Title :
An Exact and O(1) Time Heaviest and Lightest Hitters Algorithm for Sliding-Window Data Streams
Author :
Koutsiamanis, Remous-Aris ; Efraimidis, Pavlos S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Democritus Univ. of Thrace, Xanthi, Greece
Abstract :
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.
Keywords :
approximation theory; data handling; probability; query processing; e-approximate algorithm; hitter algorithm; probability complexity; query operation; query time; sliding window data stream; Approximation algorithms; Arrays; Computational complexity; Itemsets; Prediction algorithms; Continuous Queries; Data Mining; Data Streams; Heaviest Hitters; Lightest Hitters; On-line Algorithms; Sliding Window;
Conference_Titel :
Multimedia and Ubiquitous Engineering (MUE), 2011 5th FTRA International Conference on
Conference_Location :
Loutraki
Print_ISBN :
978-1-4577-1228-9
Electronic_ISBN :
978-0-7695-4470-0
DOI :
10.1109/MUE.2011.27