Energy efficient latency optimized data gathering framework for wireless sensor networks

Abstract

Wireless Sensor Networks (WSN) consist of large number of inexpensive sensor nodes, which are deployed densely in the field to collect information and transmit it to the base station wirelessly. The densely deployed nodes exhibit high correlation in their sensed data and hence it is not required to transmit the similar information by many nodes individually. In the present work, a data aggregation framework for real time applications is proposed which maximizes the lifetime of the network and delivers the aggregated data to the sink before the deadline with more accuracy and aggregation gain. This framework has two phases, (i) construction of data gathering tree with the objective of maximizing the lifetime of the network and (ii) aggregation timeout model to minimize the delay and maximize the aggregation gain and accuracy. In the first phase, the data aggregation tree (DAT) is constructed, which is based on the new routing protocol Energy and Link Quality based Routing (ELQR). In the second phase, the timing model for the aggregation framework is proposed. Two models were proposed the time synchronized model and the non time synchronized model. In the non-time synchronized algorithm, Delay Efficient Aggregation Timing Model (DEATM), each node calculates the initial timeout period for data aggregation to ensure that the parent s timeout takes place after the completion of timeout of all its children. In the time synchronized model, Distributed Least Cost First (DLCF) algorithm, the deadline is divided into number of time slots and each node chooses a particular time slot, which is based on the number of children it has in its sub tree. The data aggregation framework is implemented over ELQR algorithm which is an energy efficient algorithm and hence the complete data aggregation framework increases the lifetime of the network and deliver the data to the sink in an energy efficient manner. newline newline newline