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arXiv 1306.6428cs.NI
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基于模型的变点检测技术在Internet控制平面事件识别中的应用

Internet Control Plane Event Identification using Model Based Change Point Detection Techniques

S. P. Meenakshi, S. V. Raghavan

摘要:

随着许多全球组织在印度部署数据中心和内容服务,全球目的地的前缀可达性性能研究引起了我们的关注。互联网拓扑中发生的故障和攻击等事件会影响控制平面中宣布的自治系统(AS)路径以及空间分布AS的前缀可达性。因此,客户对服务的可达性在增加的延迟和短时间或长时间的中断方面经历。控制平面事件检测中的挑战是数据平面流量何时能够正确到达预期目的地。然而,检测此类事件对于内容和数据中心行业的运营至关重要。通过监测AS路径长度分布、空间前缀可达性分布和覆盖重叠路由比等空间分布的路由表特征,可以检测控制平面事件。在我们的工作中,我们研究前缀AS路径从公开的路由视图数据和分析的全球可达性,以及可达印度AS拓扑结构。为了捕捉空间事件在一个单一的时间模式,我们提出了一个基于计数的措施,使用前缀宣布的x %的空间对等体。采用统计特征的变化点检测和时间偏差算法的时间序列的建议措施,我们确定发生的长和随机控制平面事件。事件的影响和持续时间也被量化。我们使用SEA-Me-We 4电缆切断事件在印度AS拓扑的控制平面上的表现形式来验证所提出的措施的机制。考虑对2012年6月6日(长期事件)和2012年4月17日(随机事件)发生的电缆切断事件进行确认。

英文摘要:

In the raise of many global organizations deploying their data centers and content services in India, the prefix reachability performance study from global destinations garners our attention. The events such as failures and attacks occurring in the Internet topology have impact on Autonomous System (AS) paths announced in the control plane and reachability of prefixes from spatially distributed ASes. As a consequence the customer reachability to the services in terms of increased latency and outages for a short or long time are experienced. The challenge in control plane event detection is when the data plane traffic is able to reach the intended destinations correctly. However detection of such events are crucial for the operations of content and data center industries. By monitoring the spatially distributed routing table features like AS path length distributions, spatial prefix reachability distribution and covering to overlap route ratio, we can detect the control plane events. In our work, we study prefix AS paths from the publicly available route-view data and analyze the global reachability as well as reachability to Indian AS topology. To capture the spatial events in a single temporal pattern, we propose a counting based measure using prefixes announced by x % of spatial peers. Employing statistical characteristics change point detection and temporal aberration algorithm on the time series of the proposed measure, we identify the occurrence of long and stochastic control plane events. The impact and duration of the events are also quantified. We validate the mechanisms over the proposed measure using the SEA-Me-We4 cable cut event manifestations in the control plane of Indian AS topology. The cable cut events occurred on 6th June 2012 (long term event) and 17th April 2012 (stochastic event) are considered for validation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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