Task Decomposing Optimization in Wireless Sensor Network

Numerous techniques available in the area of wireless sensor network to optimize the energy requirement. Several software and hardware approaches are existing for same purpose. For minimizing the energy, bandwidth and maximizing the security, shortest route is followed by Greedy and many hybrid heuristic algorithms. By proper management of load balancing, a significant life years and performance can extend in WSNs. Load management is one of the other very precise fields in literature. Transport layer computational loading ensures accurate delivery with sufficient aspects of energy and memory in WSNs. Balanced loading is primarily focus rather than equal distribution among all nodes. Load balancing improves the application responsiveness and life time. Complicated task performance is creating a very heavy load in WSN and resulting complex computation, large communication overhead, large amount of information, and high energy requirement. In this paper, we tried to decompose the complex tasks into divisional parts for smooth operation and transmission among nodes in WSNs. This paper considered advance surveillance management as complicated task and tried to decompose in some easy tasks as layering systems. Three layered task subdivision is providing better energy consumption. More sub-layers can also be increased in development of efficient load management.