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Algorithm design for a class of base station location problems in sensor networks

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Abstract

Base station placement has significant impact on sensor network performance. Despite its significance, results on this problem remain limited, particularly theoretical results that can provide performance guarantee. This paper proposes a set of procedure to design (1− ε) approximation algorithms for base station placement problems under any desired small error bound ε > 0. It offers a general framework to transform infinite search space to a finite-element search space with performance guarantee. We apply this procedure to solve two practical problems. In the first problem where the objective is to maximize network lifetime, an approximation algorithm designed through this procedure offers 1/ε2 complexity reduction when compared to a state-of-the-art algorithm. This represents the best known result to this problem. In the second problem, we apply the design procedure to address base station placement problem when the optimization objective is to maximize network capacity. Our (1− ε) approximation algorithm is the first theoretical result on this problem.

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References

  1. M. Bhardwaj and A.P. Chandrakasan, Bounding the lifetime of sensor networks via optimal role assignments, in: Proc. IEEE Infocom (June 2002) pp. 1587–1596.

  2. A. Bogdanov, E. Maneva and S. Riesenfeld, Power-aware base station positioning for sensor networks, in: Proc. IEEE Infocom (March 2004) pp. 575–585.

  3. T.X. Brown, H.N. Gabow and Q. Zhang, Maximum flow-life curve for a wireless ad hoc network, in: Proc. ACM Mobihoc (October 2001) pp. 128–136.

  4. S.S. Dhillon and K. Chakrabarty, Sensor placement for effective coverage and surveillance in distributed sensor networks, in: Proc. IEEE WCNC (March 2003) pp. 1609–1614.

  5. A. Efrat, S. Har-Peled and J. Mitchell, Approximation algorithms for location problems in sensor networks, in: Proc. IEEE/Creat-Net BROADNETS—Wireless Networking Symposium (October 2005) pp. 767–776.

  6. Y.T. Hou, Y. Shi and H.D. Sherali, Rate allocation in wireless sensor networks with network lifetime requirement, in: Proc. ACM Mobihoc (May 2004) pp. 67–77.

  7. Y.T. Hou, Y. Shi, H.D. Sherali and S.F. Midkiff, Prolonging sensor network lifetime with energy provisioning and relay node placement, in: Proc. IEEE SECON (September 2005) pp. 295–304.

  8. W. Heinzelman, Application-specific Protocol Architectures for Wireless Networks, Ph.D. thesis, Massachusetts Institute of Technology, (June 2000).

  9. K. Kalpakis, K. Dasgupta and P. Namjoshi, Maximum lifetime data gathering and aggregation in wireless sensor networks, in: Proc. of the IEEE International Conference on Networking (August 2002) pp. 685–696.

  10. D. Marco, E.J. Duarte-Melo, M. Liu and D.L. Neuhoff, On the many-to-one transport capacity of a dense wireless sensor network and the compressibility of its data, in: Proc. of the International Workshop on Information Processing in Sensor Networks (April 2003) pp. 1–16.

  11. J. Pan, Y.T. Hou, L. Cai, Y. Shi and S.X. Shen, Topology control for wireless sensor networks, in: Proc. ACM Mobicom (September 2003) pp. 286–299.

  12. T.S. Rappaport, Wireless Communications: Principles and Practice (Prentice Hall, Upper Saddle River, NJ, 1996).

    Google Scholar 

  13. N. Sadagopan and B. Krishnamachari, Maximizing data extraction in energy-limited sensor networks, in: Proc. IEEE Infocom (March 2000) pp. 1717–1727.

  14. K. Sohrabi, J. Gao, V. Ailawadhi and G. Pottie, Protocols for self-organizing of a wireless sensor network, IEEE Personal Communications Magazine 7 (2000) 16–27.

    Article  Google Scholar 

  15. S. Toumpis, Capacity bounds for three classes of wireless networks: asymmetric, cluster and hybrid, in: Proc. ACM Mobihoc (May 2004) pp. 133–144.

  16. G. Wang, G. Cao and T. La Porta, Movement-assisted sensor deployment, in: Proc. IEEE Infocom (March 2004) pp. 2469–2479.

