An approach to evaluate the availability of system in cloud computing using fault tree technique

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Abstract

The Fault tree furnishes an engraving and analytical structure to dissect the dependability of systems. A fault tree gives an abstractly essential demonstrating schema to embody the level of system communications among all the component reliabilities in cloud computing environment. Fault tree Investigation is that fundamental technique which concentrates on failure modes for whatever system and the probabilities for occurrence/ likelihood risk dissection connected with it. Fault Tree Analysis signifies to significant deficiency or critical failures connected to the system and reasons for the faults graphically. Here we will realise that likelihood from claiming the failure of the primary event with that assistance about which we get that probability of failure of the top event. Dynamic fault trees include a progressive thought of the conventional issue tree tactic: system failures might rely on component failure. Exceptional motivation dynamic fault tree gates can model gradual supplanting of neglected segments. Starting with pools from claiming spares, failures that happen just if others happen for certain orders, dependencies that propagate failure, also circumstances the place failures could happen best to a predefined request. With the help of the dynamic gates, the fault trees need to be tackled by automatic change with proportional Markov models regularly in a cloud environment. The proposed system uses fault tree analysis and Markov chain process to efficiently identify the repair and failures of each virtual machine and reduces the energy consumption rate and cost accordingly. The result obtained in our proposed model definitely bounds optimum solutions and deceptively specifies the triumph of an efficient fault tree analysis of failures on minimal cost and energy consumption.

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APA

Mani, D., & Mahendran, A. (2017). An approach to evaluate the availability of system in cloud computing using fault tree technique. International Journal of Intelligent Engineering and Systems, 10(4), 245–255. https://doi.org/10.22266/ijies2017.0831.26

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