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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Online Access: | http://w1.mdpi.com/1424-8220/12/8/11307 |
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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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