title: Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.
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.
authors.affiliation: Department of Computer Science and Engineering, Nandha Engineering College,Erode, Tamilnadu.
authors.forename: Thirumoorthy
authors.initials: T
authors.lastname: Palanisamy
authors.affiliation: Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, Tamilnadu, India.
authors.forename: Karthikeyan N
authors.initials: KN
authors.lastname: Krishnasamy
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003195:Computer Communication Networks / Q000295:instrumentation*; D012044:Regression Analysis; D013997:Time Factors; D059015:Wireless Technology / Q000295:instrumentation*