Authors: Govind Gupta; Manoj Misra; Kumkum Garg
Addresses: Department of Electronics and Computer Engineering, Indian Institute of Technology, Roorkee, 247667, India ' Department of Electronics and Computer Engineering, Indian Institute of Technology, Roorkee, 247667, India ' Department of Computer Science and Engineering, Manipal University, Jaipur, 302026, India
Abstract: In wireless sensor network, sensor readings generated by nearby nodes are redundant and highly correlated, both in space and time domains. Since transmitting redundant and highly correlated data incurs a huge waste of energy and bandwidth, spatial and temporal correlation should be exploited in order to reduce redundant data transmission. In this paper, we propose an energy efficient data gathering protocol that uses a prediction-based filtering (EEDGPF) mechanism to solve the problem of redundant data transmissions. Our data gathering protocol organises a WSN into clusters, using data similarity that exists in readings of sensor nodes and cluster heads and uses a GARCH (1, 1) model-based non-linear predictor to exploit the temporal correlation of sensor readings. Experimental results over real dataset show that our protocol significantly outperforms linear predictor (AR(3))-based protocol proposed in Jiang et al. (2011), in terms of number of data packets delivered, number of successful predictions and average energy consumption.
Keywords: wireless sensor networks; WSNs; data filtering; nonlinear predictor; spatial clustering; energy efficiency; data collection; prediction based filtering; energy consumption.
International Journal of Information and Communication Technology, 2013 Vol.5 No.1, pp.75 - 94
Received: 05 Sep 2012
Accepted: 09 Nov 2012
Published online: 26 Feb 2013 *