Abstract
Wireless Sensor Network (WSN) technology has recently moved out of controlled laboratory settings to real-world deployments. Many of these deployments experience high rates of failure. Common types of failure include node failure, link failure, and node reboot. Due to the resource constraints of sensor nodes, existing techniques for fault detection in enterprise networks are not applicable. Previously proposed WSN fault detection algorithms either rely on periodic transmission of node status data or inferring node status based on passive information collection. The former approach significantly reduces network lifetime, while the latter achieves poor accuracy in dynamic or large networks. Herein, we propose Sequence-Based Fault Detection (SBFD), a novel framework for network fault detection in WSNs. The framework exploits in-network packet tagging using the Fletcher checksum and server-side network path analysis to efficiently deduce the path of all packets sent to the sink. The sink monitors the extracted packet paths to detect persistent path changes which are indicative of network failures. When a failure is suspected, the sink uses control messages to check the status of the affected nodes. SBFD was implemented in TinyOS on TelosB motes and its performance was assessed in a testbed network and in TOSSIM simulation. The method was found to achieve a fault detection accuracy of 90.7% to 95.0% for networks of 25 to 400 nodes at the cost of 0.164% to 0.239% additional control packets and a 0.5% reduction in node lifetime due to in-network packet tagging. Finally, a comparative study was conducted with existing solutions.
- A. Arora, P. Dutta, S. Bapat, V. Kulathumani, H. Zhang, V. Naik, V. Mittal, H. Cao, M. Gouda, Y. Choi, T. Herman, S. Kulkarni, U. Arumugam, M. Nesterenko, A. Vora, and M. Miyashita. 2004. A line in the sand: A wireless sensor network for target detection, classification, and tracking. Comput. Netw. 46, 605--634. Google ScholarDigital Library
- R. Beckwith, D. Teibel, and P. Bowen. 2004. Unwired wine: Sensor networks in vineyards. In Proceedings of the IEEE Conference on Sensors. 561--564.Google Scholar
- P. Buonadonna, D. Gay, J. M. Hellerstein, W. Hong, and S. Madden. 2005. Task: Sensor network in a box. In Proceedings of the European Workshop on Sensor Networks. 133--144.Google Scholar
- B.-R. Chen, G. Peterson, G. Mainland, and M. Welsh. 2008. Livenet: Using passive monitoring to reconstruct sensor network dynamics. In Proceedings of the 4th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'08). Springer, 79--98. Google ScholarDigital Library
- P. Corke, T. Wark, R. Jurdak, W. Hu, P. Valencia, and D. Moore. 2010. Environmental wireless sensor networks. Proc. IEEE 98, 11, 1903--1917.Google ScholarCross Ref
- Crossbow. 2012. Data sheet from crossbow. http://www.xbow.com/Products/productdetails.aspx?sid=252.Google Scholar
- J. Fletcher. 1982. An arithmetic checksum for serial transmissions. IEEE Trans. Comm. 30, 1, 247--252.Google ScholarCross Ref
- O. Gnawali, R. Fonseca, K. Jamieson, D. Moss, and P. Levis. 2009. Collection tree protocol. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys'09). ACM Press, New York, 1--14. Google ScholarDigital Library
- S. Guo, Z. Zhong, and T. He. 2009. Find: Faulty node detection for wireless sensor networks. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys'09). ACM Press, New York, 253--266. Google ScholarDigital Library
- T. He, S. Krishnamurthy, L. Luo, T. Yan, L. Gu, R. Stoleru, G. Zhou, Q. Cao, P. Vicaire, J. A. Stankovic, T. F. Abdelzaher, J. Hui, and B. Krogh. 2006. Vigilnet: An integrated sensor network system for energy-efficient surveillance. ACM Trans. Sens. Netw. 2, 1, 1--38. Google ScholarDigital Library
- HPO. 2007. http://www.openview.hp.com.Google Scholar
- IBM Tivoli. 1996. http://www.ibm.com/software/tivoli.Google Scholar
- S. Kandula, D. Katabi, and J.-P. Vasseur. 2005. Shrink: A tool for failure diagnosis in ip networks. In Proceedings of the ACM SIGCOMM Workshop on Mining Network Data (MineNet'05). ACM Press, New York, 173--178. Google ScholarDigital Library
- M. M. H. Khan, H. K. Le, H. Ahmadi, T. F. Abdelzaher, and J. Han. 2008. Dustminer: Troubleshooting interactive complexity bugs in sensor networks. In Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (SenSys'08). ACM Press, New York, 99--112. Google ScholarDigital Library
