Efficient threshold monitoring for distributed probabilistic data

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2012, Pages 1120-1131

  Tang, Mingwang ^a   Li, Feifei ^a   Phillips, Jeff M ^a   Jestes, Jeffrey ^a  

^a Department of Electrical and Computer Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BASELINE METHODS; COMMUNICATION COST; COMPREHENSIVE STUDIES; DETERMINISTIC DATA; DISTRIBUTED DATA; EXPERIMENTAL EVALUATION; LARGE DATASETS; MULTIPLE SOURCE; PROBABILISTIC DATA; PROBABILITY THRESHOLD; RUNNING TIME; SCIENTIFIC INSTITUTES; SENSOR FIELDS; USER-SPECIFIED CONSTRAINTS;

INFORMATION MANAGEMENT;

MONITORING;

EID: 84864192454     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2012.34     Document Type: Conference Paper

References (35)

1. P. Billingsley. Probability and measure. Wiley-Interscience, 1995.
2. R. Cheng, D. Kalashnikov, and S. Prabhakar. Evaluating probabilistic queries over imprecise data. In SIGMOD, 2003.
3. R. Cheng, Y. Xia, S. Prabhakar, R. Shah, and J. S. Vitter. Efficient indexing methods for probabilistic threshold queries over uncertain data. In VLDB, 2004.
4. G. Cormode, S. Muthukrishnan, and K. Yi. Algorithms for distributed functional monitoring. In SODA, 2008.
5. N. Dalvi and D. Suciu. Efficient query evaluation on probabilistic databases. In VLDB, 2004.
6. A. Deshpande, C. Guestrin, and S. Madden. Using probabilistic models for data management in acquisitional environments. In CIDR, 2005.
7. A. Deshpande, C. Guestrin, S. Madden, J. Hellerstein, and W. Hong. Model-driven data acquisition in sensor networks. In VLDB, 2004.
8. X. Dong, A. Y. Halevy, and C. Yu. Data integration with uncertainty. In VLDB, 2007.
9. T. Ge, D. Grabiner, and S. B. Zdonik. Monte carlo query processing of uncertain multidimensional array data. In ICDE, 2011.
10. L. Gruenwald, H. Chok, and M. Aboukhamis. Using data mining to estimate missing sensor data. In ICDMW, 2007.
11. M. Hua and J. Pei. Continuously monitoring top-k uncertain data streams: a probabilistic threshold method. DPD, 26(1):29-65, 2009.
12. L. Huang, M. Garofalakis, A. D. Joseph, and N. Taft. Communication- efficient tracking of distributed cumulative triggers. In ICDCS, 2007.
13. R. Jampani, F. Xu, M. Wu, L. L. Perez, C. M. Jermaine, and P. J. Haas. MCDB: a monte carlo approach to managing uncertain data. In SIGMOD, 2008.
14. T. S. Jayram, S. Kale, and E. Vee. Efficient aggregation algorithms for probabilistic data. In SODA, 2007.
15. T. S. Jayram, A. McGregor, S. Muthukrishnan, and E. Vee. Estimating statistical aggregates on probabilistic data streams. In PODS, 2007.
16. S. Jeyashanker, S. Kashyap, R. Rastogi, and P. Shukla. Efficient constraint monitoring using adaptive thresholds. In ICDE, 2008.
17. C. Jin, K. Yi, L. Chen, J. X. Yu, and X. Lin. Sliding-window top-k queries on uncertain streams. In VLDB, 2008.
18. B. Kanagal and A. Deshpande. Online filtering, smoothing and probabilistic modeling of streaming data. In ICDE, 2008.
19. R. Keralapura, G. Cormode, and J. Ramamirtham. Communication efficient distributed monitoring of thresholded count. In SIGMOD, 2006.
20. F. Li, K. Yi, and J. Jestes. Ranking distributed probabilistic data. In SIGMOD, 2009.
21. R. Motwani and P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995.
22. R. Murthy, R. Ikeda, and J. Widom. Making aggregation work in uncertain and probabilistic databases. TKDE, 23(8):1261-1273, 2011.
23. C. Olston, J. Jiang, and J. Widom. Adaptive filters for continuous queries over distributed data streams. In SIGMOD, 2003.
24. L. Perez, S. Arumugam, and C. Jermaine. Evaluation of probabilistic threshold queries in MCDB. In SIGMOD, 2010.
25. Y. Qi, R. Jain, S. Singh, and S. Prabhakar. Threshold query optimization for uncertain data. In SIGMOD, 2010.
26. R. Ross, V. S. Subrahmanian, and J. Grant. Aggregate operators in probabilistic databases. J. ACM, 52(1):54-101, 2005.
27. SAMOS. Shipboard Automated Meteorological and Oceanographic System. http://samos.coaps.fsu.edu.
28. A. D. Sarma, O. Benjelloun, A. Halevy, S. Nabar, and J. Widom. Representing uncertain data: models, properties, and algorithms. The VLDB Journal, 18(5):989-1019, 2009.
29. I. Sharfman, A. Schuster, and D. Keren. A geometric approach to monitoring threshold functions over distributed data streams. In SIGMOD, 2006.
30. M. A. Soliman, I. F. Ilyas, and K. C.-C. Chang. Probabilistic top-k and ranking-aggregate queries. TODS, 33(3):1-54, 2008.
31. D. Suciu, D. Olteanu, C. Ré, and C. Koch. Probabilistic Databases. Synthesis Lectures on Data Management. Morgan & Claypool Publishers, 2011.
32. T. T. L. Tran, A. McGregor, Y. Diao, L. Peng, and A. Liu. Conditioning and aggregating uncertain data streams: Going beyond expectations. PVLDB, 3(1):1302-1313, 2010.
33. V. Vapnik and A. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. The. of Prob. App., 16:264-280, 1971.
34. S. Wang, G. Wang, and J. Chen. Distributed frequent items detection on uncertain data. In ADMA, 2010.
35. H. Woo and A. K. Mok. Real-time monitoring of uncertain data streams using probabilistic similarity. In RTSS, 2007.