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  1. Research Profile of My Group Guoliang Xing Department of Computer ScienceCity University of Hong Kong

  2. Facts of My Group • Members • Three PhD students • CityU, CityU-USTC, CityU-WuhanU • One Master student • Two research assistants (joint supervision) • Part of CityU wireless group • 6 faculty members • more than 20 research staff/students • ~3 million HK$ government funding in 2007-08

  3. Research Directions • Controlled mobility • Data fusion based target detection • Power management • Sensing coverage

  4. 2007-08 Conference Publications • Controlled mobility • Rendezvous Design Algorithms for Wireless Sensor Networks with a Mobile Base Station, G. Xing, T. Wang, W. Jia, M. Li, MobiHoc 2008, 44/300=14.6%. • Rendezvous Planning in Mobility-assisted Wireless Sensor Networks,G. Xing, T. Wang, Z. Xie and W. Jia;RTSS 2007, 44/171=25.7%. • Data fusion based target detection • Mobility-assisted Spatiotemporal Detection in Wireless Sensor Networks, G. Xing; J. Wang; K. Shen; Q. Huang; H. So; X. Jia, ICDCS 2008, 102/638=16%. • Collaborative Target Detection in Wireless Sensor Networks with Reactive Mobility, R. Tan, G. Xing, J. Wang and H. So, IWQoS 2008 • Power management • Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks. K. Klues, G. Xing and C. Lu,IPSN 200738/170=22.3%. • Dynamic Multi-resolution Data Dissemination in Storage-centric Wireless Sensor Networks. H. Luo, G. Xing, M. Li, and X. Jia, MSWiM 2007, 41/161=24.8%.

  5. Earlier Work on Sensor Networks ACM/IEEE Transactions Papers • Minimum Power Configuration for Wireless Communication in Sensor Networks, G. Xing C. Lu, Y. Zhang, Q. Huang, R. Pless, ACM Transactions on Sensor Networks, Vol 3(2), 2007, extended MobiHoc 2005 paper • Impact of Sensing Coverage on Greedy Geographic Routing Algorithms, G. Xing; C. Lu; R. Pless; Q. Huang. IEEE Transactions on Parallel and Distributed Systems (TPDS),17(4), 2006, extended MobiHoc 2004 paper • Integrated Coverage and Connectivity Configuration for Energy Conservation in Sensor Networks, G. Xing; X. Wang; Y. Zhang; C. Lu; R. Pless; C. D. Gill, ACM Transactions on Sensor Networks, Vol. 1 (1), 2005, extended SenSys 2003 paper, one of the most widely cited work on the coverage problem of sensor networks, total number of citations is 358 in Google Scholar.

  6. Focus of this Talk • Controlled mobility • Rendezvous Planning in Mobility-assisted Wireless Sensor Networks,G. Xing, T. Wang, Z. Xie and W. Jia;RTSS 2007, 44/171=25.7%. • Power management • Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks. K. Klues, G. Xing and C. Lu,IPSN 200738/170=22.3%. • Sensing Coverage • Integrated Coverage and Connectivity Configuration for Energy Conservation in Sensor Networks, G. Xing; X. Wang; Y. Zhang; C. Lu; R. Pless; C. D. Gill, ACM Transactions on Sensor Networks, Vol. 1 (1), 2005, extended SenSys 2003 paper

  7. Motivations • Sensor nets face the fundamental performance bottleneck • Many applications are data-intensive • Multi-hop wireless relays are power-consuming • A tension exists between the sheer amount of data generated and limited power supply • Controlled mobility is a promising solution • Number of related papers increases significantly in last 3 years: MobiSys, MobiHoc, MobiCom, IPSN

  8. Mobile Sensor Platforms • Low movement speed (0.1~2 m/s) • Increased latency of data collection • Reduced network capacity XYZ @ Yale http://www.eng.yale.edu/enalab/XYZ/ Robomote @ USC [Dantu05robomote] Networked Infomechanical Systems (NIMS) @ CENS, UCLA

  9. Basic idea • Some nodes serve as “rendezvous points” (RPs) • Other nodes send their data to the closest RP • Mobiles visit RPs and transport data to base station • Advantages • In-network caching + controlled mobility • Mobiles can collect a large volume of data at a time • Minimize disruptions due to mobility • Mobiles contact static nodes at RPs at scheduled time

  10. An Example mobile node The field is 500 × 500 m2 The mobile moves at 0.5 m/s It takes ~20 minutes to visit six randomly distributed RPs It takes > 4 hours to visit 200 randomly distributed nodes. rendezvous point source node

