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Issue No.10 - Oct. (2012 vol.11)
pp: 1555-1568
Tao Zhang , Nanjing University, Nanjing
Dan Wang , The Hong Kong Polytechnic University, Hong Kong
Jiannong Cao , The Hong Kong Polytechnic University, Hong Kong
Yi Qing Ni , The Hong Kong Polytechnic University, Hong Kong
Li-Jun Chen , Nanjing University, Nanjing
Daoxu Chen , Nanjing University, Nanjing
Sensor networks nowadays are widely used for structural health monitoring; for example, the sensor monitoring system deployed on the Guangzhou New TV Tower, China. While wired systems still dominate, it is commonly believed that wireless sensors will play a key role in the near future. One key difficulty for such systems is the data transmission from the sensor nodes to the base station. Given the long span of the civil structures, neither a strategy of long-range one-hop data transmission nor short-range hop-by-hop communication is cost-efficient. In this paper, we propose a novel scheme of using the elevators to assist data collection. A base station is attached to an elevator. A representative node on each floor collects and transmits the data to the base station using short range communication when the elevator stops at or passes by this floor. As such, communication distance can be minimized. To validate the feasibility of the idea, we first conduct an experiment in an elevator of the Guangzhou New TV Tower. We observe steady transmission when elevator is in movement. To maximize the gain, we formulate the problem as an optimization problem where the data traffic should be transmitted on time and the lifetime of the sensors should be maximized. We show that if we know the movement pattern of the elevator in advance, this problem can be solved optimally. We then study the online version of the problem and show that no online algorithm has a constant competitive ratio against the offline algorithm. We show that knowledge of the future elevator movement will intrinsically improve the data collection performance. We discuss how the information could be collected and develop online algorithms based on different level of knowledge of the elevator movement patterns. Theoretically, given that the links capacity assumptions we made, we can prove that our online algorithm can guarantee data delivery on time. In practice, we may set a buffer zone to minimize the possible data delivery violation. A comprehensive set of simulations and MicaZ testbed experiments have demonstrated that our algorithm substantially outperforms conventional multihop routing and naive waiting for elevator scheme. The performance of our online algorithm is close to the optimal offline solution.
Elevators, Throughput, Base stations, Mobile communication, Monitoring, Prediction algorithms, Routing, mobile sink., Wireless sensor networks, data collection
Tao Zhang, Dan Wang, Jiannong Cao, Yi Qing Ni, Li-Jun Chen, Daoxu Chen, "Elevator-Assisted Sensor Data Collection for Structural Health Monitoring", IEEE Transactions on Mobile Computing, vol.11, no. 10, pp. 1555-1568, Oct. 2012, doi:10.1109/TMC.2011.191
[1] J.M. Ko, Y.Q. Ni, H.F. Zhou, J.Y. Wang, and X.T. Zhou, "Investigation Concerning Structural Health Monitoring of An Instrumented Cable-Stayed Bridge," Structure and Infrastructure Eng., vol. 5, no. 6, pp. 497-513, 2009.
[2] Y.Q. Ni, Y. Xia, W.Y. Liao, and J.M. Ko, "Technology Innovation in Developing the Structural Health Monitoring System for Guangzhou New TV Tower," Structural Control and Health Monitoring, vol. 16, no. 1, pp. 73-98, 2009.
[3] F. Wang, D. Wang, and J. Liu, "Poster: Exploiting Elevator for Wireless Sensor Data Collection in High-Rise Structural Monitoring," Proc. ACM MobiCom, 2010.
[4] M. Buettner, G. Yee, E. Anderson, and H. Han, "X-MAC: A Short Preamble MAC Protocol for Duty-Cycled Wireless Sensor Networks," Proc. Fourth Int'l Conf. Embedded Networked Sensor Systems (SenSys '06), pp. 307-320, Nov. 2006.
[5] R. Ahuja, T. Magnanti, and J. Orlin, Network Flows: Theory, Aplgorithms, and Applications. Prentice Hall, 1993.
[6] MICAZ Motes, http:/, 2012.
[7] A. Rao and G. Anandakumar, "Optimal Sensor Placement Techniques for System Identification and Health Monitoring of Civil Structures," Smart Structures and Systems, vol. 4, no. 4, pp. 465-492, 2008.
[8] Z. Shi, S. Law, and L. Zhang, "Optimum Sensor Placement for Structural Damage Detection," J. Eng. Mechanics, vol. 126, pp. 1173-1179, 2000.
