Energy-efficient data redistribution in sensor networks
Kurkal, Rohini (2010). Energy-efficient data redistribution in sensor networks. -- In Proceedings: 6th Annual Symposium: Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p. 45-46
We tackle the data redistribution problem in data intensive sensor networks, which concerns how to redistribute the large volume of sensory data into the sensor networks wherein sensor nodes have limited storage space and battery energy. The goal of the problem is to minimize the energy consumption incurred by data redistribution, while fully utilizing the storage capacity in the DISNs. We first show that this problem is equivalent to the balanced assignment problem, which can be solved by the well-known Hungarian algorithm. However, there are two limitations of this approach. First, the Hungarian algorithm gives O(Nm) time complexity where N is the total number of sensor nodes in the network and m is the average storage capacity of each node. Second, Hungarian algorithm is a centralized algorithm, which cannot be easily implemented in a distributed manner. In our work, we design a fully distributed, highly scalable, and efficient data distributed mechanism. Using our own simulator (written in C language) we show that our distributed algorithm outperforms the existing data redistribution techniques in sensor networks in terms of energy consumption for data redistribution.
Paper presented to the 6th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Hughes Metropolitan Complex, Wichita State University, April 23, 2010.