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Process-oriented non-intrusive recovery for sporadic operations on cloud


Min Fu, Liming Zhu, Ingo Weber, Len Bass, Anna Liu and Sherry Xu




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 platform. 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 X-Recovery. X-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. X-Recovery employs an efficient technique from artificial intelligence (AI) planning for generating recovery plans. We implement X-Recovery and evaluate it by recovering from faults injected into a total of 920 runs of five representative sporadic operations.

BibTeX Entry

    author           = {Fu, Min and Zhu, Liming and Weber, Ingo and Bass, Len and Liu, Anna and Xu, Xiwei (Sherry)},
    month            = jul,
    year             = {2016},
    keywords         = {software reliability; cloud; non-intrusive recovery; log analysis; devops},
    address          = {Toulouse, France},
    title            = {Process-Oriented Non-Intrusive Recovery for Sporadic Operations on Cloud},
    booktitle        = {DSN 2016}


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