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A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

Shamsan Saleh AM, Ali BM, Rasid MF, Ismail A - Sensors (Basel) (2012)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia. ah_almshreqy@yahoo.com

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Comparison of throughput between Static and Mobile-SensorAnt with different sensors.
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f17-sensors-12-11307: Comparison of throughput between Static and Mobile-SensorAnt with different sensors.

Mentions: the result presented here compares the Static-SensorAnt and the Mobile-SensorAnt as the number of sensor nodes varies. Figure 17 demonstrates that the Mobile-SensorAnt obtains better throughput compared to the Static-SensorAnt. This is because in the static case, the congestion and message drops occur more than in the mobile case. Moreover, notice that the difference between the two cases is not too much, which is indicative of the fact that adaptation of the proposed SensorAnt scheme from the static to a mobile environment is indeed feasible.


A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

Shamsan Saleh AM, Ali BM, Rasid MF, Ismail A - Sensors (Basel) (2012)

Comparison of throughput between Static and Mobile-SensorAnt with different sensors.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472886&req=5

f17-sensors-12-11307: Comparison of throughput between Static and Mobile-SensorAnt with different sensors.
Mentions: the result presented here compares the Static-SensorAnt and the Mobile-SensorAnt as the number of sensor nodes varies. Figure 17 demonstrates that the Mobile-SensorAnt obtains better throughput compared to the Static-SensorAnt. This is because in the static case, the congestion and message drops occur more than in the mobile case. Moreover, notice that the difference between the two cases is not too much, which is indicative of the fact that adaptation of the proposed SensorAnt scheme from the static to a mobile environment is indeed feasible.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia. ah_almshreqy@yahoo.com

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus