Multimedia and Ubiquitous Engineering, International Conference on (2011)
June 28, 2011 to June 30, 2011
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MUE.2011.27
In this work we focus on the problem of finding the heaviest-k and lightest-k hitters in a sliding window data stream. The most recent research endeavours  have yielded an e-approximate algorithm with update operations in constant time with high probability and O(1/e) query time for the heaviest hitters case. We propose a novel algorithm which for the first time, to our knowledge, provides exact, not approximate, results while at the same time achieves O(1) time with high probability complexity on both update and query operations. Furthermore, our algorithm is able to provide both the heaviest-k and the lightest-k hitters at the same time without any overhead. In this work, we describe the algorithm and the accompanying data structure that supports it and perform quantitative experiments with synthetic data to verify our theoretical predictions.
Data Mining, Continuous Queries, Heaviest Hitters, Lightest Hitters, Data Streams, Sliding Window, On-line Algorithms
Remous-Aris Koutsiamanis, Pavlos S. Efraimidis, "An Exact and O(1) Time Heaviest and Lightest Hitters Algorithm for Sliding-Window Data Streams", Multimedia and Ubiquitous Engineering, International Conference on, vol. 00, no. , pp. 89-94, 2011, doi:10.1109/MUE.2011.27