[9] S. Kim, S. Pakzad, D. Culler, J. Demmel, G. Fenves, S. Glaser, and M. Turon, "Health Monitoring of Civil Infrastructures Using Wireless Sensor Networks," Proc. Sixth Int'l Conf. Information Processing in Sensor Networks (IPSN '07), Apr. 2007.
[10] N. Xu, S. Rangwala, K. Chintalapudi, D. Ganesan, A. Broad, R. Govindan, and D. Estrin, "A Wireless Sensor Network for Structural Monitoring," Proc. Second Int'l Conf. Embedded Networked Sensor Systems (SenSys '04), Nov. 2004.
[11] K. Chebrolu, B. Raman, N. Mishra, P.K. Valiveti, and R. Kumar, "BriMon: A Sensor Network System for Railway Bridge Monitoring," Proc. ACM MobiSys, June 2008.
[12] B. Li, D. Wang, F. Wang, and Y.Q. Ni, "High Quality Sensor Placement for Structural Health Monitoring: Refocusing on Application Demands," Proc. IEEE INFOCOM, Mar. 2010.
[13] J. Luo and J.-P. Hubaux, "Joint Mobility and Routing for Lifetime Elongation in Wireless Sensor Networks," Proc. IEEE INFOCOM, Mar. 2005.
[14] J. Luo, J. Panchard, M. Pirkowski, M. Grossglauser, and J.-P. Hubaux, "MobiRoute: Routing Towards A Mobile Sink for Improving Lifetime in Sensor Networks," Proc. IEEE/ACM Distributed Computing in Sensor Systems (DCOSS), pp. 480-497, 2006.
[15] A. Chakrabarti, A. Sabharwal, and B. Aazhang, "Using Predictable Observer Mobility for Power Efficient Design of Sensor Networks," Proc. Second Int'l Conf. Information Processing in Sensor Networks (IPSN '03), pp. 129-145, 2003.
[16] G. Xing, T. Wang, W. Jia, and M. Li, "Rendezvous Design Algorithms for Wireless Sensor Networks with A Mobile Base Station," Proc. ACM MobiHoc, pp. 231-240, 2008.
[17] Y. Shi and T. Hou, "Theoretical Results on Base Station Movement Problem for Sensor Networks," Proc. IEEE INFOCOM, 2008.
[18] H.S. Kim, T.F. Abdelzaher, and W.H. Kwon, "Minimum-Energy Asynchronous Dissemination to Mobile Sinks in Wireless Sensor Networks," Proc. First Int'l Conf. Embedded Networked Sensor Systems (SenSys '03), pp. 193-204, 2003.
[19] F. Ye, H. Luo, J. Cheng, S. Lu, and L. Zhang, "A Two-Tier Data Dissemination Model for Large-Scale Wireless Sensor Networks," Proc. ACM MobiCom, June 2009.
[20] R. Shah, S. Roy, S. Jain, and W. Brunette, "Data Mules: Modeling a Three-Tier Architecture for Sparse Sensor Networks," Proc. IEEE Int'l Workshop Sensor Network Protocols and Applications, May 2003.
[21] R. Wohlers, N. Trigoni, R. Zhang, and S. Ellwood, "TwinRoute: Energy-Efficient Data Collection in Fixed Sensor Networks with Mobile Sinks," Proc. 10th Int'l Conf. Mobile Data Management: Systems, Services and Middleware (MDM '09), pp. 192-201, 2009.
[22] D. Johnson and D. Maltz, "Dynamic Source Routing in Ad Hoc Wireless Networks," Mobile Computing, Kluwer Academic, 1996.
[23] C. Perkins and E. Royer, "Ad Hoc On-Demand Distance Vector Routing," Proc. IEEE Workshop Mobile Computing Systems and Applications (WMCSA '09), Feb. 1999.
[24] K. Fall, "A Delay-Tolerant Network Architecture for Chanllenged Internets," Proc. SIGCOMM, Aug. 2003.
[25] S. Jain, K. Fall, and R. Patra, "Routing in a Delay Tolerant Network," Proc. SIGCOMM, Aug. 2004.
[26] W. Zhao, M. Ammar, and E. Zegura, "Controlling the Mobility of Multiple Data Transport Ferries in a Delay-Tolerant Network," Proc. IEEE INFOCOM, 2005.
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