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Issue No.12 - December (2010 vol.9)
pp: 1794-1808
Pei Zhang , Carnegie Mellon University Silivon Valley, Moffett Field
Margaret Martonosi , Princeton University, Princeton
With the proliferation of mobile devices, an increasing number of sensing applications are using mobile sensor networks. These mobile networks are severely energy-constrained, and energy usage is one of the most common causes of failure in their deployments. In these networks, nodes that exhaust their energy before the targeted system lifetime degrade system performance; nodes that run past the system lifetime cannot fully utilize their stored energy. Although much work has focused on policies to reduce and regulate energy usage in fixed and dense networks, intermittently connected networks have been largely overlooked. Due to variations in hardware, software, node mobility, and environment, it is especially difficult for intermittently connected mobile networks to improve operations collectively in a dynamic environment. Here, we present and evaluate Collaborative Adaptive Targeted System Lifetime (CA-TSL), an adaptive policy that enforces a system-wide targeted lifetime in an intermittently connected system by adapting node energy usage to an estimated desired energy profile. For evaluation, we present both real-system and large-scale simulated results. Our approach improves sink data reception by an average of 50 percent, and an additional 30 percent when a density estimation technique is also employed. In addition, it reduces system lifetime variations by up to 5.5{\times}.
Mobile sensor networks, energy budgeting, intermittently connected networks, recharged networks, parameter estimation.
Pei Zhang, Margaret Martonosi, "CA-TSL: Energy Adaptation for Targeted System Lifetime in Sparse Mobile Ad Hoc Networks", IEEE Transactions on Mobile Computing, vol.9, no. 12, pp. 1794-1808, December 2010, doi:10.1109/TMC.2010.138
[1] K. Akkaya and M. Younis, “A Survey on Routing Protocols for Wireless Sensor Networks,” J. Ad Hoc Networks, vol. 3, pp. 325-349, May 2005.
[2] R. Braynard, A. Silberstein, and C. Ellis, “Extending Network Lifetime Using an Automatically Tuned Energy-Aware MAC Protocol,” technical report, Eidgenössische Technische Hochschule (ETH) Zurich, Feb. 2006.
[3] L. Buttyan and J.P. Hubaux, “Nuglets: A Virtual Currency to Stimulate Cooperation in Self-Organized Mobile Ad Hoc Networks,” Technical Report DSC/2001/001, Swiss Fed. Inst. of Tech nology, 2001.
[4] M. Cardei and D.Z. Du, “Improving Wireless Sensor Network Lifetime through Power Aware Organization,” J. Wireless Networks, pp. 333-340, May 2005.
[5] J.-H. Chang and L. Tassiulas, “Energy Conserving Routing in Wireless Ad-hoc Networks,” Proc. IEEE INFOCOM, vol. 1, pp. 22-31, May 2000.
[6] P. Dutta, J. Hui, J. Jeong, S. Kim, C. Sharp, J. Taneja, G. Tolle, K. Whitehouse, and D. Culler, “Trio: Enabling Sustainable and Scalable Outdoor Wireless Sensor Network Deployments,” Proc. Fifth Int'l Conf. Information Processing in Sensor Networks (IPSN '06) Special track on Platform Tools and Design Methods for Network Embedded Sensors (SPOTS '06), pp. 407-415, Apr. 2006.
[7] J. Flinn and M. Satyanarayanan, “Energy-Aware Adaptation for Mobile Applications,” Proc. Symp. Operating Systems Principles, pp.48-63, Dec. 1999.
[8] J. Flinn and M. Satyanarayanan, “Rate Allocation in Wireless Sensor Networks with Network Lifetime Requirement,” Proc. Fifth ACM Int'l Symp. Mobile Ad Hoc Networking and Computing, pp. 67-77, 2004.
[9] T. He, P. Vicaire, T. Yan, Q. Cao, G. Zhou, L. Gu, L. Luo, R. Stoleru, J.A. Stankovic, and T. Abdelzaher, “Achieving Long-Term Surveillance in VigilNet,” Proc. IEEE INFOCOM, vol. 5, Apr. 2006.
[10] B. Hohlt, L. Doherty, and E. Brewer, “Flexible Power Scheduling for Sensor Networks,” Proc. Int'l Symp. Information Processing in Sensor Networks (IPSN), pp. 205-214, Apr. 2004.
[11] B. Hong and V. Prasanna, “Optimizing System Life Time for Data Gathering in Networked Sensor Systems,” Proc. IEEE Workshop Algorithms for Wireless and Ad-Hoc Networks (A-SWAN), July 2004.
[12] C. Intanagonwiwat, R. Govindan, and D. Estrin, “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” Proc. ACM MobiCom, pp. 56-67, Aug. 2000.
[13] K. Kalpakis, K. Dasgupta, and P. Namjoshi, “Maximum Lifetime Data Gathering and Aggregation in Wireless Sensor Networks,” Proc. IEEE Int'l Conf. Networking (ICN '02), pp. 685-696, Aug. 2002.
