Randomized algorithms for tracking distributed count, frequencies, and ranks

Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems

Volumn , Issue , 2012, Pages 295-305

  Huang, Zengfeng ^a   Yi, Ke ^a   Zhang, Qin ^b  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b AARHUS UNIVERSITY   (Denmark)

Author keywords

distributed tracking

Indexed keywords

COMMUNICATION COMPLEXITY; COMMUNICATION COST; COMPUTING POWER; DETERMINISTIC ALGORITHMS; DISTRIBUTED TRACKING; FUNDAMENTAL PROBLEM; LARGE DATA; LOWER BOUNDS; RANDOMIZED ALGORITHMS;

COMMUNICATION;

ALGORITHMS;

EID: 84862607379     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2213556.2213596     Document Type: Conference Paper

References (28)

1. P. K. Agarwal, G. Cormode, Z. Huang, J. M. Phillips, Z. Wei, and K. Yi. Mergeable summaries. In Proc. ACM Symposium on Principles of Database Systems, 2012.
2. C. Arackaparambil, J. Brody, and A. Chakrabarti. Functional monitoring without monotonicity. In Proc. International Colloquium on Automata, Languages, and Programming, 2009.
3. B. Babcock and C. Olston. Distributed top-k monitoring. In Proc. ACM SIGMOD International Conference on Management of Data, 2003.
4. Z. Bar-Yossef. The complexity of massive data set computations. PhD thesis, University of California at Berkeley, 2002.
5. H.-L. Chan, T. W. Lam, L.-K. Lee, and H.-F. Ting. Continuous monitoring of distributed data streams over a time-based sliding window. Algorithmica, 62(3-4):1088-1111, 2011.
6. G. Cormode, M. Garofalakis, S. Muthukrishnan, and R. Rastogi. Holistic aggregates in a networked world: Distributed tracking of approximate quantiles. In Proc. ACM SIGMOD International Conference on Management of Data, 2005.
7. G. Cormode and M. Hadjieleftheriou. Finding frequent items in data streams. In Proc. International Conference on Very Large Data Bases, 2008.
8. G. Cormode, S. Muthukrishnan, and K. Yi. Algorithms for distributed functional monitoring. ACM Transactions on Algorithms, 7(2), Article 21, 2011. Preliminary version in SODA'08.
9. G. Cormode, S. Muthukrishnan, K. Yi, and Q. Zhang. Continuous sampling from distributed streams. Journal of the ACM, 59(2), 2012. Preliminary version in PODS'10.
10. W. Feller. An introduction to probability theory and its applications. Wiley, New York, 1968.
11. P. B. Gibbons and S. Tirthapura. Estimating simple functions on the union of data streams. In Proc. ACM Symposium on Parallelism in Algorithms and Architectures, 2001.
12. M. Greenwald and S. Khanna. Space-efficient online computation of quantile summaries. In Proc. ACM SIGMOD International Conference on Management of Data, 2001.
13. Z. Huang, L. Wang, K. Yi, and Y. Liu. Sampling based algorithms for quantile computation in sensor networks. In Proc. ACM SIGMOD International Conference on Management of Data, 2011.
14. Z. Huang, K. Yi, Y. Liu, and G. Chen. Optimal sampling algorithms for frequency estimation in distributed data. In IEEE INFOCOM, 2011.
15. R. Keralapura, G. Cormode, and J. Ramamirtham. Communication-efficient distributed monitoring of thresholded counts. In Proc. ACM SIGMOD International Conference on Management of Data, 2006.
16. A. Manjhi, V. Shkapenyuk, K. Dhamdhere, and C. Olston. Finding (recently) frequent items in distributed data streams. In Proc. IEEE International Conference on Data Engineering, 2005.
17. G. Manku and R. Motwani. Approximate frequency counts over data streams. In Proc. International Conference on Very Large Data Bases, 2002.
18. A. Metwally, D. Agrawal, and A. Abbadi. An integrated efficient solution for computing frequent and top-k elements in data streams. ACM Transactions on Database Systems, 31(3):1095-1133, 2006. (Pubitemid 44600833)
19. J. Misra and D. Gries. Finding repeated elements. Science of Computer Programming, 2:143-152, 1982.
20. J. I. Munro and M. S. Paterson. Selection and sorting with limited storage. Theoretical Computer Science, 12:315-323, 1980.
21. B. Patt-Shamir and A. Shafrir. Approximate distributed top-k queries. Distributed Computing, 21(1):1-22, 2008.
22. S. Suri, C. Toth, and Y. Zhou. Range counting over multidimensional data streams. Discrete and Computational Geometry, 2006.
23. S. Tirthapura and D. P. Woodruff. Optimal random sampling from distributed streams revisited. In Proc. International Symposium on Distributed Computing, 2011.
24. V. N. Vapnik and A. Y. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and its Applications, 16:264-280, 1971.
25. D. P. Woodruff. Efficient and Private Distance Approximation in the Communication and Streaming Models. PhD thesis, Massachusetts Institute of Technology, 2007.
26. D. P. Woodruff and Q. Zhang. Tight bounds for distributed functional monitoring. In Proc. ACM Symposium on Theory of Computing, 2012.
27. A. C. Yao. Probabilistic computations: Towards a unified measure of complexity. In Proc. IEEE Symposium on Foundations of Computer Science, 1977.
28. K. Yi and Q. Zhang. Optimal tracking of distributed heavy hitters and quantiles. In Proc. ACM Symposium on Principles of Database Systems, 2009.