Article ID Journal Published Year Pages File Type
4950504 Future Generation Computer Systems 2017 15 Pages PDF
Abstract
Event matching acts as a key role in publish/subscribe services, which takes charge of finding all subscriptions that match an event from a subscription set. In large content-based multi-attribute publish/subscribe systems, the performance of event matching is severely challenged due to the increased system scale and search complexity. Most existing event matching algorithms cannot effectively sustain in such a scenario. In this paper, we propose DEXIN (Dynamic EXclusive and INclusive), a fast content-based multi-attribute event matching algorithm using dynamic exclusive and inclusive methods. DEXIN supports highly efficient event matching for subscriptions with limited range-based, unlimited range-based and point-based constraints. DEXIN prepares a pipelined event matching process optimized for each incoming event. The exclusive and inclusive methods, which have different matching costs, are dynamically chosen for event matching over a single attribute. Thus, the search space shrinks very fast since non-matched subscriptions can be filtered out by DEXIN at very early stages in the pipeline. The experiment results demonstrate that DEXIN is superior to several state-of-the-art reference algorithms. Especially, the leading advantage of DEXIN is more significant on matching time and stability for large number of subscriptions and attributes in multiple scenarios.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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