Efficient resource arbitration and allocation strategies in cloud computing through virtualization

Nair, T. R. Gopalakrishnan; Vaidehi, M.

doi:10.1109/ccis.2011.6045097

Cited by 13 publications

(8 citation statements)

References 3 publications

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“…It is observed from the graph that the jobs are classified and assigned priority ranging from 0, 0.1…..1, the job with priority "1" implies that it is provisioned a larger resource based on its request, there is maximum utilization. This Classification technique prevents the under utilization and over utilization of the resources [9].…”

Section: Simulations and Results Analysismentioning

confidence: 99%

An Efficient Job Classification Technique to Enhance Scheduling in Cloud to Accelerate the Performance

Vaidehi

Nair

Suma

2014

ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I

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Abstract.As cloud computing is becoming more ubiquitous with increasing espousal of advanced technologies, more and more efficient techniques are required to enhance the system performance. The computing systems in the cloud comprise heterogeneity of components or resources. Challenge here is efficient scheduling and resource allocation to jobs requesting the computing devices in order to achieve customer satisfaction. Retention of customer satisfaction is one of the primary factors for an organization to exist. To achieve the aforementioned goal, it is required to implement the principles of software engineering in every task that is accomplished in the organization. Thus, with organizations marching towards cloud environment, the jobs are initially clustered or grouped and subsequently scheduled for the resource arbitration and allocation. This paper focuses on clustering or grouping of jobs. The unsupervised technique or the clustering of the jobs is done based on the logistic regression approach. As this approach is more robust and the parameters considered for classification are more independent, simulation evidence suggests the classification technique cluster the jobs more effectively and provide a consistent utilization of the available resources. This ensures that the non functional requirement of availability of jobs to their customers is achieved thereby enhancing the business performance.

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Section: Simulations and Results Analysismentioning

confidence: 99%

An Efficient Job Classification Technique to Enhance Scheduling in Cloud to Accelerate the Performance

Vaidehi

Nair

Suma

2014

ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I

Self Cite

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“…Fault-tolerance techniques such as fault recovery is one of the techniques that can be employed to improve reliability. It employs checkpoint and rollback/roll-forward scheme, that enables a resource to recover from an error and resume execution [14]. In this paper, we investigate the problem of resource provisioning in hybrid Clouds considering the probability of resource failure during job execution.…”

Section: A Our Contributionmentioning

confidence: 99%

“…Their approach seeks to maximize the profit of the SaaS provider by minimizing the number of SLA violations and the cost by reusing VMs. Other related works [9], [11], [12], [13] and [14] also focused on cost-optimization strategies for resource provisioning. This paper is also focused on cost optimization and also consider workloads that are dynamic in nature.…”

Section: Related Workmentioning

confidence: 99%

Fault-Tolerant Resource Provisioning with Deadline-Driven Optimization in Hybrid Clouds

Ahene¹,

Acheampong²,

Xu³

2016

ijacsa

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Abstract-Resource provisioning remains as one of the challenging research problems in cloud computing, more importantly when considered together with service reliability. Fault-tolerance techniques such as fault-recovery is one of the techniques that can be employed to improve on service reliability. Technically, fault-recovery has obvious impact on service performance. Such impact requires detailed studies. Only few works on hybrid cloud resource provisioning address fault recovery and its impact. In this paper, we investigate the problem of resource provisioning in hybrid Clouds, considering the probability of hybrid cloud resource failure during job execution. We formulate this problem as an optimization model with operational cost as an objective function subject to the deadline constraint of jobs. Based on our proposed optimization model, we design a heuristic-based algorithm called dynamic resource provisioning algorithm (DRPA). We then perform extensive experiments to evaluate performance of the proposed algorithm based on a real world set of data. The results confirm the obvious impact of fault recovery on the performance metrics (operational cost and deadline violation rate) and also confirms that DRPA can be useful in minimizing operational cost.

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“…It could also be seen as any mechanism that aims to guarantee that the applications' requirements as stated in the SLA are attended to correctly by the provider's infrastructure. Resource allocation is defined as the process of integrating cloud provider activities for utilizing and allocation scarce resources, which may seem unlimited to users, within the limit of cloud environment so as to meet the needs of the cloud application in an elastic and transparent manner [13] [14] [15]. Resource allocation strategies help the two major players (users and service providers) in cloud computing to achieve their goals.…”

Section: Resource Allocationmentioning

confidence: 99%

SURVEY ON DYNAMIC RESOURCE ALLOCATION STRATEGIES (RAS) & CONTENTION MANAGEMENT IN CLOUD COMPUTING ENVIRONMENT

2015

IJAERD

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Efficient resource arbitration and allocation strategies in cloud computing through virtualization

Cited by 13 publications

References 3 publications

An Efficient Job Classification Technique to Enhance Scheduling in Cloud to Accelerate the Performance

An Efficient Job Classification Technique to Enhance Scheduling in Cloud to Accelerate the Performance

Fault-Tolerant Resource Provisioning with Deadline-Driven Optimization in Hybrid Clouds

SURVEY ON DYNAMIC RESOURCE ALLOCATION STRATEGIES (RAS) & CONTENTION MANAGEMENT IN CLOUD COMPUTING ENVIRONMENT

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