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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 drain rate
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pone.0138932.g004: Measure of energy drain rate

Mentions: Fig 4 shows the energy draining rate variations of 350 different nodes over a period of simulation time. Simulations are conducted through static and dynamic node positioning ranging from 50 to 350 nodes. From the Fig it is clear that as the number of sensor nodes increases the draining rate also increases. This is because of the application of polynomial regression function in BNEPD technique that maintains high energy nodes in the routing path with the objective of reducing the energy drain rate by 14–34% compared to DRINA and therefore improving the overall network. Also by applying the polynomial function, the coefficient values of the regression is obtained for each object. At the same time, separate coefficient values are obtained for pressure, temperature and so on, therefore reducing the energy drain rate by 44–62% 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 drain rate
© Copyright Policy
Related In: Results  -  Collection

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

pone.0138932.g004: Measure of energy drain rate
Mentions: Fig 4 shows the energy draining rate variations of 350 different nodes over a period of simulation time. Simulations are conducted through static and dynamic node positioning ranging from 50 to 350 nodes. From the Fig it is clear that as the number of sensor nodes increases the draining rate also increases. This is because of the application of polynomial regression function in BNEPD technique that maintains high energy nodes in the routing path with the objective of reducing the energy drain rate by 14–34% compared to DRINA and therefore improving the overall network. Also by applying the polynomial function, the coefficient values of the regression is obtained for each object. At the same time, separate coefficient values are obtained for pressure, temperature and so on, therefore reducing the energy drain rate by 44–62% 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