EDGS: Efficient data gathering scheme for dense Wireless Sensor Networks

Dense and large scale Wireless Sensor Networks (WSNs) require strategies for data gathering with efficient, scalable, robust, large area coverage, and extended network lifetime attributes. We propose a novel and efficient data gathering algorithm, EDGS, to collect data in these challenging WSNs. EDGS creates virtual network backbone based on regular graph structure called the Gray Cube. Several short multi-hop data collection paths are embedded in the cube´s communication tree. The backbone nodes are subset of the WSN nodes and act as access points for other nodes. The virtual backbone has good connectivity, low network diameter, and short average path length. EDGS balances energy consumption, shorten delay, and replaces dead sensors through reconfiguration. Several versions of EDGS are presented using adaptive top-down and bottom-up techniques. A comparative study is conducted using modeling and simulation to demonstrate EDGS´s efficiency and superiority compared to other recently proposed techniques in terms of energy consumption, gathering delay, scalability, QoS requirements, and fault tolerance.