Asynchronous in-network prediction: Efficient aggregation in sensor networks

ACM Transactions on Sensor Networks

Volumn 4, Issue 4, 2008, Pages

  Edara, Pavan ^a   Limaye, Ashwin ^a   Ramamritham, Krithi ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

Aggregation; Coherency; Energy efficient; Prediction; Query processing

Indexed keywords

AGGREGATE QUERIES; AGGREGATION; COHERENCY; COMPUTATIONALLY EFFICIENT; ENERGY CONSUMPTION; ENERGY EFFICIENT; HIGH-QUALITY; IN-NETWORK AGGREGATION; MESSAGE PROCESSING; NETWORK FILTERING; NETWORK PREDICTION; PREDICTION; QUALITY OF DATA; QUERY PROCESSING; QUERY RESULTS; REAL-WORLD DATA;

AGGLOMERATION; AGGREGATES; CONSERVATION; EFFICIENCY; ENERGY EFFICIENCY; ENERGY POLICY; FORECASTING; SENSORS;

SENSOR NETWORKS;

EID: 51849106407     PISSN: 15504859     EISSN: 15504867     Source Type: Journal    
DOI: 10.1145/1387663.1387671     Document Type: Article

References (24)

1. CHU, D., DESHPANDE, A., HELLERSTEIN, J. M., AND HONG, W. 2006. Approximate data collection in sensor networks using probabilistic models. In Proceedings of the 22nd International Conference on Data Engineering (ICDE'06).
2. CORMODE, G., GAROFALAKIS, M., MUTHUKRISHNAN, S., AND RASTOGI, R. 2005. Holistic aggregates in a networked world: distributed tracking of approximate quantiles. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD'05). 25-36.
3. DESHPANDE, A., GUESTRIN, C., MADDEN, S., HELLERSTEIN, J. M., AND HONG, W. 2004. Model-driven data acquisition in sensor networks. In Proceedings of the 30th Internatinal Conference on Very Large Databases (VLDB'04). 588-599.
4. GOEL, S. AND IMIELINSKI, T. 2001. Prediction-based monitoring in sensor networks: taking lessons from MPEG. SIGCOMM Comput. Comm. Rev. 31, 5.
5. HILL, J. AND MICA, D.C. 2002. Awireless platform for deeply embedded networks. IEEE Micro. 22, 6.
6. HILL, J., SZEWCZYK, R., WOO, A., HOLLAR, S., CULLER, D., AND PISTER, K. 2000. System architecture directions for network sensors. In Proceedings of the 9th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'00).
7. INTANAGONWIWAT, C., GOVINDAN, R., AND ESTRIN, D. 2000. Directed diffusion: A scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th International Conference on Mobile Computing and Networking (MobiCom'00).
8. INVENTORY OF U. S. GLOBEC GEORGES BANK DATA, PROJECT: AL9508. 1995. http://jgof.wh.whoi.edu/jg/serv/globec/gb/brdscale/al_shipdata.html1%7Bdir= globec.whoi.edu/jg/dir/globec/gb/broadscale/,info=globec.whoi.edu/jg/info/ globec/gb/broadscale/alongtrack%7D?cruise_id%20%eq%20al9508.
9. KAISER, W. J. 2000. WINS NG 1.0 Transceiver Power Dissipation Specifications. Sensoria Corp.
10. LEVIS, P., LEE, N., WELSH, M., AND CULLER, D. 2003. TOSSIM: accurate and scalable simulation of entire TinyOS applications. In Proceedings of the 1st ACM Conference on Embedded Networked Sensor Systems (SenSys'03).
11. LI, M., GANESAN, D., AND SHENOY, P. 2006. PRESTO: feedbackdriven data management in sensor networks. In ACM/USENIX Symposium on Networked Systems Design and Implementation.
12. MADDEN, S., FRANKLIN, M. J., HELLERSTEIN, J. M., AND HONG, W. 2002. TAG: a tiny aggregation service for ad-hoc sensor networks. SIGOPS Oper. Syst. Rev. 36, SI.
13. MANJHI, A., NATH, S., AND GIBBONS, P. B. 2005. Tributaries and deltas: efficient and robust aggregation in sensor network streams. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD'05).
14. NATH, S., GIBBONS, P. B., SESHAN, S., AND ANDERSON, Z. R. 2004. Synopsis diffusion for robust aggregation in sensor networks. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys'04). ACM Press, New York, NY, 250-262.
15. OLSTON, C., JIANG, J., AND WIDOM, J. 2003. Adaptive filters for continuous queries over distributed data streams. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD'03). ACM Press, New York, NY, 563-574.
16. OLSTON, C., LOO, B. T., AND WIDOM, J. 2001. Adaptive precision setting for cached approximate values. SIGMOD Rec. 30, 2, 355-366.
17. PAPADIMITRIOU, S., BROCKWELL, A., AND FALOUTSOS, C. 2003. Adaptive, hands-off stream mining. In Proceedings of the 29th International Conference on Very Large Databases (VLDB'03).
18. SHAH, S., DHARMARAJAN, S., AND RAMAMRITHAM, K. 2003. An efficient and resilient approach to filtering and disseminating streaming data. In Proceedings of the 29th International Conference on Very Large Data Bases (VLDB'03).
19. SHARAF, M.A., BEAVER, J., LABRINIDIS, A., and Chrysanthis,P.K. 2003. TiNA:ascheme for temporal coherency-aware in-network aggregation. In Proceedings of the 3rd International ACM Workshop on Data Engineering for Wireless and Mobile Access (MobiDE'03).
20. TINYOS WEBSITE. http://www.tinyos.net.
21. TRIGONI, N., YAO, Y., DEMERS, A. J., GEHRKE, J., AND RAJARAMAN, R. 2005. Multi-query optimization for sensor networks. In Proceedings of the 1st IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'05). 307-321.
22. WOO, A., TONG, T., AND CULLER, D. 2003. Taming the underlying challenges of reliable multihop routing in sensor networks. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys'03).
23. YAO, Y. AND GEHRKE, J. 2002. The cougar approach to in-network query processing in sensor networks. SIGMOD Rec. 31, 3, 9-18.
24. YOUNG, P. 1984. Recursive Estimation and Time-Series Analysis: An Introduction. Springer-Verlag. Berlin, Germany.