A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes’ energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization...

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Main Authors: Alyani Ismail, Mohd Fadlee A. Rasid, Ahmed M. Shamsan Saleh, Borhanuddin Mohd Ali
Format: Article
Language:English
Published: MDPI AG 2012-08-01
Series:Sensors
Subjects:
Online Access:http://w1.mdpi.com/1424-8220/12/8/11307
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spelling doaj-5e9e4995a1c942b9828f4fa593f51ee72020-11-25T00:52:16ZengMDPI AGSensors1424-82202012-08-01128113071133310.3390/s120811307A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAntAlyani IsmailMohd Fadlee A. RasidAhmed M. Shamsan SalehBorhanuddin Mohd AliPlanning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes’ energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes’ resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.http://w1.mdpi.com/1424-8220/12/8/11307energy balancingenergy consumptionant colonybattery lifetimeWSNs
collection DOAJ
language English
format Article
sources DOAJ
author Alyani Ismail
Mohd Fadlee A. Rasid
Ahmed M. Shamsan Saleh
Borhanuddin Mohd Ali
spellingShingle Alyani Ismail
Mohd Fadlee A. Rasid
Ahmed M. Shamsan Saleh
Borhanuddin Mohd Ali
A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt
Sensors
energy balancing
energy consumption
ant colony
battery lifetime
WSNs
author_facet Alyani Ismail
Mohd Fadlee A. Rasid
Ahmed M. Shamsan Saleh
Borhanuddin Mohd Ali
author_sort Alyani Ismail
title A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt
title_short A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt
title_full A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt
title_fullStr A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt
title_full_unstemmed A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt
title_sort self-optimizing scheme for energy balanced routing in wireless sensor networks using sensorant
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2012-08-01
description Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes’ energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes’ resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.
topic energy balancing
energy consumption
ant colony
battery lifetime
WSNs
url http://w1.mdpi.com/1424-8220/12/8/11307
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