Randomized Algorithms for Tracking Distributed Count, Frequencies, and Ranks

We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k players, each holding a counter n i that gets incremented over time, and the goal is to track an ε -approximation of thei...

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Vydáno v:Algorithmica Ročník 81; číslo 6; s. 2222 - 2243
Hlavní autoři: Huang, Zengfeng, Yi, Ke, Zhang, Qin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.06.2019
Springer Nature B.V
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ISSN:0178-4617, 1432-0541
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Shrnutí:We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k players, each holding a counter n i that gets incremented over time, and the goal is to track an ε -approximation of their sum n = ∑ i n i continuously at all times, using minimum communication. While the deterministic communication complexity of the problem is Θ ( k / ε · log N ) , where N is the final value of n when the tracking finishes, we show that with randomization, the communication cost can be reduced to Θ ( k / ε · log N ) . Our algorithm is simple and uses only O (1) space at each player, while the lower bound holds even assuming each player has infinite computing power. Then, we extend our techniques to two related distributed tracking problems: frequency-tracking and rank-tracking , and obtain similar improvements over previous deterministic algorithms. Both problems are of central importance in large data monitoring and analysis, and have been extensively studied in the literature.
Bibliografie:ObjectType-Article-1
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ISSN:0178-4617
1432-0541
DOI:10.1007/s00453-018-00531-y