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  • 标题:Quantitative evaluation of fault propagation in a commercial cloud system
  • 本地全文:下载
  • 作者:Chao Wang ; Zhongchuan Fu
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2020
  • 卷号:16
  • 期号:3
  • 页码:1
  • DOI:10.1177/1550147720903613
  • 出版社:Hindawi Publishing Corporation
  • 摘要:As semiconductor technology scales into the nano regime, hardware faults have been threats against computational devices. Cloud systems are incorporating more and more computing density and energy into themselves; thus, fundamental research on topics such as dependability validation is needed, in order to verify the robustness of clouds for sensor networks. However, dependability evaluation studies have often been carried out beyond isolated physical systems, such as processors, sensors, and single boards with or without operating system hosts. These studies have been performed using inaccurate simulations instead of validating complete cloud software stacks (firmware, hypervisor, operating system hosts and workloads) as a whole. In this article, we describe the implementation of a fault injection tool, which validates the dependability of a commercial cloud software stack. Hardware faults induced by high energy density environments can be injected; the fault propagation through the cloud software stack is traced, and quantitatively evaluated. Experimental results show that the integrated fault detection mechanism of the cloud system, such as fatal trap detectors, has left a detection margin of 20% silent data corruption to narrow down. We additionally propose two detection mechanisms, which proved good performance in fault detection of cloud systems.
  • 关键词:Cloud computing; dependability evaluation; fault injection; cross-layer resilience; intermittent fault
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