Prediction Algorithms for Improving Network Lifetime in WSNs

The localized, self organizing, robust, scalable and energy-efficient data aggregation tree approaches for sensor networks, is called as Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs). L-PEDAPs are based on LMST and RNG topologies, which can be estimated minimum spanning tree and can be computed efficiently using only position or distance information of one-hop neighbors. In order to use the sensor networks for long duration an efficient utilization of energy is essential because the sensor nodes are battery driven. The routing tree is constructed over these topologies and also considers different parent selection strategies. Then compare each topology and parent selection strategy and conclude that the best among them is the shortest path strategy over LMST structure. To reduce data traffic inside sensor networks, reduce the amount of data that need to send to base station. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. To propose a new algorithm to evaluate the node lifetime and the link lifetime utilizing the dynamic nature, such as the energy drain rate and the relative mobility estimation rate of nodes. The proposed solution is furthermore adapted to consider the node lifetime and link lifetime prediction algorithm in order to increase the network lifetime.