Abstract: Currently, the wireless sensor network is facing four major issues namely power management, routing, localization and deployment techniques. Out of these in power management, energy conservation is the major constraint due to irreplaceable and limited power sources of the sensor nodes. Therefore, efficient cluster formation is very challenging in WSNs by considering the energy consumption of cluster heads. In this research, we propose a novel enhanced data routing For In-Network Aggregation algorithm is that here we are using the concept of intelligent routing, i.e., ant colony optimization which provides optimized path for route formation that connects to all source nodes to sink while maximizing data aggregation throughout the whole network. The projected algorithm was extensively compared to other known solution: data routing for in-network aggregation algorithm. Our results clearly indicate that routing path built by genetically driven algorithm providesoptimized routing quality and best aggregation quality with more energy consumption when compared to other algorithm.
Rimple Manni, M.K. Rai and Lavish Kansal, 2015. EDRINA: Enhanced Data Routing for In-Network Aggregation Algorithm for WSNS. Asian Journal of Information Technology, 14: 276-280.