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Issue No.05 - May (2009 vol.20)
pp: 740-752
Hongzi Zhu , Shanghai Jiao Tong University, Shanghai
Minglu Li , Shanghai Jiao Tong University, Shanghai
Yanmin Zhu , Imperial College London, London
Lionel M. Ni , Hong Kong University of Science and Technology, Hong Kong
Intelligent transportation systems have become increasingly important for the public transportation in Shanghai. In response, ShanghaiGrid (SG) project aims to provide abundant intelligent transportation services to improve the traffic condition. A challenging service in SG is to accurately locate the positions of moving vehicles in real time. In this paper, we present an innovative scheme, Hierarchical Exponential Region Organization (HERO), to tackle this problem. In SG, the location information of individual vehicles is actively logged in local nodes which are distributed throughout the city. For each vehicle, HERO dynamically maintains an advantageous hierarchy on the overlay network of local nodes to conservatively update the location information only in nearby nodes. By bounding the maximum number of hops the query is routed, HERO guarantees to meet the real-time constraint associated with each vehicle. A small-scale prototype system implementation and extensive simulations based on the real road network and trace data of vehicle movements from Shanghai demonstrate the efficacy of HERO.
Distributed applications, real-time system, RFID system, peer-to-peer network, vehicle tracking.
Hongzi Zhu, Minglu Li, Yanmin Zhu, Lionel M. Ni, "HERO: Online Real-Time Vehicle Tracking", IEEE Transactions on Parallel & Distributed Systems, vol.20, no. 5, pp. 740-752, May 2009, doi:10.1109/TPDS.2008.147
[1] European Commission, The Karen European ITS Framework Architecture, http:/, 2004.
[2] The Nat'l ITS Architecture Version 5.1. Dept. Transportation of the US, , 2005.
[3] Ministry of Internal Affairs and Communication National Police Agency, and Ministry of Land, Infrastructure, and Transport of Japan, Vehicle Information and Comm. System,, 2006.
[4] Shanghai City Comprehensive Transportation Planning Inst.,, 2007.
[5] LoJack Corporation, Stolen Vehicle Recovery System, , 2007.
[6] iPico Corporation, Test Report: Single-Lane Vehicle Identification with UHF RFID, , 2007.
[7] “Transportation Recall Enhancement, Accountability, and Documentation (TREAD) Act,” The 106th United States Congress, , 2000.
[8] Cisco Systems Inc., Cisco Aironet 1240 Series 802.11a/B/G Access Point Data Sheet, us/guest/products/ps6521/c1650cdccont_0900aecd8031c844.pdf , 2007.
[9] Shanghai Telecom, http:/, 2007.
[10] Shanghai Super Electronic Technology, http://www.superrfid. netenglish/, 2007.
[11] The Network Simulator,, 2007.
[12] The Gnutella Protocol Specification V0.6, http:/rfc-gnutella., 2005.
[13] H. Zhu, Y. Zhu, M. Li, and L.M. Li, “ANTS: Efficient Vehicle Locating Based on Ant Search in Shanghai Transportation Grid,” Proc. Int'l Conf. Parallel Processing (ICCP), 2007.
[14] H. Zhu, Y. Zhu, M. Li, and L.M. Li, “HERO: Online Real-time Vehicle Tracking in Shanghai,” Proc. IEEE INFOCOM, 2008.
[15] A. Bakker, E. Amade, G. Ballintijn, I. Kuz, P. Verkaik, I. van der Wijk, M. van Steen, and A.S. Tanenbaum, “The Globe Distribution Network,” Proc. USENIX Ann. Conf., 2000.
[16] A. Civilis, C.S. Jensen, and S. Pakalnis, “Techniques for Efficient Road-Network-Based Tracking of Moving Objects,” IEEE Trans. Knowledge and Data Eng., vol. 17, pp. 698-712, 2005.
[17] D. Pfoser, C.S. Jensen, and Y. Theodoridis, “Novel Approaches to the Indexing of Moving Object Trajectories,” Proc. 26th Int'l Conf. Very Large Data Bases (VLDB), 2000.
[18] G. Kollios, D. Gunopulos, V. Tsotras, A. Delis, and M. Hadjieleftheriou, “Indexing Animated Objects Using Spatiotemporal Access Methods,” IEEE Trans. Knowledge and Data Eng., vol. 13, pp. 758-777, 2001.
[19] D. Lin, C.S. Jensen, B.C. Ooi, and S. Saltenis, “Efficient Indexing of the Historical, Present, and Future Positions of Moving Objects,” Proc. Sixth Int'l Conf. Mobile Data Management (MDM), 2005.
[20] M. Pelanis, S. Saltenis, and C.S. Jensen, “Indexing the Past, Present, and Anticipated Future Positions of Moving Objects,” ACM Trans. Database Systems, vol. 31, pp. 255-298, 2006.
[21] J.F. Roddick, M.J. Egenhofer, E. Hoel, and D. Papadias, “Spatial, Temporal and Spatio-Temporal Databases—Hot Issues and Directions for PhD Research,” Proc. ACM SIGMOD, 2004.
[22] B.Y. Zhao, J. Kubiatowicz, and A.D. Joseph, “Tapestry: An Infrastructure for Fault-Tolerant Wide-Area Location and Routing,” Technical Report UCB/CSD-01-1141, Univ. of California at Berkeley, 2001.
[23] I. Stoica, R. Morris, D. Karger, M.F. Kaashoek, and H. Balakrishnan, “Chord: A Scalable Peer-to-Peer Lookup Service for Internet Applications,” Proc. ACM SIGCOMM, 2001.
[24] A. Rowstron and P. Druschel, “Pastry: Scalable, Decentralized Object Location and Routing for Large-Scale Peer-to-Peer Systems,” Proc. 18th IFIP/ACM Int'l Conf. Distributed Systems Platforms (Middleware), 2001.
[25] S. Ratnasamy, P. Francis, M. Handley, R. Karp, and S. Shenker, “A Scalable Content-Addressable Network,” Proc. ACM SIGCOMM, 2001.
[26] Q. Lv, P. Cao, E. Cohen, K. Li, and S. Shenker, “Search and Replication in Unstructured Peer-to-Peer Networks,” Proc. 16th ACM Int'l Conf. on Supercomputing (ICS), 2002.
[27] C. Gkantsidis, M. Mihail, and A. Saberi, “Random Walks in Peer-to-Peer Networks,” Proc. IEEE INFOCOM, 2004.
[28] S. Boyd, A. Ghosh, B. Prabhakar, and D. Shah, “Gossip Algorithms: Design, Analysis, and Applications,” Proc. IEEE INFOCOM, 2005.
[29] D. Kempe, A. Dobra, and J. Gehrke, “Gossip-Based Computation of Aggregation Information,” Proc. 44th Ann. IEEE Symp. Foundations of Computer Science (FOCS '03), pp. 482-491, 2003.
[30] S. Jiang, L. Guo, and X. Zhang, “LightFlood: An Efficient Flooding Scheme for File Search in Unstructured Peer-to-Peer Systems,” Proc. Int'l Conf. Parallel Processing (ICCP), 2003.
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