  17. J. Wu and S. Yang, SMART: A scan-based movement-assisted sensor deployment method in wireless sensor networks, in: Proc. IEEE Infocom (March 2005) pp. 2313–2324.

  18. K. Xu, H. Hassanein and G. Takahara, Relay node deployment strategies in heterogeneous wireless sensor networks: multiple-hop communication case, in: Proc. IEEE SECON (September 2005) pp. 575–585.

  19. H. Zhang and J. Hou, On deriving the upper bound of α-lifetime for large sensor networks, in: Proc. ACM Mobihoc (May 2004) pp. 121–132.

  20. W. Zhao, M. Ammar and E. Zegura, The energy-limited capacity of wireless networks, in: Proc. IEEE SECON (October 2004) pp. 279–288.

  21. Y. Zou and K. Chakrabarty, Sensor deployment and target localization based on virtual forces, in: Proc. IEEE Infocom (April 2003) pp. 1293–1303.

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Authors and Affiliations

  1. The Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, 24061, USA

    Yi Shi & Y. Thomas Hou

  2. Department of Computer Science, University of Arizona, Tucson, AZ, 85721, USA

    Alon Efrat

Authors
  1. Yi Shi
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  2. Y. Thomas Hou
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  3. Alon Efrat
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Correspondence to Yi Shi.

Additional information

Yi Shi received his B.S. degree from University of Science and Technology of China, Hefei, China, in 1998, a M.S. degree from Institute of Software, Chinese Academy of Science, Beijing, China, in 2001, and a second M.S. degree from Virginia Tech, Blacksburg, VA, in 2003, all in computer science. He is currently working toward his Ph.D. degree in electrical and computer engineering at Virginia Tech. While in undergraduate, he was a recipient of Meritorious Award in International Mathematical Contest in Modeling and 1997 and 1998, respectively. His current research focuses on algorithms and optimizations for wireless sensor networks, wireless ad hoc networks, UWB-based networks, and SDR-based networks. His work has appeared in journals and highly selective international conferences (ACM Mobicom, ACM Mobihoc, and IEEE Infocom).

Y. Thomas Hou received the B.E. degree from the City College of New York in 1991, the M.S. degree from Columbia University in 1993, and the Ph.D. degree from Polytechnic University, Brooklyn, New York, in 1998, all in Electrical Engineering.

Since Fall 2002, he has been an Assistant Professor at Virginia Tech, the Bradley Department of Electrical and Computer Engineering, Blacksburg, VA. His current research interests are radio resource (spectrum) management and networking for software-defined radio wireless networks, optimization and algorithm design for wireless ad hoc and sensor networks, and video communications over dynamic ad hoc networks. From 1997 to 2002, Dr. Hou was a Researcher at Fujitsu Laboratories of America, Sunnyvale, CA, where he worked on scalable architectures, protocols, and implementations for differentiated services Internet, service overlay networking, video streaming, and network bandwidth allocation policies and distributed flow control algorithms.

Prof. Hou is a recipient of an Office of Naval Research (ONR) Young Investigator Award (2003) and a National Science Foundation (NSF) CAREER Award (2004). He is a Co-Chair of Technical Program Committee of the Second International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM 2007), Orlando, FL, August 1–3, 2007. He also was the Chair of the First IEEE Workshop on Networking Technologies for Software Defined Radio Networks, September 25, 2006, Reston, VA. Prof. Hou holds two U.S. patents and has three more pending.

Alon Efrat earned his Bachelor in Applied Mathematics from the Technion (Israel’s Institute of Technology) in 1991, his Master in Computer Science from the Technion in 1993, and his Ph.D in Computer Science from Tel-Aviv University in 1998. During 1998–2000 he was a Post Doctorate Research Associate at the Computer Science Department of Stanford University, and at IBM Almaden Research Center. Since 2000, he is an assistant professor at the Computer Science Department of the University of Arizona. His main research areas are Computational Geometry, and its applications to sensor networks and medical imaging.

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Shi, Y., Hou, Y.T. & Efrat, A. Algorithm design for a class of base station location problems in sensor networks. Wireless Netw 15, 21–38 (2009). https://doi.org/10.1007/s11276-007-0020-2

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