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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Scalable Real-Time Monitoring for Distributed Applications
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Scalable Real-Time Monitoring for Distributed Applications

机译：分布式应用程序的可扩展实时监控

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摘要

In order to assess service quality of a networked application (such as a streaming session), distributed monitoring servers need to continuously collect application-specific performance metrics in real time. Much of the previous work to address this is to use distributed aggregation tree (DAT) rooted at each monitor. However, this approach often leads to high monitoring delay and network stress. In this paper, we study a highly scalable monitoring network for distributed applications. In the network, there are distributed monitors collecting application performance in two steps: first, client applications report their performance to some proxies by means of a client overlay, and then the proxies report the performance to the distributed monitors using another proxy overlay. We first formulate the problem to construct overlays minimizing monitoring delay. The problem is shown to be NP-hard. Then, we present a simple, efficient, and scalable monitoring algorithm called SMon, which continuously reduces network diameter in real time in a distributed manner. Through simulations and actual experimental measurements with implementation, we show that SMon achieves low monitoring delay, network stress, and protocol overhead for distributed applications.
机译：为了评估联网应用程序（例如流会话）的服务质量，分布式监视服务器需要连续不断地实时收集特定于应用程序的性能指标。解决此问题的许多先前工作是使用植根于每个监视器的分布式聚合树（DAT）。但是，这种方法通常会导致较高的监视延迟和网络压力。在本文中，我们研究了用于分布式应用程序的高度可扩展的监视网络。在网络中，有分布在两个步骤中的收集监控器的分布式监视器：首先，客户端应用程序通过客户端覆盖将其性能报告给某些代理，然后代理使用另一个代理覆盖将性能报告给分布式监视器。我们首先提出问题以构造覆盖层，以最小化监视延迟。该问题显示为NP难题。然后，我们提出了一种称为SMon的简单，高效且可扩展的监视算法，该算法以分布式方式连续不断地实时减小网络直径。通过仿真和实际实验测量以及实施，我们表明SMon实现了分布式应用程序的低监视延迟，网络压力和协议开销。

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