstemmed EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications
title_short EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications
title_sort eegt energy efficient grid based routing protocol in wireless sensor networks for iot applications
topic Internet of Things
wireless sensor networks
energy-efficient
clustering routing protocol
grid-based
data fusion
url https://www.mdpi.com/2073-431X/12/5/103
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