Component Importance Analysis of Mobile Cloud Computing System in the Presence of Common-Cause Failures

IEEE Access

Junjun Zheng¹  Hiroyuki Okamura²  Tadashi Dohi² 

[1] Department of Computer Science, Ritsumeikan University, Kusatsu, Japan;Department of Information Engineering, Hiroshima University, Higashihiroshima, Japan;

关键词: Mobile cloud computing;    component importance analysis;    parametric sensitivity;    common-cause failure;    continuous-time Markov chain;   

DOI  :  10.1109/ACCESS.2018.2822338

来源: DOAJ

【 摘 要 】

Mobile cloud computing (MCC) is a state-of-the-art architecture that integrates the cloud computing into the mobile environment and overcomes obstacles, such as processing capability, battery life, storage, and availability. Also the MCC is expected to be a key technology for cyber physical systems by connecting to vehicular systems, medical systems, and other mission-critical systems. Therefore, it is a critical issue for MCC to guarantee the high reliability. In this paper, we consider the component importance analysis of an MCC with common-cause failures (CCFs) by using a Markov reward modelbased componentwise sensitivity approach. The component importance analysis is capable of quantifying the criticality of components and helps us to design the highly reliable system. In particular, this paper examines the effect of CCFs on the MCC. Our experimental results show that the preferred action to improve the availability of system with CCFs efficiently is to decrease the failure rate of the cloud node in the cloud infrastructure.

【 授权许可】

Unknown