IWANN 2009: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living pp 831-838 | Cite as
A Device Search Strategy Based on Connections History for Patient Monitoring
Abstract
Ambient Assisted Living provides support for people’s daily life and aims at improving their quality of life. A health monitoring service could be intended to address the needs of sick people. Patient monitoring by medical personnel is frequently supported by handheld devices receiving health-care information. Location of these mobile devices is necessary in order to communicate any information, and the search strategy to locate them becomes a challenging issue in comparison to networks with permanent connections. We address this problem from an application point of view considering a membership based communication system characterized by users following repetitive patrol patterns day after day. We identify these patterns to generate a history of network connections to decrease the time required to locate any device on the network. We propose a modification of the commonly used Random Walk strategy to setup new connections on ad-hoc networks taking advantage of the learned patrol patterns.
Keywords
Random Walk search strategy patrol patterns communication historyPreview
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References
- 1.Bar-Yossef, Z., Friedman, R., Kliot, G.: RaWMS - Random Walk Based Lightweight Membership Service for Wireless Ad Hoc Networks. ACM Trans. Comput. Syst. 26(2), 1–66 (2008)CrossRefGoogle Scholar
- 2.Chockler, G.V., Keidar, I., Vitenberg, R.: Group communication specifications: a comprehensive study. ACM Comput. Surv. 33(4), 427–469 (2001)CrossRefGoogle Scholar
- 3.Bar-Yossef, Z., Gurevich, M.: Random sampling from a search engine’s index. In: Proceedings of the 15th International Conference on World Wide Web, WWW 2006, pp. 367–376. ACM, New York (2006)Google Scholar
- 4.Dasgupta, A., Das, G., Mannila, H.: A random walk approach to sampling hidden databases. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, SIGMOD 2007, pp. 629–640. ACM, New York (2007)CrossRefGoogle Scholar
- 5.Grundel, D.A.: Searching for a moving target: optimal path planning. In: Proceedings of Networking, Sensing and Control, pp. 867–872. IEEE, Los Alamitos (2005)Google Scholar
- 6.Kurumida, Y., Ogata, T., Ono, H., Sadakane, K., Yamashita, M.: A generic search strategy for large-scale real-world networks. In: Proceedings of the 1st international Conference on Scalable information Systems, InfoScale 2006, vol. 152. ACM, New York (2006)Google Scholar
- 7.Mabrouki, I., Lagrange, X., Froc, G.: Random walk based routing protocol for wireless sensor networks. In: Proceedings of the 2nd international Conference on Performance Evaluation Methodologies and Tools. ACM International Conference Proceeding Series, vol. 321, pp. 1–10. ICST, Brussels (2007)Google Scholar
- 8.Avin, C., Brito, C.: Efficient and robust query processing in dynamic environments using random walk techniques. In: Proceedings of the Third International Symposium on Information Processing in Sensor Networks, pp. 277–286 (2004)Google Scholar
- 9.Alon, N., Avin, C., Koucky, M., Kozma, G., Lotker, Z., Tuttle, M.R.: Many random walks are faster than one. In: Proceedings of the Twentieth Annual Symposium on Parallelism in Algorithms and Architectures, SPAA 2008, pp. 119–128. ACM, New York (2008)CrossRefGoogle Scholar