PAS: Prediction-based Adaptive Sleeping for Environment Monitoring in Sensor Networks

Energy efficiency has proven to be an important factor dominating the working period of WSN surveillance systems. Intensive studies have been done to provide energy efficient power management mechanisms. In this paper, we present PAS, a Prediction-based Adaptive Sleeping mechanism for environment monitoring sensor networks to conserve energy. PAS focuses on the diffusion stimulus (DS) scenario, which is very common and important in the application of environment monitoring. Different with most of previous works, PAS explores the features of DS spreading process to obtain higher energy efficiency. In PAS, sensors determine their sleeping schedules based on the observed emergency of DS spreading. While sensors near the DS boundary stay awake to accurately capture the possible stimulus arrival, the far away sensors turn into sleeping mode to conserve energy. Simulation experiment shows that PAS largely reduces the energy cost without decreasing system performance.

[1]  Yunhao Liu,et al.  Non-Threshold based Event Detection for 3D Environment Monitoring in Sensor Networks , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).

[2]  Gaurav S. Sukhatme,et al.  Call and response: experiments in sampling the environment , 2004, SenSys '04.

[3]  Lionel M. Ni,et al.  Stimulus-based adaptive sleeping for wireless sensor networks , 2005, 2005 International Conference on Parallel Processing (ICPP'05).

[4]  Tarek F. Abdelzaher,et al.  Towards optimal sleep scheduling in sensor networks for rare-event detection , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[5]  Chua-Huang Huang,et al.  2003 International Conference on Parallel Processing Workshops , 2003 .

[6]  Peter I. Corke,et al.  Data collection, storage, and retrieval with an underwater sensor network , 2005, SenSys '05.

[7]  David E. Culler,et al.  Telos: enabling ultra-low power wireless research , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[8]  Deborah Estrin,et al.  Habitat monitoring with sensor networks , 2004, CACM.

[9]  Deborah Estrin,et al.  Geography-informed energy conservation for Ad Hoc routing , 2001, MobiCom '01.

[10]  Yunhao Liu,et al.  Iso-Map: Energy-Efficient Contour Mapping in Wireless Sensor Networks , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).

[11]  Songwu Lu,et al.  PEAS: a robust energy conserving protocol for long-lived sensor networks , 2002, 10th IEEE International Conference on Network Protocols, 2002. Proceedings..

[12]  Robert Tappan Morris,et al.  Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks , 2001, MobiCom '01.

[13]  Mani B. Srivastava,et al.  Topology management for sensor networks: exploiting latency and density , 2002, MobiHoc '02.

[14]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[15]  Yunhao Liu,et al.  Contour map matching for event detection in sensor networks , 2006, SIGMOD Conference.

[16]  Yunhao Liu,et al.  Underground Structure Monitoring with Wireless Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[17]  Rong Zheng,et al.  Asynchronous wakeup for ad hoc networks , 2003, MobiHoc '03.

[18]  Vinayak S. Naik,et al.  A line in the sand: a wireless sensor network for target detection, classification, and tracking , 2004, Comput. Networks.