New Data Gathering Scheme for Large Scale Wireless Sensor Networks

Wireless Sensor Networks (WSNs) is getting larger in size and coverage area. Currently, some WSNs are having thousands of sensor nodes deployed to monitor critical regions or watch out for ecological phenomenon. Large Scale WSNs place strong challenges on many aspects of network modeling, deployment, protocols, and data gathering. Existing policies and techniques in WSNs need to be scaled efficiently as the average deployable network size increases. In this paper, we propose a new data gathering scheme based on Gray Cube backbone to tackle different challenging large network design issues. The Gray Cube is an efficient interconnection network with good connectivity and low values of network diameter and average distance. A comparative study is conducted by simulation to demonstrate the superiority of our scheme compared to other recently proposed techniques in terms of energy efficiency, gathering delay, scalability, and fault tolerance. Key-Words: sensor networks, energy efficient data gathering, Gray cube, distributed infrastructure, adaptive neighborhood discovery, fault tolerant data collection paths, energy efficient