Sensitivity analysis of a hierarchical model of mobile cloud computing

Matos, Rubens; Araújo, Jean; Oliveira, Danilo; Maciel, Paulo; Trivedi, Kishor S.

doi:10.1016/j.simpat.2014.04.003

Cited by 59 publications

(30 citation statements)

References 9 publications

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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%

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Genetic-variable neighborhood search with thread replication for mobile cloud computing

Singh

2016

International Journal of Parallel, Emergent and Distributed Sys

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The resource-intensive resettlement procedure and inherent restrictions of the wireless medium obstruct the understanding of faultless implementation in mobile cloud computing (MCC) surroundings. In MCC, transfer of thread execution to high end servers allows the processing of those jobs which demand more resources on the mobile equipment. Hence, implementing the application with stumpy cost, least overhead and non-obtrusive relocation is a demanding research area in MCC. Many scheduling mechanisms have been proposed so far to balance the load between the given set of mobile servers, but it is found to be NP-Hard problem. Therefore, evolutionary techniques are required to balance the load among mobile servers. Genetic Algorithm (GA) has been verified to be fine by jumble up the key values, but it becomes unsuccessful to strengthen the exploration in the rising areas. In Variable Neighborhood Search (VNS), local exploration technique is implemented continually to evaluate optimistic outcomes in neighborhood to attain local best solution. But VNS is still prone to premature convergence traps only because of limited search capability. Therefore hybridization with non-global finding techniques may conquer the limitations and guide the dominant search mechanisms to some extent. The GA along with VNS using thread replication (GVNSTR) is implemented to set stability of non-local searching and local utilization for an evolutionary processing period and get the optimized solution.

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Section: Design Of the Gvnstrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genetic-variable neighborhood search with thread replication for mobile cloud computing

Singh

2016

International Journal of Parallel, Emergent and Distributed Sys

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“…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

S_{θ}^{*} (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%

“…36 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. 10 The values for S Â .A/ were calculated with Mercury tool, 37 where A is the system steady-state availability and Â is each of the system parameters (the failure and repair rates of each component). The sensitivity indicators can also be computed with the following equation: With the failure and repair rates of the HW defined as HW and HW , respectively, the corresponding derivative expressions are given in Equations (12) and (13).…”

Section: Parametric Sensitivity Analysismentioning

confidence: 99%

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Availability Evaluation and Sensitivity Analysis of a Mobile Backend‐as‐a‐service Platform

Costa

Araújo

Dantas

et al. 2015

Quality & Reliability Eng

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Performance evaluation of mobile applications has received considerable attention as a prominent activity for improving services quality. Because many data stored on mobile device are synchronized with distributed data centers, the system availability is a critical attribute that requires investigation. Mobile backend‐as‐a‐service (MBaaS) allows developers to link the backend of their applications to cloud storage, as well as providing device management and integration with social networking services. The OpenMobster platform offers a complete synchronization service for mobile applications, but its availability is an inherent critical issue, because one failure can result in losses for companies that use this environment. Analytical models can be used to assess availability of this type of environment and perhaps mitigate downtimes. This paper proposes a hierarchical model to assess the availability of the MBaaS OpenMobster platform focusing on two scenarios: the basic architecture and the automatic recovery process. The designed models were validated through testbed measurements by automatically injecting and repairing the infrastructure. Taking into account the three layers: hardware, operating system, and the MBaaS OpenMobster, we observed OpenMobster being the most critical service component. We have applied failover strategy on the Java virtual machine, and we obtained 10% of reduction in annual downtime. This work may guide systems' administrators in planning their maintenance policies. Copyright © 2015 John Wiley & Sons, Ltd.

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Sensitivity analysis of an availability model for disaster tolerant cloud computing system

et al. 2018

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Because of the dependence on Internet-based services, many efforts have been conceived to mitigate the impact of disasters on service provision. In this context, cloud computing has become an interesting alternative for implementing disaster tolerant services due to its resource on-demand and pay-as-you-go models.This paper proposes a sensitivity analysis approach to assess the parameters that most impact the availability of cloud data centers, taking into account disaster occurrence, hardware and software failures, and disaster recovery mechanisms for cloud systems. The analysis adopts continuous-time Markov chains, and the results indicate that disaster issues should not be neglected. Hardware failure rate and time for migration of virtual machines (VMs) are the critical factors pointed out for the system modeled in our analysis. Moreover, the location where data centers are placed has a significant impact on system availability, due to time for migrating VMs from a backup server.Int J Network Mgmt. 2018;28:e2040.wileyonlinelibrary.com/journal/nem

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Sensitivity analysis of a hierarchical model of mobile cloud computing

Cited by 59 publications

References 9 publications

Genetic-variable neighborhood search with thread replication for mobile cloud computing

Genetic-variable neighborhood search with thread replication for mobile cloud computing

Availability Evaluation and Sensitivity Analysis of a Mobile Backend‐as‐a‐service Platform

Sensitivity analysis of an availability model for disaster tolerant cloud computing system

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