Process-Oriented Non-intrusive Recovery for Sporadic Operations on Cloud

2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) Pub Date : 2016-06-01 DOI:10.1109/DSN.2016.17

Min Fu, Liming Zhu, I. Weber, L. Bass, Anna Liu, Xiwei Xu

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引用次数: 2

Abstract

Cloud-based systems get changed more frequently than traditional systems. These frequent changes involve sporadic operations such as installation and upgrade. Sporadic operations may fail due to the uncertainty of cloud platforms. Each sporadic operation manipulates a number of cloud resources. The accessibility of resources manipulated makes it possible to build an accurate process model of the correct behavior for an operation and its desired effects. This paper proposes a non-intrusive recovery approach for sporadic operations on cloud, called POD-Recovery. POD-Recovery utilizes the above-mentioned process model of the operation. When needed, it triggers recovery actions based on the model through non-intrusive means, i.e., without modifying the code which implements the sporadic operation. POD-Recovery employs an efficient artificial intelligence (AI) planning technique for generating recovery plans. We implement POD-Recovery and evaluate it by recovering from faults injected into 920 runs of five representative sporadic operations.

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面向流程的非侵入式云上零星操作恢复

基于云计算的系统比传统系统变化更频繁。这些频繁的更改涉及零星的操作，例如安装和升级。由于云平台的不确定性，可能导致零星的操作失败。每个零星操作都要操作许多云资源。操作资源的可访问性使得为操作及其预期效果构建正确行为的准确流程模型成为可能。本文提出了一种针对云上零星操作的非侵入式恢复方法，称为POD-Recovery。POD-Recovery利用了上述操作过程模型。当需要时，它通过非侵入性的方式触发基于模型的恢复操作，即不修改实现零星操作的代码。POD-Recovery采用高效的人工智能(AI)规划技术来生成恢复计划。我们实现了POD-Recovery，并通过对5个有代表性的零星操作的920次运行中注入的故障进行恢复来评估它。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)

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