ABSTRACT
There is a growing need to support localization in low-power mobile sensor networks, both indoors and outdoors, when mobile sensor nodes (e.g., mote class) are incapable of independently estimating their location (e.g., when GPS is inappropriate or too costly), or are unable to leverage localization schemes designed for static sensor networks. To address this challenge, we propose ambient beacon localization (ABL), an unconventional approach that allows mobile sensors to localize by exploiting their ambient physical environment. Ambient beacon localization combines machine learning and free range beacon-based techniques to bind distinct characteristics of the physical world that appear in sensor data of known locations, which we call ambient beacon points (ABPs). Supervised learning algorithms are used to allow mobile sensors to recognize ABPs, i.e., those physical locations that are sufficiently distinguishable in terms of sensed data from the rest of the sensor field. Ambient beacon localization leverages the very same sensed data that nodes are already collecting on behalf of applications. When a mobile sensor finds itself at an ambient beacon point it starts to beacon that location so that other nodes in range of an ambient beacon can localize themselves, for example, by applying existing beacon based localization schemes. In this paper, we present the design of ambient beacon localization and its initial evaluation in a building-sized testbed. Our work is at an early stage but our experimental testbed and simulation results demonstrate that this unusual approach to localization shows promise.
- T. Abdelzaher, et al. Mobiscopes for Human Spaces In IEEE Pervasive Computing, 6(2), 2007. Google ScholarDigital Library
- A. T. Campbell, S. B. Eisenman, N. D. Lane, E. Miluzzo, and R. A. Peterson. People-centric Urban Sensing. In ACM/IEEE WICON 2006. Boston, MA, USA. Google ScholarDigital Library
- P. Zhang, C. M. Sadler, S. A. Lyon, and M. Martonosi. Hardware design experiences in zebranet. In ACM SenSys 2004. Baltimore, MD, USA. Google ScholarDigital Library
- B. Hull, et al. CarTel: A Distributed Mobile Sensor Computing System. In ACM SenSys 2006. Boulder, CO, USA. Google ScholarDigital Library
- L. Hu and D. Evans. Localization for mobile sensor networks. In ACM MobiCom 2004. Philadelphia, PA, USA. Google ScholarDigital Library
- R. Nagpal, H. E. Shrobe, and J. Bachrach. Organizing a global coordinate system from local information on an ad hoc sensor network. In IPSN 2003. Palo Alto, CA, USA. Google ScholarDigital Library
- N. Bulusu, J. Heidemann, and D. Estrin. Gps-less low cost outdoor localization for very small devices. IEEE Personal Communications Magazine, 7(5), 2000.Google ScholarCross Ref
- T. He, et al. Range-free localization schemes for large scale sensor networks. In ACM MobiCom 2003. San Diego, CA, USA. Google ScholarDigital Library
- I. Witten and E. Frank. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann, 2005. Google ScholarDigital Library
- Moteiv Tmote Invent. http://www.moteiv.com/Google Scholar
- Y. Wang, et al. CRAWDAD data set princeton/zebranet (v. 2007-02-14). Downloaded from http://crawdad.cs.dartmouth.edu/princeton/zebranet, Feb 2007.Google Scholar
- Y. Wang, S. Jain, M. Martonosi, and K. Fall. Erasure-coding based routing for opportunistic networks. In ACM SIGCOMM WDTN 2005. Philadelphia, Pennsylvania, USA. Google ScholarDigital Library
- P. N. Pathirana, N. Bulusu, A. V. Savkin, and S. Jha. Node localization using mobile robots in delay-tolerant sensor networks. IEEE Trans. on Mobile Computing, 4(3), 2005. Google ScholarDigital Library
- N. B. Priyantha, H. Balakrishnan, E. Demaine, and S. Teller. Mobile-Assisted Localization in Wireless Sensor Networks. In IEEE INFOCOM 2005. Miami, FL, USA.Google Scholar
- B. Dil, S. O. Dulman, and P. J. M. Havinga. Range-based localization in mobile sensor networks. In EWSN 2006. Zurich, Switzerland. Google ScholarDigital Library
- B. Kusy, et al. intrack: High precision tracking of mobile sensor nodes. In EWSN 2007. Delft, The Netherlands.Google ScholarCross Ref
- X. Nguyen, M. I. Jordan, and B. Sinopoli. A kernel-based learning approach to ad hoc sensor network localization. ACM Trans. Sen. Netw., 1(1), 2005. Google ScholarDigital Library
- S. Thrun. Bayesian landmark learning for mobile robot localization. Mach. Learn., 33(1), 1998. Google ScholarDigital Library
- R. Lerner, E. Rivlin, and I. Shimshoni. Landmark selection for task-oriented navigation. In Proc. Of the IEEE/RSJ Int'l Conf. on Intelligent Robots and Systems, Oct 2006.Google ScholarCross Ref
- Nike+. http://www.nikeplus.com.Google Scholar
- Metrosense Project. http://metrosense.dartmouth.edu/.Google Scholar
- I. Ulrich and I. R. Nourbakhsh. Appearance-based place recognition for topological localization. In IEEE Int'l Conf. on Robotics and Automation, 2000.Google Scholar
Index Terms
- Ambient beacon localization: using sensed characteristics of the physical world to localize mobile sensors
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