[14] A. Kansal and M. Srivastava, “An Environmental Energy Harvesting Framework for Sensor Networks,” Proc. Int'l Symp. Low Power Electronics and Design, pp. 481-486, Aug. 2003.
[15] K. Langendoen, A. Baggio, and O. Visser, “Murphy Loves Potatoes: Experiences from a Pilot Sensor Network Deployment in Precision Agriculture,” Proc. 14th Int. Workshop Parallel and Distributed Real-Time Systems (WPDRTS), Apr. 2006.
[16] S. Madden, M.J. Franklin, J. Hellerstein, and W. Hong, “TAG: A Tiny Aggregation Service for Ad-Hoc Sensor Networks,” Proc. Fift Symp. Operating System Design and Implementation (OSDI), pp. 131-146, Dec. 2002.
[17] Maxstream, Inc., XTend OEM RF Module: Product Manual v1.2.4, http:/, Oct. 2005.
[18] V.P. Mhatre, C. Rosenberg, D. Kofman, R. Mazumdar, and N. Shroff, “A Minimum Cost Heterogeneous Sensor Network with a Lifetime Constraint,” IEEE Trans. Mobile Computing, vol. 4, no. 1, pp. 4-15, Jan./Feb. 2005.
[19] P. Michiardi and R. Molva, “CORE: A COllaborative REputation Mechanism to Enforce Node Cooperation in Mobile Ad Hoc Networks,” Proc. IFIP TC6/TC11 Sixth Joint Working Conf. Comm. and Multimedia Security, pp. 107-121, Sept. 2002.
[20] S. Soro and W. Heinzelman, “Prolonging the Lifetime of Wireless Sensor Networks via Unequal Clustering,” Proc. 19th IEEE Int'l Parallel and Distributed Processing Symp. (IPDPS '05), Apr. 2005.
[21] R. Szewczyk, J. Polastre, A. Mainwaring, J. Anderson, and D. Culler, “An Analysis of a Large Scale Habitat Monitoring Application,” Proc. Second ACM Conf. Embedded Networked Sensor Systems (SenSys), pp. 214-226, Nov. 2004.
[22] Texas Instrument, “SBS 1.1-Compliant Gas Gauge Enabled with Impedance Track(TM) Technology for Use with the bq29312,” http:/, Oct. 2005.
[23] Texas Instrument, “Single-Cell Li-Ion and Li-Pol Battery Gas Gauge IC For Portable Applications Data Sheet,” http:/www.ti. com, Oct. 2005.
[24] G. Tolle, J. Polastre, R. Szewczyk, N. Turner, K. Tu, P. Buonadonna, S. Burgess, D. Gay, W. Hong, T. Dawson, and D. Culler, “A Macroscope in the Redwoods,” Proc. Third ACM Conf. Embedded Networked Sensor Systems (SenSys), pp. 51-63, Nov. 2005.
[25] I. Vasclescu, K. Kotay, D. Rus, P. Corke, and M. Duabablu, “Data Collection, Storage and Retrieval with an Underwater Optical and Acoustical Sensor Networks,” Proc. Third ACM Conf. Embedded Networked Sensor Systems (SenSys), pp. 154-165, Nov. 2005.
[26] Y. Wang, P. Zhang, T. Liu, C. Sadler, and M. Martonosi, “Movement Data Traces from Princeton ZebraNet Deployments,” CRAWDAD Database, http:/, Oct. 2007.
[27] G. Werner-Allen, K. Lorincz, J. Johnson, J. Lees, and M. Welsh, “Fidelity and Yield in a Volcano Monitoring Sensor Network,” Proc. Seventh USENIX Symp. Operating Systems Design and Implementation (OSDI '06), pp. 381-396, Nov. 2006.
[28] O. Younis and S. Fahmy, “Distributed Clustering in Ad-Hoc Sensor Networks: A Hybrid, Energy-Efficient Approach,” Proc. IEEE INFOCOM, pp. 629-640, Mar. 2004.
[29] Y. Yu, R. Govindan, and D. Estrin, “Geographical and Energy Aware Routing: A Recursive Data Dissemination Protocol for Wireless Sensor Networks,” Technical Report UCLA/CSD-TR-01-0023, University of California, Los Angeles, Computer Science Dept., May 2001.
[30] P. Zhang, C. Sadler, S. Lyon, and M. Martonosi, “Hardware Design Experiences in ZebraNet,” Proc. Second ACM Conf. Embedded Networked Sensor Systems (SenSys), pp. 227-238, Nov. 2004.
[31] P. Zhang, C. Sadler, and M. Martonosi, “Middleware for Long-Term Deployment of Delay-Tolerant Sensor Networks,” Proc. First Int'l Workshop Middleware for Sensor Networks (MidSens '06), Nov. 2006.
[32] S. Zhong, J. Chen, and Y.R. Yang, “Sprite: A Simple, Cheat-Proof, Credit-Based System for Mobile Ad-Hoc Networks,” Proc. IEEE INFOCOM, pp. 1987-1997, Apr. 2003.
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