Graph simulation is one of the most important queries in graph pattern matching, and it is being increasingly used in various applications, e.g., protein interaction networks, software plagiarism detection. Most previous studies mainly focused on the simulation problem on static graphs, which neglected the temporal factors in daily life. In this paper, we investigate a novel problem, namely, temporal bounded simulation on temporal graphs. Specifically, given a pattern query Q with bound constraint and a temporal graph G, we aim to find out the matches Q(G) of Q on G, such that Q(G) satisfies temporal reachability and bound constraint of Q. To tackle this problem efficiently, we propose a simulation matching framework, which consists of three phases, namely pattern segmentation, temporal bounded simulation of pattern segments, and result integration. We first divide the Q into simple small subgraphs (segments). We construct a temporal reachable tree of G. Based on the tree, we propose a basic matching algorithm for the pattern segments. Furthermore, we propose two optimization algorithms by leveraging multi-layer partition strategy to accelerate query processing. After that, we integrate the simulation results obtained from the pattern segments according to the constraints of temporal reachability and the bound of query pattern. Finally, we use real temporal and synthetic datasets to empirically verify the efficiency and effectiveness of our solutions for temporal bounded simulation matching.

中文翻译：

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大规模时间图上的图模拟

图形仿真是图形模式匹配中最重要的查询之一，并且越来越多地用于各种应用程序中，例如蛋白质相互作用网络，软件抄袭检测。以前的大多数研究主要集中在静态图上的模拟问题，而忽略了日常生活中的时间因素。在本文中，我们研究了一个新问题，即时间图的时间有界模拟。具体来说，给定具有约束条件和时间图G的模式查询Q，我们旨在找出Q在G上的匹配Q（G），使得Q（G）满足Q的时间可达性和约束。为了有效地解决这个问题，我们提出了一个仿真匹配框架，它由三个阶段组成，即模式分割，模式段的时间有界模拟和结果集成。我们首先将Q分为简单的小子图（段）。我们构造一个G的时间可达树。基于该树，我们提出了一种用于模式段的基本匹配算法。此外，我们提出了两种利用多层分区策略来加速查询处理的优化算法。然后，根据时间可达性和查询模式的边界，对从模式段中获得的仿真结果进行整合。最后，我们使用真实的时间和综合数据集，以经验方式验证我们的时间有限仿真匹配解决方案的效率和有效性。