Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2011-11-13
Computer Science
Distributed, Parallel, and Cluster Computing
22 pages, 7 figures
Scientific paper
The proliferation of sensing and monitoring applications motivates adoption of the event stream model of computation. Though sliding windows are widely used to facilitate effective event stream processing, it is greatly challenged when the event sources are distributed and asynchronous. To address this challenge, we first show that the snapshots of the asynchronous event streams within the sliding window form a convex distributive lattice (denoted by Lat-Win). Then we propose an algorithm to maintain Lat-Win at runtime. The Lat-Win maintenance algorithm is implemented and evaluated on the open-source context-aware middleware we developed. The evaluation results first show the necessity of adopting sliding windows over asynchronous event streams. Then they show the performance of detecting specified predicates within Lat-Win, even when faced with dynamic changes in the computing environment.
Cao Jiannong
Huang Yu
Lu Jian
Ma Xiaoxing
Yang Yiling
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