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This paper is a significant extension of our previous works “Otiy: Locator Tracking Nodes”, published in the proceedings of ACM Conext 2007 and “Design and evaluation of an agenda-based location service”, publlished in the proceedings of ACM Globecom 2008.
To setup efficient wireless mesh networks, it is fundamental to limit the overhead needed to localize a mobile user. A promising approach is to rely on a rendezvous-based location system where the current location of a mobile node is stored at specific nodes called locators. Nevertheless, such a solution has a drawback, which happens when the locator is far from the source–destination shortest path. This results in a triangular location problem and consequently in increased overhead of signaling messages. One solution to prevent this problem would be to place the locator as close as possible to the mobile node. This requires however to predict the mobile node’s location at all times. To obtain such information, we define a mobility prediction model (an agenda) that, for each node, specifies the mesh router that is likely to be the closest to the mobile node at specific time periods. The location service that we propose formalizes the integration of the agenda with the management of location servers in a coherent and self-organized fashion. To evaluate the performance of our system compared to traditional approaches, we use two real-life mobility datasets of Wi-Fi devices in the Dartmouth campus and Taxicabs in the bay area of San Francisco. We show that our strategy significantly outperforms traditional solutions; we obtain gains ranging from 39 to 72% compared to the centralized scheme and more than 35% compared to a traditional rendezvous-based solution.
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Bruno, R., Conti, M., & Gregori, E. (2005). Mesh networks: Commodity multihop ad hoc networks. IEEE Communications Magazine, 43(3), 123–131. CrossRef
Akyildiz, I. F., & Wang, X. (2005). A survey on wireless mesh networks. IEEE Communications Magazine, 43(9), 23–30. CrossRef
Li, J., Blake, C., Couto, D. S. J. D., Lee, H. I., & Morris, R. (2001). Capacity of ad hoc wireless networks. In ACM mobicom (pp. 61–69). Rome, Italy. July 2001.
Bicket, J., Aguayo, D., Biswas, S., & Morris, R. (2005). Architecture and evaluation of an unplanned 802.11b mesh networks. In ACM mobicom (pp. 31–42). Cologne, Germany. August 2005.
Sethom, K., Afifi, H., & Pujolle, G. (2005). A distributed architecture for location management in next generation networks. In IEEE international conference on wireless networks, communications and mobile computing. Maui, HI, USA. June 2005.
Kieb, W., Fubler, H., Widmer, J., & Mauve, M. (2004). Hierarchical location service for mobile ad-hoc networks. Proceedings of ACM Sigmobile, 8(4), 47–58.
Li, J., Jannotti, J., Couto, D. S. J. D., Karger, D. R., & Morris, R. (2000). A scalable location service for geographic ad hoc routing. In ACM mobicom. Boston, MA, USA. August 2000.
Zang, H., & Bolot, J. C. (2007). Mining call and mobility data to improve paging efficiency in cellular networks. In ACM mobicom. Montreal, QC, Canada. September 2007.
Axhausen, K. W., Knig, A., & Schnfelder, S. Mobidrive. Dynamic and routines of travel behaviour. http://www.ivt.ethz.ch/vpl/research/mobidrive.
Schnfelder, S., & Samaga, U. (2003). Where do you want to go today?—re observations on daily mobility. In Swiss transport research conference. Monte Verita, Ascona, Switzerland. March 2003.
Michael, K., McNamee, A., Michael, M., & Tootell, H. (2006). Location-based intelligence? modeling behavior in humans using GPS. In International Symposium on technology and society. New York, NY, USA. June 2006.
Lee, J. K., & Hou, J. C. (2006). Modeling steady-state and transient behaviors of user mobility: Formulation, analysis, and application. In ACM mobihoc. Florence, Italy. May 2006.
Wu, H. K., Jin, M. H., & Horng, J. T. (2001). Personal paging area design based on mobiles moving behaviors. In IEEE infocom. Anchorage, AK, USA. April 2001.
Boc, M., Fladenmuller, A., & de Amorim, M. D. (2007). Otiy: Locators tracking nodes. In ACM CoNEXT. New York, NY. December 2007.
Boc, M., Fladenmuller, A., & de Amorim, M. D. (2008). Design and evaluation of an agenda-based location service. In IEEE Globecom (pp. 1–5). New Orleans, LA, USA. November 2008.
