One of the most important design objectives in wireless sensor networks (WSN) is minimizing the energy consumption since these networks are expected to operate in harsh conditions where the recharging of batteries is impractical, if not impossible. The sleep scheduling mechanism allows sensors to sleep intermittently in order to reduce energy consumption and extend network lifetime. In applications where 100% coverage of the network field is not crucial, allowing the coverage to drop below full coverage while keeping above a predetermined threshold, i.e., partial coverage, can further increase the network lifetime. In this paper, we develop the distributed adaptive sleep scheduling algorithm (DASSA) for WSNs with partial coverage. DASSA does not require location information of sensors while maintaining connectivity and satisfying a user defined coverage target. In DASSA, nodes use the residual energy levels and feedback from the sink for scheduling the activity of their neighbors. This feedback mechanism reduces the randomness in scheduling that would otherwise occur due to the absence of location information. The performance of DASSA is compared with an integer linear programming (ILP) based centralized sleep scheduling algorithm (CSSA), which is devised to find the maximum number of rounds the network can survive assuming that the location information of all sensors is available. DASSA is also compared with the decentralized DGT algorithm. DASSA attains network lifetimes up to 92% of the centralized solution and it achieves significantly longer lifetimes compared with the DGT algorithm.
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Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2005). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.
Wang, L., & Xiao, Y. (2006). A survey of energy-efficient scheduling mechanisms in sensor networks. Mobile Networks and Applications, 11(5), 723–740.
Xu, Y., Heidemann, J., & Estrin, D. (2001). Geography-informed energy conservation for ad hoc routing. In Proceedings of ACM MOBICOM.
Chen, B., Jamieson, K., Balakrishnan, H., & Morris, R. (2001). Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. In Mobile Computing and Networking, pp. 85–96.
Cerpa, A., & Estrin, D. (2002). ASCENT: Adaptive self-configuring sensor networks topologies. In Proceedings of IEEE INFOCOM, June 2002.
Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of IEEE INFOCOM, pp. 1567–1576.
Ye, F., Zhong, G., Cheng, J., Lu, S., & Zhang, L. (2003). PEAS: A robust energy conserving protocol for long-lived sensor networks. In ICDCS ’03: Proceedings of the 23rd International Conference on Distributed Computing Systems, Providence, Rhode Island, USA, p. 28.
Meguerdichian, S., & Potkonjak, M. (2003). Low power 0/1 coverage and scheduling techniques in sensor networks. University of California Los Angeles, Technical Reports 030001, January 2003.
Tian, D., & Georganas, N. (2002). A coverage-preserving node scheduling scheme for large wireless sensor networks. In First ACM International Workshop on Wireless Sensor Networks and Applications.
Tian, D., & Georganas, N. (2003). A node scheduling scheme for energy conservation in large wireless sensor networks. Wireless Communications and Mobile Computing, 3(2), 271–290.
Boukerche, A., Fei, X., Araujo, R. B., & Patnaik, P. (2006). A local information exchange based coverage-preserving protocol for wireless sensor networks. In Proceedings of IEEE ICC.
Gupta, H., Das, S., & Gu, Q. (2003). Connected sensor cover: Self organization of sensor networks for efficient query execution. In ACM Mobile Adhoc Network Symposium (MOBIHOC), pp. 189–199.
Cardei, M., & Du, D.-Z. (2005). Improving wireless sensor network lifetime through power aware organization. Wireless Networks, 11(3), 333–340.
Wang, X., Zhang, Q., Sun, W., Wang, W., & Shi, B. (2006). A coverage-based maximum lifetime data gathering algorithm in sensor networks. In MDM ’06: Proceedings of the 7th International Conference on Mobile Data Management (MDM’06) (p. 33). Washington, DC, USA: IEEE Computer Society.
Wang, X. et al. (2003). Integrated coverage and connectivity configuration in wireless sensor networks. In Proceedings of Sensys.
Zhang, H., & Hou, J. C. (2005). Maintaining sensing coverage and connectivity in large sensor networks. International Journal of Wireless Ad Hoc and Sensor Networks, 1(12), 89–124.
Liu, Y., & Liang, W. (2005). Approximate coverage in wireless sensor networks. In Proceedings of 30th Annual IEEE Conference on Local Computer Networks, IEEE Computer Society, November 2005, pp. 68–75.
Xu, Y., Heidemann, J., & Estrin, D. (2005). pCover: Partial coverage for long-lived surveillance sensor networks. Department of Computer Science, Michigan State University, Tech. Rep., November 2005.
Lu, J., & Suda, T. (2003). Coverage-aware self-scheduling in sensor networks. In IEEE 18th Annual Workshop on Computer Communications, October 2003, pp. 117–123.
Zhang, H., & Hou, J. (2004). On deriving the upper bound of α-lifetime for large sensor networks. In MobiHoc ’04 (pp. 121–132). New York, NY, USA: ACM Press.
Wu, K., Gao, Y., Li, F., & Xiao, Y. (2005). Lightweight deployment-aware scheduling for wireless sensor networks. ACM/Kluwer MONET Journal, Special Issue on Energy Constraints and Lifetime Performance in Wireless Sensor Networks, 10(6), 837–852.
Choi, W., & Das, S. K. (2005). A novel framework for energy-conserving data gathering in wireless sensor networks. In Proceedings of IEEE INFOCOM, March 2005.
Yang, X., & Vaidya, N. H. (2004). A wakeup scheme for sensor networks: Achieving balance between energy saving and end-to-end delay. In RTAS ’04: 10th IEEE Real-Time and Embedded Technology and Applications Symposium, pp. 19–26.
Elson, J., & Estrin, D. (2001). Time synchronization for wireless sensor networks. In 15th International Parallel & Distributed Processing Symposium (IPDPS).
Ganeriwal, S., Kumar, R., & Srivastava, M. B. (2003). Timing-sync protocol for sensor networks. In ACM Conference on Embedded Networked Sensor Systems (SENSYS).
Rajendran, V., Obraczka, K., & Garcia-Luna-Aceves, J. J. (2003). Energy-efficient collision-free medium access control for wireless sensor networks. In SenSys ’03: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, pp. 181–192.
Yardibi, T. (2006). Sleep scheduling for energy conservation in wireless sensor networks with partial coverage. Master’s thesis, Bilkent University, Ankara, [Online]. Available: http://www.ee.bilkent.edu.tr/ytarik/thesis.pdf
Hohlt, B., Doherty, L., & Brewer, E. (2004). Flexible power scheduling for sensor networks. In IPSN ’04: Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks, pp. 205–214.
Leuschner, C. J. (2005). The design of a simple energy efficient routing protocol to improve wireless sensor network lifetime. MS thesis. Faculty of Engineering, University of Pretoria, April 2005.
ILOG CPLEX 10.0. [Online]. Available: http://www.ilog.com/products/cplex/
Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In HICSS ’00 (p. 8020). Washington, DC, USA: IEEE Computer Society.
Boulis, A., Ganeriwal, S., & Srivastava, M. B. (2003). Aggregation in sensor networks: An energy-accuracy trade-off. Elsevier Ad Hoc Networks, 1(23), 317–331.
This research has been conducted within the NEWCOM++ Network of Excellence in Wireless Communications funded through the EC 7th Framework Programme.
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Yardibi, T., Karasan, E. A distributed activity scheduling algorithm for wireless sensor networks with partial coverage. Wireless Netw 16, 213–225 (2010). https://doi.org/10.1007/s11276-008-0125-2
- Wireless sensor networks
- Energy efficiency
- Sleep/activity scheduling
- Partial coverage