Continuous monitoring of global events in sensor networks

Authors:
Yongxuan Lai;Yilong Chen;Hong Chen
Affiliations:
Information School, Renmin University of China, Beijing 100872, PR China/ Key Laboratory of Data Engineering and Knowledge Engineering, MOE, PR China.;Information School, Renmin University of China, Beijing 100872, PR China/ Key Laboratory of Data Engineering and Knowledge Engineering, MOE, PR China.;Information School, Renmin University of China, Beijing 100872, PR China/ Key Laboratory of Data Engineering and Knowledge Engineering, MOE, PR China
Venue:
International Journal of Sensor Networks
Year:
2010

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Abstract

Event detection is an essential application in Wireless Sensor Networks (WSNs), especially for the monitoring of physical world. While most previous research focuses on the detection of local events, in this paper we propose novel algorithms to energy efficiently detect events of large and global scale. We divide a global event into regional events, so the detection algorithm can be executed distributively inside the network. Our approach also takes advantage of the temporal correlations of sensing data to gain energy efficiency. It uses a bound-suppression mechanism to set bounds and suppresses 'silent' regional events, cutting down the transmissions. Simulation results show that the proposed c-GEDA (Continuous Global Event Detection Algorithm) is efficient to reduce the cost of transmissions, and it gains more than 50% of cost reduction compared with the previous detection approaches.