Abstract:
Wireless Sensor Network is prominent among researchers and users for its unique data gathering and remote monitoring processes in adverse on-demand environments. Sensor nodes are battery dependant computational devices that have limited lifetime; to prolong the lifetime of these devices, energy optimization in WSNs becomes significant. Data aggregation conserves energy by integrating and transmitting data from different sources to the target node through a common aggregator. Extensive data aggregation techniques were proposed for energy optimization and to support data intensive transmissions in these networks. Cluster based adaptive and distributed data gathering protocols concentrate on extending lifetime of node and network with adequate data gathering. On account of change in multiple header and updation phases, the process of extending lifetime fails and transmission pause time increases. Transmission pause time in turn increases aggregation delay that reflects in end-to-end delay. Asynchronous information transmission increases routing loops which adds up data duplication and as well retards the flow rate after cluster head re-election. We put forth a distributed, fore hand status updating, data handling and node replacement algorithm called Efficient Energy and Load Balancing Data Aggregation (E2LBDA) Algorithm to minimize aggregation pause time and to avoid routing loops. Our algorithm further enhances the lifetime of the nodes by sharing data based on residual energy. Our manifold process not only improves energy conservation and network lifetime, but also minimizes delay and upholds network throughput.
