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Pattern Matching in Link Streams: A Token-Based Approach

机译:链接流中的模式匹配:基于令牌的方法

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摘要

Link streams model the dynamics of interactions in complex distributed systems as sequences of links (interactions) occurring at a given time. Detecting patterns in such sequences is crucial for many applications but it raises several challenges. In particular, there is no generic approach for the specification and detection of link stream patterns in a way similar to regular expressions and automata for text patterns. To address this, we propose a novel automata framework integrating both timed constraints and finite memory together with a recognition algorithm. The algorithm uses structures similar to tokens in high-level Petri nets and includes non-determinism and concurrency. We illustrate the use of our framework in real-world cases and evaluate its practical performances.
机译:链路流模拟复杂分布式系统中的交互动态作为在给定时间发生的链路(交互)的序列。这些序列中的检测模式对于许多应用来说至关重要,但它提高了几个挑战。特别地,以类似于文本模式的常规表达式和自动机的方式,对规范和检测链路流模式没有通用方法。为了解决这个问题,我们提出了一种新颖自动机框架,将定时约束和有限内存与识别算法一起集成。该算法使用类似于高级Petri网中的标记的结构,并包括非确定性和并发性。我们说明了我们在现实案例中使用我们的框架,并评估其实际表现。

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