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STACS
2010
Springer

Continuous Monitoring of Distributed Data Streams over a Time-based Sliding Window

12 years 3 months ago
Continuous Monitoring of Distributed Data Streams over a Time-based Sliding Window
The past decade has witnessed many interesting algorithms for maintaining statistics over a data stream. This paper initiates a theoretical study of algorithms for monitoring distributed data streams over a time-based sliding window (which contains a variable number of items and possibly out-of-order items). The concern is how to minimize the communication between individual streams and the root, while allowing the root, at any time, to be able to report the global statistics of all streams within a given error bound. This paper presents communication-efficient algorithms for three classical statistics, namely, basic counting, frequent items and quantiles. The worst-case communication cost over a window is O(k ε log εN k ) bits for basic counting and O(k ε log N k ) words for the remainings, where k is the number of distributed data streams, N is the total number of items in the streams that arrive or expire in the window, and ε < 1 is the desired error bound. Matching and nearl...
Ho-Leung Chan, Tak Wah Lam, Lap-Kei Lee, Hing-Fung
Added 14 May 2010
Updated 14 May 2010
Type Conference
Year 2010
Where STACS
Authors Ho-Leung Chan, Tak Wah Lam, Lap-Kei Lee, Hing-Fung Ting
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