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Measuring and Analyzing Migration Delay for the Computational Load Balancing of Distributed Virtual Simulations

机译:测量和分析迁移延迟,以实现分布式虚拟仿真的计算负载平衡

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Distributed virtual simulations can always undergo load imbalances during run-time due to their dependency on underlying shared resources. Such imbalances are commonly generated by external background load, improper deployment of simulation elements, and dynamic oscillations of simulation load. HLA was devised as a simulation framework that simplifies the design and management of distributed simulations. Even though the framework presents services for the coordination of simulations, it does not provide any tool for identifying and reacting to load imbalances. Due to the importance of balancing simulation load, many schemes have been developed, aiming to reduce simulation time through analysis of specific metrics. These schemes are limited to issues from specific simulation applications, or they disregard large-scale environmental characteristics. In order to overcome the drawbacks of previous balancing approaches, a distributed balancing scheme has been designed. Nevertheless, this scheme, as well as the others, is not concerned with migration latencies when redistributing simulation load. Migration delays are directly involved with balancing responsiveness and efficiency, and they can cause simulation performance loss instead of performance improvement if they are not considered in the redistribution analysis. Thus, a migration-aware balancing scheme is proposed to include migration latency analysis in its load redistribution algorithm. Extensions are also proposed to improve the analysis of migration delays by enabling necessary costly migrations in iterative analysis. Experiments have been conducted to evaluate the proposed migration-aware balancing schemes by comparing performance when costly migrations are present in simulations.
机译:由于分布式虚拟仿真对基础共享资源的依赖,因此在运行时始终会遇到负载不平衡的情况。这种不平衡通常是由外部背景负载,模拟元素的不正确部署以及模拟负载的动态振荡引起的。 HLA被设计为一种仿真框架,可简化分布式仿真的设计和管理。即使该框架提供了用于协调仿真的服务,也没有提供任何工具来识别负载不平衡并对负载不平衡做出反应。由于平衡仿真负载的重要性,因此已经开发了许多方案,旨在通过分析特定指标来减少仿真时间。这些方案仅限于来自特定仿真应用程序的问题,或者它们忽略了大规模的环境特征。为了克服先前的平衡方法的缺点,已经设计了分布式平衡方案。但是,在重新分配模拟负载时,该方案以及其他方案都与迁移延迟无关。迁移延迟与平衡响应速度和效率直接相关,如果在重新分配分析中未考虑迁移延迟,则会导致仿真性能下降而不是性能改善。因此,提出了一种迁移感知平衡方案,该方案将迁移等待时间分析包括在其负载重新分配算法中。还提出了扩展,以通过在迭代分析中进行必要的昂贵迁移来改善对迁移延迟的分析。当仿真中存在昂贵的迁移时,已经进行了一些实验,通过比较性能来评估建议的迁移感知平衡方案。

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