2015
DOI: 10.1016/j.simpat.2014.04.003
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Sensitivity analysis of a hierarchical model of mobile cloud computing

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Cited by 59 publications
(30 citation statements)
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“…Algo 1 is clearly showing the brief steps of GVNSTR which are required to successfully follow each other inorder to implement the objectives of this paper. algo 1. gVnstr (servers, jobs) 1. first of all, random chromosomes are developed which provides mapping of threads on mobile servers in such a way that thread replication holds, as shown in figure 5 2. evaluate multi-objective function of each chromosome using equations (10) and (11) and assign to obj. 3. apply crossover and mutation operator one by one to develop new chromosomes from random chromosomes.…”
Section: Design Of the Gvnstrmentioning
confidence: 99%
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“…Algo 1 is clearly showing the brief steps of GVNSTR which are required to successfully follow each other inorder to implement the objectives of this paper. algo 1. gVnstr (servers, jobs) 1. first of all, random chromosomes are developed which provides mapping of threads on mobile servers in such a way that thread replication holds, as shown in figure 5 2. evaluate multi-objective function of each chromosome using equations (10) and (11) and assign to obj. 3. apply crossover and mutation operator one by one to develop new chromosomes from random chromosomes.…”
Section: Design Of the Gvnstrmentioning
confidence: 99%
“…MCC is a novel prototype that employs cloud calculated possessions to prevail over the limitations of mobile services. Due to its difficulty, constancy and performance evaluation of mobile servers may necessitate compound replica methods, using dissimilar models for every sub modules and integrating state-dependent and non-state-dependent formalisms [11]. MCC assuage the boundaries of resource-based mobile clouds by leveraging the cloud features.…”
Section: Introductionmentioning
confidence: 99%
“…The goal of sensitivity analysis is to expose performance or availability bottlenecks in the system, thereby providing guidelines for improvement and optimization of the architecture . In relation to analytic models such as Markov chains, parametric sensitivity analysis is a particularly important technique for assessing the effect of alterations in the input parameter constants on the measures of interest . The values for Sθ(A) were calculated with Mercury tool, where A is the system steady‐state availability and θ is each of the system parameters (the failure and repair rates of each component).…”
Section: Experimental Studymentioning
confidence: 99%
“…Matos et al 10 apply hierarchical modeling and different sensitivity analysis techniques to determine the parameters that cause the greatest impact on the availability of a mobile cloud. For this, it was approached the whole domain of an MCC, as mobile client, mobile communication, and cloud infrastructure.…”
Section: Related Workmentioning
confidence: 99%
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