Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer

Wireless sensor network (WSN) nodes are devices with limited power, and rational utilization of node energy and prolonging the network lifetime are the main objectives of the WSN’s routing protocol. However, irrational considerations of heterogeneity of node energy will lead to an energy i...

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Main Authors: Xiaoqiang Zhao, Shaoya Ren, Heng Quan, Qiang Gao
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/3/820
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spelling doaj-1218c8aa6ccc4d17be39484fcfd543de2020-11-25T02:05:53ZengMDPI AGSensors1424-82202020-02-0120382010.3390/s20030820s20030820Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf OptimizerXiaoqiang Zhao0Shaoya Ren1Heng Quan2Qiang Gao3School of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaSchool of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaSchool of Communication and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaCollege of Mechanical and Electronic Engineering, Northwest Agriculture and Forestry University, Yangling 712100, ChinaWireless sensor network (WSN) nodes are devices with limited power, and rational utilization of node energy and prolonging the network lifetime are the main objectives of the WSN’s routing protocol. However, irrational considerations of heterogeneity of node energy will lead to an energy imbalance between nodes in heterogeneous WSNs (HWSNs). Therefore, in this paper, a routing protocol for HWSNs based on the modified grey wolf optimizer (HMGWO) is proposed. First, the protocol selects the appropriate initial clusters by defining different fitness functions for heterogeneous energy nodes; the nodes’ fitness values are then calculated and treated as initial weights in the GWO. At the same time, the weights are dynamically updated according to the distance between the wolves and their prey and coefficient vectors to improve the GWO’s optimization ability and ensure the selection of the optimal cluster heads (CHs). The experimental results indicate that the network lifecycle of the HMGWO protocol improves by 55.7%, 31.9%, 46.3%, and 27.0%, respectively, compared with the stable election protocol (SEP), distributed energy-efficient clustering algorithm (DEEC), modified SEP (M-SEP), and fitness-value-based improved GWO (FIGWO) protocols. In terms of the power consumption and network throughput, the HMGWO is also superior to other protocols.https://www.mdpi.com/1424-8220/20/3/820heterogeneous wireless sensor networksgrey wolf optimizernetwork lifecycleenergy consumption
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoqiang Zhao
Shaoya Ren
Heng Quan
Qiang Gao
spellingShingle Xiaoqiang Zhao
Shaoya Ren
Heng Quan
Qiang Gao
Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer
Sensors
heterogeneous wireless sensor networks
grey wolf optimizer
network lifecycle
energy consumption
author_facet Xiaoqiang Zhao
Shaoya Ren
Heng Quan
Qiang Gao
author_sort Xiaoqiang Zhao
title Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer
title_short Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer
title_full Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer
title_fullStr Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer
title_full_unstemmed Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer
title_sort routing protocol for heterogeneous wireless sensor networks based on a modified grey wolf optimizer
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2020-02-01
description Wireless sensor network (WSN) nodes are devices with limited power, and rational utilization of node energy and prolonging the network lifetime are the main objectives of the WSN’s routing protocol. However, irrational considerations of heterogeneity of node energy will lead to an energy imbalance between nodes in heterogeneous WSNs (HWSNs). Therefore, in this paper, a routing protocol for HWSNs based on the modified grey wolf optimizer (HMGWO) is proposed. First, the protocol selects the appropriate initial clusters by defining different fitness functions for heterogeneous energy nodes; the nodes’ fitness values are then calculated and treated as initial weights in the GWO. At the same time, the weights are dynamically updated according to the distance between the wolves and their prey and coefficient vectors to improve the GWO’s optimization ability and ensure the selection of the optimal cluster heads (CHs). The experimental results indicate that the network lifecycle of the HMGWO protocol improves by 55.7%, 31.9%, 46.3%, and 27.0%, respectively, compared with the stable election protocol (SEP), distributed energy-efficient clustering algorithm (DEEC), modified SEP (M-SEP), and fitness-value-based improved GWO (FIGWO) protocols. In terms of the power consumption and network throughput, the HMGWO is also superior to other protocols.
topic heterogeneous wireless sensor networks
grey wolf optimizer
network lifecycle
energy consumption
url https://www.mdpi.com/1424-8220/20/3/820
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