Chronograph is a novel system enabling temporal graphtraversals. Compared to snapshot-oriented systems, this traversal-oriented system is suitable for analyzing information diffusion over time without violating a tim...
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Chronograph is a novel system enabling temporal graphtraversals. Compared to snapshot-oriented systems, this traversal-oriented system is suitable for analyzing information diffusion over time without violating a time constraint on temporal paths. The cornerstone of Chronograph aims at bridging the chasm between point-based semantics and period-based semantics and the gap between temporal graphtraversals and static graphtraversals. Therefore, our graph model and traversallanguage provide the temporal syntax for both semantics, and we present a method converting point-based semantics to period-based ones. Also, Chronograph exploits the temporal support and parallelism to handle the temporal degree, which explosively increases compared to static graphs. We demonstrate how three traversal recipes can be implemented on top of our system: temporal breadth-first search (tBFS), temporal depth-first search (tDFS), and temporal single source shortest path (tSSSP). According to our evaluation, our temporal support and parallelism enhance temporal graphtraversals in terms of convenience and efficiency. Also, Chronograph outperforms existing property graph databases in terms of temporal graphtraversals. We prototype Chronograph by extending Tinkerpop, a de facto standard for property graphs. Therefore, we expect that our system would be readily accessible to existing property graph users.
Model-driven approaches in developing and operating Cyber-Physical Systems are increasingly complemented by data-driven methods. Examples for their use cases are the analysis of model repositories for discovering patt...
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ISBN:
(纸本)9781728122823
Model-driven approaches in developing and operating Cyber-Physical Systems are increasingly complemented by data-driven methods. Examples for their use cases are the analysis of model repositories for discovering patterns and relationships in models, the design-time learning of approximate system and environment models from data, and the detection of divergence from design-time assumptions during operations. In this paper we argue that model- and data-driven approaches have combined use cases that that need complementary services provided by modeling and data analytic frameworks. However, convergence of model-driven and data-driven methods is hindered by the strongly different tool infrastructure. The paper summarizes the integration challenges and proposes a semantic bridge as a solution for filling the gap between the model - and data-driven tool suites.
Chronograph is a novel system enabling temporal graphtraversals. Compared to snapshot-oriented systems, this traversal-oriented system is suitable for analyzing information diffusion over time without violating a tim...
详细信息
ISBN:
(纸本)9781728129037
Chronograph is a novel system enabling temporal graphtraversals. Compared to snapshot-oriented systems, this traversal-oriented system is suitable for analyzing information diffusion over time without violating a time constraint on temporal paths. The cornerstone of Chronograph aims at bridging the chasm between point-based semantics and period-based semantics and the gap between temporal graphtraversals and static graphtraversals. Therefore, our graph model and traversallanguage provide the temporal syntax for both semantics, and we present a method converting point-based semantics to period-based ones. Also, Chronograph exploits the temporal support and parallelism to handle the temporal degree, which explosively increases compared to static graphs. We demonstrate how three traversal recipes can be implemented on top of our system: temporal breadth-first search (tBFS), temporal depthfirst search (tDFS), and temporal single source shortest path (tSSSP). According to our evaluation, our temporal support and parallelism enhance temporal graphtraversals in terms of convenience and efficiency. Also, Chronograph outperforms existing property graph databases in terms of temporal graphtraversals. We prototype Chronograph by extending Tinkerpop, a de facto standard for property graphs. Therefore, we expect that our system would be readily accessible to existing property graph users.
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