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Maximizing container-based network isolation in parallel computing clusters

机译：在并行计算群集中最大化基于容器的网络隔离

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摘要

Data-parallel applications, especially those associated with user-facing web services, have struggled to enhance their worst case performance. It is therefore important to improve the minimum amount of resources guaranteed for applications in a cluster. Existing cluster management frameworks, however, provide isolation for computation resources (such as CPU) only, and are oblivious to network isolation guarantees. In this paper, we design, implement and evaluate Libra, a new cluster management framework that helps to maximize the isolation guarantee for the bandwidth requirements from applications. We start with a theoretical analysis of the network sharing problem, which contains two key steps: container placement and bandwidth allocation. By collecting the status of access links and the bandwidth demand of applications, we coordinate the placement of containers to minimize the system bottleneck such that the bandwidth guarantee for applications can be optimized. We further embrace host-based rate limiting to ensure such maximized bandwidth guarantee can be reached without hurting network utilization. Both our testbed-based experiments and large-scale simulations demonstrate that Libra significantly improves the network isolation guarantee: in comparison with existing cluster managers and network schedulers, the performance gain is more than 105.59%. Meanwhile, it improves application performance by 57.71% and maintains high network utilization.
机译：数据并行应用，尤其是与面向用户的Web服务相关的应用程序，努力提高他们最糟糕的案例性能。因此，重要的是提高为集群中的应用程序保证的最低资源量。但是，现有的群集管理框架仅为仅提供计算资源（例如CPU）的隔离，并且令人遗憾的是网络隔离保证。在本文中，我们设计，实现和评估了Libra，这是一个新的群集管理框架，有助于最大化应用程序的带宽要求的隔离保证。我们从网络共享问题的理论分析开始，其中包含两个关键步骤：容器放置和带宽分配。通过收集访问链接的状态和应用程序的带宽需求，我们协调容器的放置，以最小化系统瓶颈，以便可以优化应用程序的带宽保证。我们进一步拥抱基于主机的速率限制，以确保可以达到这种最大化的带宽保证，而不会损害网络利用率。我们测试的基于测试的实验和大规模模拟表明，Libra显着提高了网络隔离保证：与现有的集群经理和网络调度率相比，性能收益超过105.59％。同时，它将应用性能提高了57.71％，并保持了高网络利用率。

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