- M. M. H. Khan, H. K. Le, M. Lemay, P. Moinzadeh, L. Wang, Y. Yang, D. K. Noh, T. Abdelzaher, C. A. Gunter, J. Han, and X. Jin. 2010. Diagnostic powertracing for sensor node failure analysis. In Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN'10). ACM Press, New York, 117--128. Google ScholarDigital Library
- L. Krishnamurthy, R. Adler, P. Buonadonna, J. Chhabra, M. Flanigan, N. Kushalnagar, L. Nachman, and M. Yarvis. 2005. Design and deployment of industrial sensor networks: Experiences from a semiconductor plant and the north sea. In Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems (SenSys'05). ACM Press, New York, 64--75. Google ScholarDigital Library
- K. Langendoen, A. Baggio, and O. Visser. 2006. Murphy loves potatoes: Experiences from a pilot sensor network deployment in precision agriculture. In Proceedings of the 20th International Parallel and Distributed Processing Symposium (IPDPS'06). Google ScholarDigital Library
- P. Levis, N. Lee, M. Welsh, and D. Culler. 2003. Tossim: Accurate and scalable simulation of entire tinyos applications. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys'03). ACM Press, New York, 126--137. Google ScholarDigital Library
- Y. Liu, K. Liu, and M. Li. 2010. Passive diagnosis for wireless sensor networks. IEEE/ACM Trans. Netw. 18, 4, 1132--1144. Google ScholarDigital Library
- MySQL Reference Guide. 2012. MySQL reference manual for 5.5 version. http://dev.mysql.com/doc/refman/5.5/en/.Google Scholar
- Oracle Database. 2012. Oracle database performance tuning guide,11g release 1 (11.1). http://www.oracle.com/pls/db111/portal.portal_db?selected=17&frame.Google Scholar
- D. Puccinelli and M. Haenggi. 2010. Reliable data delivery in large-scale low-power sensor networks. ACM Trans. Sen. Netw. 6, 28:1--28:41. Google ScholarDigital Library
- N. Ramanathan, K. Chang, R. Kapur, L. Girod, E. Kohler, and D. Estrin. 2005. Sympathy for the sensor network debugger. In Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems (SenSys'05). ACM Press, New York, 255--267. Google ScholarDigital Library
- K. Romer and J. Ma. 2009. Pda: Passive distributed assertions for sensor networks. In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN'09). 337--348. Google ScholarDigital Library
- S. Rost and H. Balakrishnan. 2006. Memento: A health monitoring system for wireless sensor networks. http://nms.lcs.mit.edu/papers/memento-secon-2006.pdf.Google Scholar
- M. Steinder and A. Sethi. 2002. Increasing robustness of fault localization through analysis of lost, spurious, and positive symptoms. In Proceedings of the 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM'02). Vol. 1. 322--331.Google Scholar
- R. Szewczyk, A. Mainwaring, J. Polastre, J. Anderson, and D. Culler. 2004. An analysis of a large scale habitat monitoring application. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys'04). ACM Press, New York, 214--226. Google ScholarDigital Library
- TinyOS. 2010. TinyOS documentation. http://docs.tinyos.net/index.php/Main_Page.Google Scholar
- M. Wachs, J. I. Choi, J. W. Lee, K. Srinivasan, Z. Chen, M. Jain, and P. Levis. 2007. Visibility: A new metric for protocol design. In Proceedings of the 5th International Conference on Embedded Networked Sensor Systems (SenSys'07). ACM Press, New York, 73--86. Google ScholarDigital Library
- Y. Zhao, R. Govindan, and D. Estrin. 2002. Residual energy scan for monitoring sensor networks. In Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC'02). Vol. 1. 356--362.Google Scholar
Index Terms
- Failure detection in wireless sensor networks: A sequence-based dynamic approach
Recommendations
Modeling and Analysis of Fault Detection and Fault Tolerance in Wireless Sensor Networks
Technological advancements in communications and embedded systems have led to the proliferation of Wireless Sensor Networks (WSNs) in a wide variety of application domains. These application domains include but are not limited to mission-critical (e.g., ...
Packet-level attestation (PLA): A framework for in-network sensor data reliability
Wireless sensor networks (WSN) show enormous potential for collection and analysis of physical data in real-time. Many papers have proposed methods for improving the network reliability of WSNs. However, real WSN deployments show that sensor data-faults ...
A distributed clustering method for energy-efficient data gathering in sensor networks
Since sensor nodes operate on batteries, energy-efficient mechanisms for gathering sensor data are indispensable in prolonging the lifetime of a sensor network as long as possible. In this paper, we propose a novel clustering method where energy-...
Comments