On optimal communication cost for gathering correlated data through wireless sensor networks

Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM

Volumn 2006, Issue , 2006, Pages 310-321

  Liu, Junning ^a   Adler, Micah ^a   Towsley, Don ^a   Zhang, Chun ^b  

^a Biologically Inspired Neural and Dynamical Systems Laboratory   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Communication cost minimization; Distributed source coding; Joint coding and routing; Network coding

Indexed keywords

ALGORITHMS; CODES (SYMBOLS); COSTS; HIERARCHICAL SYSTEMS; SENSOR DATA FUSION; TELECOMMUNICATION NETWORKS; WIRELESS TELECOMMUNICATION SYSTEMS;

COMMUNICATION COST MINIMIZATION; DISTRIBUTED SOURCE CODING; JOINT CODING; NETWORK CODING;

INFORMATION RETRIEVAL;

EID: 33751030853     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1161089.1161124     Document Type: Conference Paper

References (32)

1. M. Adler. Collecting correlated information from a sensor network. In SODA, 2005.
2. M. Adler, N. Harvey, K. Jain, R. Kleinberg, and A. Lehman. On the capacity of information networks. In SODA, 2006.
3. R. Ahlswede, N. Cai, S. Li, and R. Yeung. Network information flow. IEEE Transactions on Information Theory, 46(4):1204-1216, July 2000.
4. T. Batu, S. Dasgupta, R. Kumar, and R. Rubinfeld. The complexity of approximating entropy, 2002.
5. C. Chong and S. Kumar. Sensor networks: Evolution, opportunities, and challenges. In IEEE Symposium on Foundations of Computer Science, pages 1247-1256, 2003.
6. J. Chou, D. Petrovic, and K. Ramchandran. A distributed and adaptive signal processing approach to reducing energy consumption in sensor networks. In INFOCOM, 2003.
7. T. Cover. A proof of the data compression theorem of slepian and wolf for ergodic sources. IEEE Transactions on Information Theory, 22:226-228, March 1975.
8. T. Cover and J. Thomas. Elements of Information Theory. Wiley Series in Telecommunications. John Wiley & Sons, New York, NY, USA, 1991.
9. N. Cressie. Statistics for Spatial Data. John Wiley & Sons, 1993.
10. R. Cristescu, B. Beferull-Lozano, and M. Vetterli. On network correlated data gathering. In IEEE INFOCOM, 2004.
11. R. Cristescu, B. Beferull-Lozano, and M. Vetterli. Networked Slepian-Wolf: Theory, Algorithms and Scaling Laws. IEEE Transactions on Information Theory, 2005.
12. D. Estrin, D. Culler, K. Pister, and G. Sukhatme. Connecting the physical world with pervasive networks. IEEE Pervasive Computing, 1(1):59-69, 2002.
13. D. Ganesan, R. Cristescu, and B. Beferull-Lozano. Power-efficient sensor placement and transmission structure for data gathering under distortion constraints. In IPSN, 2004.
14. A. Goel and D. Estrin. Simultaneous optimization for concave costs: Single sink aggregation or single source buy-at-bulk. In SODA, 2003.
15. T. Han. Slepian-wolf-cover theorem for networks of channels. Information and Control, 47(1):67-83, 1980.
16. T. Ho, M. Médard, M. Effros, and R. Koetter. Network coding for correlated sources. In CISS, 2004.
17. A. Jindal and K. Psounis. Modeling spatially-correlated sensor network data. In SECON, 2004.
18. A. Lehman and E. Lehman. Complexity classification of network information flow problems. In SODA, 2004.
19. Z. Li, B. Li, D. Jiang, and L. Lau. On achieving optimal throughput with network coding. In INFOCOM, 2005.
20. J. Liu, M. Adler, and D. Towsley. Collecting correlated data through a network with minimum cost: Distance entropy and a practical asymptotically optimal design. Technical Report CS TR05-64, University of Massachusetts, Amherst, 2005.
21. Y. Liu, D. Towsley, J. Weng, and D. Goeckel. An information theoretic approach to network trace compression. Technical Report CS TR05-03, University of Massachusetts, Amherst, 2005.
22. D. Lun, Médard, T. Ho, and R. Koetter. Network coding with a cost criterion. Technical Report P-2584, MIT, 2004.
23. D. Mackay. Information theory, inferrence, and learning algorithms. John Wiley & Sons, 2004.
24. D. Marco, E. 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, 2003.
25. R. Motwani and P. Raghavan. Randomized algorithms. Cambridge University Press, 1995.
26. S. Pattern, B. Krishnamachari, and R. Govindan. The impact of spatial correlation on routing with compression in wireless sensor networks. In IPSN, 2004.
27. D. W. R. Johnson, Applied Multivariate Statistical Analysis. Prentice Hall, 2002.
28. A. Ramamoorthy, K. Jain, P. Chou, and M. Effros. Separating distributed source coding from network coding. In Allerton, 2004.
29. D. Slepian and J. Wolf. Noiseless coding of correlated information sources. IEEE Transactions on Information Theory, IT-19(4):471-480, July 1973.
30. Y. Wu, V. Stankovic, Z. Xiong, and S. Kung. On practical design for joint distributed source and network coding. In NETCOD, 2005.
31. Z. Xiong, A. Liveris, and S. Cheng, Distributed source coding for sensor networks. In IEEE Signal Processing Magazine, pages 522-533, September 2004.
32. M. Xue, K. K. Droegemeier, V. Wong, A. Shapiro, K. Brewster, F. Carr, D. Weber, Y. Liu, and D. Wang. The advanced regional prediction system (arps)a multi-scale nonhydrostatic atmospheric simulation and prediction tool. part ii: Model physics and applications. Meteorol. Atmos. Phys. 76, 76, 2001.