“…Their technique is comparable to Birnbaum significance and they well defined the measures like failure and repair rate based on the system availability. Miman and Pohl (2006) presented a technology called RBD which measures the availability of the component. These works are similar like Cassady et al's (2004) and they considered availability models as two or more states.…”
This paper exhibits a risk-based philosophy in cloud computing to estimate ideal quality and maintenance which maximise the high availability of cloud administration infrastructure. The procedure is confined into two stages: 1) accessibility displaying the cloud; 2) hazard based assessment. The projected procedure is practical to the healthcare scheme using Markov chain process. The proposed system predicts, mitigate and eliminate the risk-based inspection and Markov chain process to efficiently identify the repair and failures of each virtual machine and reduce the energy consumption rate. The result of our proposed method will definitely bound optimum solutions and specifies the conquest of an efficient risk-based availability modelling on minimal cost and energy consumption. Finally, the proposed model is verified by the Nagios and OPTIMIS toolkit. The result obtained in our proposed model definitely bounds optimum solutions and triumph of an efficient risk analysis of failures on minimal cost and energy consumption.
“…Their technique is comparable to Birnbaum significance and they well defined the measures like failure and repair rate based on the system availability. Miman and Pohl (2006) presented a technology called RBD which measures the availability of the component. These works are similar like Cassady et al's (2004) and they considered availability models as two or more states.…”
This paper exhibits a risk-based philosophy in cloud computing to estimate ideal quality and maintenance which maximise the high availability of cloud administration infrastructure. The procedure is confined into two stages: 1) accessibility displaying the cloud; 2) hazard based assessment. The projected procedure is practical to the healthcare scheme using Markov chain process. The proposed system predicts, mitigate and eliminate the risk-based inspection and Markov chain process to efficiently identify the repair and failures of each virtual machine and reduce the energy consumption rate. The result of our proposed method will definitely bound optimum solutions and specifies the conquest of an efficient risk-based availability modelling on minimal cost and energy consumption. Finally, the proposed model is verified by the Nagios and OPTIMIS toolkit. The result obtained in our proposed model definitely bounds optimum solutions and triumph of an efficient risk analysis of failures on minimal cost and energy consumption.
“…Many CIMs have been developed to determine the criticality of individual components to system performance. 17 Primarily, importance measures have been introduced to measure the influence of particular components on the overall reliability of the system. 18,19 Specific CIMs include risk reduction worth (RRW), an index that quantifies the potential damage to a system caused by a particular component failure, and the reliability achievement worth (RAW) of a component, or the maximum proportion increase in system reliability generated by that component.…”
Section: Background and Literature Reviewmentioning
An effective defense strategy requires aircraft, among other weapons systems, to be available and ready for use when circumstances deem necessary. This article offers a set of importance measures to identify the critical components in a system from their influence on system-achieved availability, a common Department of Defense availability calculation that is a ratio of mean time between maintenance and total system time, including mean maintenance time. With these measures, more effective maintenance plans, including inspection and supply inventory, can focus on those components that more significantly impact achieved availability. A decision-making formulation results from these component importance measures, and an example based on a US Air Force system illustrates the modeling contributions.
“…In spite of the large amount of public funds spent on complex assets such as weapons systems, very little research incorporates measures of either cost risk, or readiness risk. Exceptions to this include the work of Miman and Pohl (2006) who examined alternatives for reduction of cost risk, and who examined readiness risk in a post hoc analysis. To our knowledge, no research has examined bi-criteria minimization of Ao and LCC risk, though there is research on the bi-criteria minimization of other types of risk.…”
Section: Silos and Risk In The Public Sectormentioning
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