论文标题

基于端到端主动测量的链接延迟的最佳估计

Optimal Estimation of Link Delays based on End-to-End Active Measurements

论文作者

Tajiki, Mohammad Mahdi, Petroudi, Seyed Hesamedin Ghasemi, Salsano, Stefano, Uhlig, Steve, Castro, Ignacio

论文摘要

当前基于IP的网络支持广泛的延迟敏感应用程序,例如网络游戏的实时视频流。对于网络提供商来说,为这些应用程序提供足够的经验质量至关重要。提供的服务通常受到紧张的服务水平协议的监管,需要不断监控。由于保证指标的第一步是测量它,因此延迟测量成为网络提供商的基本操作。在许多情况下,操作员需要测量所有网络链接的延迟。我们将所有链接延迟的集合称为链接延迟向量(LDV)。收集LDV的典型解决方案在网络上施加了大量的开销。在本文中,我们提出了一种解决方案,以低空的方法实时测量LDV。特别是,我们将一些流入网络注入网络,并根据这些流的延迟推断LDV。为此,应选择监视流及其路径,以最大程度地减少网络监视开销。在这方面,具有挑战性的问题是选择适当的流量组合,以便通过知道它们的延迟,可以解决一组线性方程并获得唯一的LDV。我们首先提出一种数学公式,以ILP问题的形式选择流量的最佳组合。然后,我们开发了一种启发式算法,以克服现有ILP求解器的高计算复杂性。作为进一步的一步,我们提出了一种荟萃分析算法来求解上述方程并推断LDV。此步骤的挑战性部分是链接延迟的波动性。使用Mininet网络模拟器对现实世界模拟网络拓扑进行了评估所提出的解决方案。仿真结果表明,用实时方式使用可忽略的网络开销的提议解决方案的准确性。

Current IP based networks support a wide range of delay-sensitive applications such as live video streaming of network gaming. Providing an adequate quality of experience to these applications is of paramount importance for a network provider. The offered services are often regulated by tight Service Level Agreements that needs to be continuously monitored. Since the first step to guarantee a metric is to measure it, delay measurement becomes a fundamental operation for a network provider. In many cases, the operator needs to measure the delay on all network links. We refer to the collection of all link delays as the Link Delay Vector (LDV). Typical solutions to collect the LDV impose a substantial overhead on the network. In this paper, we propose a solution to measure the LDV in real-time with a low-overhead approach. In particular, we inject some flows into the network and infer the LDV based on the delay of those flows. To this end, the monitoring flows and their paths should be selected minimizing the network monitoring overhead. In this respect, the challenging issue is to select a proper combination of flows such that by knowing their delay it is possible to solve a set of a linear equation and obtain a unique LDV. We first propose a mathematical formulation to select the optimal combination of flows, in form of ILP problem. Then we develop a heuristic algorithm to overcome the high computational complexity of existing ILP solvers. As a further step, we propose a meta-heuristic algorithm to solve the above-mentioned equations and infer the LDV. The challenging part of this step is the volatility of link delays. The proposed solution is evaluated over real-world emulated network topologies using the Mininet network emulator. Emulation results show the accuracy of the proposed solution with a negligible networking overhead in a real-time manner.

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