  11. The Rendezvous Planning Problem • Formulated as graph problem • An optimal algorithm for limited-mobility without data aggregation • Two approx. algorithms with aggregation

  12. Focus of this Talk • Controlled mobility • Rendezvous Planning in Mobility-assisted Wireless Sensor Networks,G. Xing, T. Wang, Z. Xie and W. Jia;RTSS 2007, 44/171=25.7%. • Power management • Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks. K. Klues, G. Xing and C. Lu,IPSN 200738/170=22.3%. • Sensing Coverage • Integrated Coverage and Connectivity Configuration for Energy Conservation in Sensor Networks, G. Xing; X. Wang; Y. Zhang; C. Lu; R. Pless; C. D. Gill, ACM Transactions on Sensor Networks, Vol. 1 (1), 2005, extended SenSys 2003 paper

  13. Power Management Interfaces Backoff Control Interfaces Send/Receive Interfaces Radio Component Send/Receive Buffers MAC Radio State Machine Radio Power Management Clear Channel Assessment Backoff Controller Traditional Core Radio Functionality Incoming and Outgoing data buffers State machine Integrated Radio Power Management CCA Functionality Real Implementations do not separate these functional components so nicely

  14. Implementation • Implemented UPMA in TinyOS 2.0 for both Mica2 and Telosb motes • Developed interfaces with different types of MAC • CSMA based: S-MAC [Ye et al. 04], B-MAC [Polastre et al. 04] • TDMA based: TRAMA [Rajendran et al. 05] • Hybrid: 802.15.4, Z-MAC [Rhee et al. 05] • Separated sleep scheduling modules from B-MAC • Implemented two new sleep schedulers on top of B-MAC

  15. Focus of this Talk • Controlled mobility • Rendezvous Planning in Mobility-assisted Wireless Sensor Networks,G. Xing, T. Wang, Z. Xie and W. Jia;RTSS 2007, 44/171=25.7%. • Power management • Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks. K. Klues, G. Xing and C. Lu,IPSN 200738/170=22.3%. • Sensing Coverage • Integrated Coverage and Connectivity Configuration for Energy Conservation in Sensor Networks, G. Xing; X. Wang; Y. Zhang; C. Lu; R. Pless; C. D. Gill, ACM Transactions on Sensor Networks, Vol. 1 (1), 2005, extended SenSys 2003 paper

  16. An Integrated Model • Assume a number of active nodes can achieve: • K-coverage: every point is monitored by at least K active sensors • N-connectivity: network is still connected if N-1 active nodes fail • Bounded routing paths: hop count between any two nodes can be predicted • Focus on fundamental relations between the constraints Active nodes Sensing range Sleeping node Communicating nodes A network with 1-coverage and 1-connectivity

  17. Connectivity vs. Coverage: Analytical Results • Network connectivity does not guarantee coverage • Connectivity only concerns with node locations • Coverage concerns with all locations in a region • If Rc/Rs 2 • K-coverage  K-connectivity • Implication: given requirements of K-coverage and N-connectivity, only needs to satisfy max(K, N)-coverage • Solution: Coverage Configuration Protocol (CCP) • If Rc/Rs< 2 • CCP + SPAN [chen et al. 01]

  18. Student Profiles • Self-motivated • Ambitious and persistent • Theory background • Graph theory, optimization, probabilistic theory, computational geometry • Hands-on experiences • C/C++ programming, embedded systems, OS, network programming

  19. Problem Formulation • Given a tree T(V,E) rooted at B and sources {si}, find RPs, {Ri}, and a tour no longer than L=vD thatvisits {B}U{Ri}, and • The problem is NP-hard (reduction from the Traveling Salesman Problem) dT(si,Ri)– the on-tree distance between si and Ri

  20. Rendezvous Planning under Limited Mobility • The mobile only moves along routing tree • Simplifies motion control and improves reliability XYZ @ Yale

  21. An Optimal Algorithm • Sort edges in the descending order of the number of sources in descendents • Choose a subset of (partial) edges from the sorted list whose length is L/2 • The mobile tour is the pre-order traversal of the chosen edges

  22. Thanks!

  23. Unified Power Management Architecture interfaces of sleep schedulers Protocol 1 Protocol 2 Protocol 0 Protocol 3 … SyncSleep AsyncSleep Other Interface … parameters specified by upper-level protocols OnTime Mode Param 0 OffTime Preamble Param 1 DutyCycling Table LPL Table Other Table Power Management Abstraction • Consistency check • Aggregation Power Manager sleep scheduling protocols … Others Sync Scheduler Async Listening MAC ChannelMonitor PreambleLength On/Off interfaces with MAC PHY