Kotz, D., Henderson, T., & Abyzov, I. (2004). CRAWDAD trace dartmouth/campus/syslog/01 04 (v. 2004-12-18). [Online]. Available: http://crawdad.cs.dartmouth.edu/dartmouth/campus/syslog/0104. December 2004.
Mouly, M., & Pautet, M.-B. (1992). The GSM system for mobile communications. Telecom publishing.
Perkins, C. (2002). IP mobility support for ipv4, RFC3344. August 2002.
Rowstron, A., & Druschel, P. (2001). Pastry: Scalable, decentralized object location and routing for large-scale peer-to-peer systems. In IFIP/ACM middleware. Heidelberg, Germany. November 2001.
Viana, A. C., Amorim, M., Viniotis, Y., Fdida, S., & de Rezende, J. F. (2006). Twins: A dual addressing space representation for self-organizing networks. IEEE Transactions on Parallel and Distributed Systems, 17(12), 1468–1481. CrossRef
Ratnasamy, S., Francis, P., Handley, M., Karp, R., & Shenker, S. (2001). A scalable content-addressable network. In: ACM sigcomm. San Diego, CA, USA. August 2001.
Ho, J. S. M., & Akyildiz, I. F. (1996). Local anchor scheme for reducing signaling costs in personal communications networks. IEEE/ACM Transactions on Networking, 4(5), 709–725. CrossRef
Malyan, A. D., Ng, L., Leung, V., & Donaldson, R. (1993). Network architecture and signaling for wireless personal communications. IEEE Journal on Selected Areas in Communications, 11(6), 830–841. CrossRef
Wang, J. Z. (1993). A fully distributed location registration strategy for universal personal communication systems. IEEE Journal on Selected Areas in Communications, 11(6), 850–860. CrossRef
Boc, M., Fladenmuller, A., & de Amorim, M. D. (2007). Towards self-characterisation of user mobility patterns. In IST mobile and wireless communications summmit poster. Budapest, Hungary. July 2007.
Ashbrook, D., & Starner, T. (2003). Using GPS to learn significant locations and predict movement across multiple users. Journal of Personal and Ubiquitous Computing, 7, 275–286. CrossRef
Kang, J. H., Welbourne, W., Stewart, B., & Borriello, G. (October 2004). Extracting places from traces of locations. In ACM international workshop on wireless mobile applications and services on WLAN hotspots, Philadelphia, PA, USA.
Rahaman, A., Abawajy, J., Hobbs, M. (2007). Taxonomy and survey of location management systems. In IEEE/ACIS international conference on computer and information science. Melbourne, Australia. July 2007.
Tabbane, S. (1995). An alternative strategy for location tracking. IEEE Journal on Selected Areas in Communications, 13(5), 880–892. CrossRef
Wang, K., Liao, J.-M., & Chen, J.-M. (2000). Intelligent location tracking strategy in PCS. IEEE Proceedings Communications, 147(1), 63–68. CrossRef
Chuon, C., Guha, S., & Hossain, A. K. M. M. (June 2005) Individual profile graphs for location management in PCS networks. In IEEE international conference on wireless networks, communications and mobile computing. Maui, HI, USA.
Ma, W., & Fang, Y. (2002). A new location management strategy based on user mobility pattern for wireless networks. In IEEE conference on local computer networks. Tampa, FL, USA. November 2002.
Ghosh, J., Beal, M. J., Ngo, H. Q., & Qiao, C. (2006). On profiling mobility and predicting locations of campus-wide wireless users. In ACM REALMAN. Florence, Italy. May 2006.
Cayirci, E., & Akyildiz, I. F. (2002). User mobility pattern scheme for location update and paging in wireless systems. IEEE Transactions on Mobile Computing, 1, 236–247. CrossRef
Zheng, Q., Hong, X., & Liu, J. (2006). An agenda based mobility model. In IEEE annual simulation symposium. Huntsville, AL, USA. April 2006.
Srinivasan, V., Motani, M., & Ooi, W. T. (2006). Analysis and implications of student contact patterns derived from campus schedules. In ACM mobicom. Los Angeles, CA, USA. September 2006.
- Near-zero triangular location through time-slotted mobility prediction
Marcelo Dias de Amorim
- Springer US
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