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Component Importance Analysis of Mobile Cloud Computing System in the Presence of Common-Cause Failures
Author(s) -
Junjun Zheng,
Hiroyuki Okamura,
Tadashi Dohi
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2822338
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
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.

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