Abstract
Updating software over the network is important for Wireless Sensor Networks in support of scale, remote deployment, feature upgrades, and fixes. The risk of a fault in the updated code causing system failure is a serious problem. In this paper, we identify a single, critical, symptom loss-of-control, that complements exception-based schemes, and supports failsafe recovery from faults in software updates. We present a new software update recovery mechanism that uses loss-of-control to provide high-reliability, low energy, software updates, including a comparison of optimised-flooding against spanning-tree for determining loss-of-control in a multi-path environment. The solution presented supports a trial phase (with lower latency), and an operational phase (with lower energy). The energy/latency tradeoff of this is shown, and the high-reliability of this update recovery is demonstrated by analysis and simulation. The results presented control the risk in existing WSN software update mechanisms.
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References
Han, C.-C., Kumar, R., Shea, R., Srivastavam, M.: Sensor network software update management: a survey. Intl. Journal of Network Management 15, 283–294 (2005)
Wang, Q., Zhu, Y., Cheng, L.: Reprogramming wireless sensor networks: challenges and approaches. IEEE Network 20(3), 48–55 (2006)
Brown, S., Sreenan, C.: A new model for updating software in wireless sensor networks. IEEE Network 20(6), 42–47 (2006)
Padhy, P., Martinez, K., Riddoch, A., Ong, H.L.R., Hart, J.K.: Glacial environment monitoring using sensor networks. In: Proc. RealWSN 2005, pp. 10–14 (2005)
Kothari, N., Nagaraja, K., Raghunathan, V., Sultan, F., Chakradhar, S.: Hermes: A software architecture for visibility and control in wireless sensor network deployments. In: Proc. IPSN 2008, pp. 395–406 (2008)
Liu, T., Sadler, C., Zhang, M., Martonosi, P.: Implementing software on resource-constrained mobile sensors: Experiences with impala and zebranet. In: Proc. MobiSys 2004, pp. 256–269. ACM, New York (2004)
Xiao, Z., Sarikaya, B.: Code dissemination in sensor networks with mdeluge. In: Proc. SECON 2006 (2), pp. 661–666. IEEE, Los Alamitos (2006)
Evers, L., Havinga, P., Kuper, J.: Flexible sensor network reprogramming for logistics. In: Proc. MASS 2007, pp. 1–4. IEEE, Los Alamitos (2007)
Tolle, G., Culler, D.: Design of an application-cooperative management system for wireless sensor networks. In: Proc. EWSN 2005, pp. 121–132. IEEE, Los Alamitos (2005)
Dutta, P., Hui, J., Jeong, J., Kim, S., Sharp, C., Taneja, J., Tolle, G., Whitehouse, K., Culler, D.: Trio: enabling sustainable and scalable outdoor wireless sensor network deployments. In: Proc. IPSN 2006, pp. 407–415. IEEE, Los Alamitos (2006)
Williams, B., Camp, T.: Comparison of broadcasting techniques for mobile ad hoc networks. In: MobiHoc 2002, pp. 194–205. ACM, New York (2002)
Liang, C.-K., Huang, Y.-J., Lin, J.-D.: An energy efficient routing scheme in wireless sensor networks. In: Proc. AINAW 2008, pp. 916–921 (2008)
Rahnavard, N., Vellambi, B., Fekri, F.: Distributed protocols for finding low-cost broadcast and multicast trees in wireless networks. In: Proc. SECON 2008, pp. 551–559. IEEE, Los Alamitos (2008)
Wieselthier, J., Nguyen, G., Ephremides, A.: On the construction of energy-efficient broadcast and multicast trees in wireless networks. In: Proc. INFOCOM 2000 (2), pp. 585–594. IEEE, Los Alamitos (2000)
Levis, P., Lee, N., Welsh, M., Culler, D.: Tossim: accurate and scalable simulation of entire tinyos applications. In: Proc. SenSys 2003, pp. 126–137. ACM, New York (2003)
Zuniga, M., Krishnamachari, B.: Analyzing the transitional region in low power wireless links. In: Proc. SECON 2004, pp. 517–526. IEEE, Los Alamitos (2004)
Dang, T., Bulusu, N., Feng, W., Park, S.: DHV: A Code Consistency Maintenance Protocol for Multi-hop Wireless Sensor Networks. In: Proc. EWSN 2009, pp. 327–342. Springer, Heidelberg (2009)
Tan, H.O., Korpeoglu, I.: Power Efficient Data Gathering and Aggregation in Wireless Sensor Networks. SIGMOD Record 32(4), 66–71 (2003)
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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Brown, S., Sreenan, C.J. (2010). Software Update Recovery for Wireless Sensor Networks. In: Komninos, N. (eds) Sensor Applications, Experimentation, and Logistics. Sensappeal 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11870-8_8
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DOI: https://doi.org/10.1007/978-3-642-11870-8_8
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