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Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Palanisamy T, Krishnasamy KN - PLoS ONE (2015)

Bottom Line: To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network.Finally, the Poly Distribute algorithm effectively distributes the sensor nodes.Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Nandha Engineering College,Erode, Tamilnadu.

ABSTRACT
Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

No MeSH data available.


Related in: MedlinePlus

Measure of energy consumption.
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pone.0138932.g003: Measure of energy consumption.

Mentions: Fig 3 depicts the energy consumption based on different sensor nodes. Our proposed BNEPD technique performs extensively well when compared to two other methods DRINA [1] and CBPS [2]. As illustrated in the Fig, the energy consumption is reduced than the two other methods with the application of Bayes Node Energy Distribution and had better changes when compared to the periodic aggregation applied in the existing technique and therefore provided reliable routing in Wireless Sensor Networks. In case of BNEPD technique, the Bayes Node Energy Distribution distributes the sensor nodes that detect an object of similar event into specific regions ensuring minimized energy consumption. By applying Bayes principle between source node and the target objects, for effective similar object detection, the energy consumption is reduced by 3–13% compared to DRINA and 17–23% compared to CBPS respectively.


Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Palanisamy T, Krishnasamy KN - PLoS ONE (2015)

Measure of energy consumption.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4591332&req=5

pone.0138932.g003: Measure of energy consumption.
Mentions: Fig 3 depicts the energy consumption based on different sensor nodes. Our proposed BNEPD technique performs extensively well when compared to two other methods DRINA [1] and CBPS [2]. As illustrated in the Fig, the energy consumption is reduced than the two other methods with the application of Bayes Node Energy Distribution and had better changes when compared to the periodic aggregation applied in the existing technique and therefore provided reliable routing in Wireless Sensor Networks. In case of BNEPD technique, the Bayes Node Energy Distribution distributes the sensor nodes that detect an object of similar event into specific regions ensuring minimized energy consumption. By applying Bayes principle between source node and the target objects, for effective similar object detection, the energy consumption is reduced by 3–13% compared to DRINA and 17–23% compared to CBPS respectively.

Bottom Line: To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network.Finally, the Poly Distribute algorithm effectively distributes the sensor nodes.Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Nandha Engineering College,Erode, Tamilnadu.

ABSTRACT
Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

No MeSH data available.


Related in: MedlinePlus