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首页> 外文期刊>The Journal of Systems and Software >Automatic retrieval and analysis of high availability scenarios from system execution traces: A case study on hot standby router protocol
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Automatic retrieval and analysis of high availability scenarios from system execution traces: A case study on hot standby router protocol

机译:从系统执行轨迹中自动检索和分析高可用性方案:热备用路由器协议的案例研究

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摘要

High availability (HA) is becoming an increasingly important requirement in a growing number of domains. It is even mandatory for critical systems, such as networking and communications, that cannot afford downtime. Such systems often monitor the state of crucial services and produce huge amounts of execution trace data, where functional and non-functional log entries are intertwined; hence they are hard to dissociate and analyze. Dynamic analysis aims at capturing and analyzing run-time behavior of a system based on its execution traces. In this paper, we apply dynamic analysis to retrieve and analyze HA scenarios from system execution traces. Our proposed approach aims to help analysts understand and report on how a highly available system detects and recovers from failures. As a proof of concept, we have selected the Hot Standby Router Protocol (HSRP) in order to demonstrate the applicability of our approach. We have evaluated empirically the effectiveness of our technique using four real-world case studies of IP networks running HSRP. Results have shown that high availability scenarios were successfully retrieved and analyzed. Moreover, results have shown that our prototype tool HAAnalyzer was able to effectively unveil high availability behavioral and temporal errors, that were seeded in the execution traces.
机译:在越来越多的域中,高可用性(HA)变得越来越重要。对于无法承受停机时间的关键系统,例如网络和通信,甚至是强制性的。这样的系统通常监视关键服务的状态并产生大量执行跟踪数据,功能和非功能日志条目交织在一起。因此,它们很难分离和分析。动态分析旨在基于系统的执行跟踪来捕获和分析系统的运行时行为。在本文中,我们应用动态分析从系统执行跟踪中检索和分析HA方案。我们提出的方法旨在帮助分析人员了解和报告高可用性系统如何检测故障并从故障中恢复。作为概念验证,我们选择了热备路由器协议(HSRP),以证明我们的方法的适用性。我们使用运行HSRP的IP网络的四个实际案例,通过经验评估了我们技术的有效性。结果表明,成功检索和分析了高可用性方案。此外,结果表明,我们的原型工具HAAnalyzer能够有效地揭露植入执行轨迹中的高可用性行为和时间错误。

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