A Bandwidth-Aware Job Grouping-Based Scheduling on Grid Environment

Ang, Tan Fong; Ng, Willie; Ling, Teck Chaw; Por, Lip Yee; Liew, Chee Sun

doi:10.3923/itj.2009.372.377

Cited by 32 publications

(24 citation statements)

References 5 publications

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“…The authors in [12,13] grouped the tasks based on resource's Million Instructions Per Second (MIPS) and task's Million Instructions (MI); e.g. for utilising a resource with 500 MIPS for 3 seconds, tasks were grouped into a single task file until the maximum MI of the file was 1500.…”

Section: Related Workmentioning

confidence: 99%

Batch Resizing Policies and Techniques for Fine-Grain Grid Tasks: The Nuts and Bolts

Muthuvelu¹,

Chai²,

Eswaran³

et al. 2011

Journal of Information Processing Systems

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Abstract-The overhead of processing fine-grain tasks on a grid induces the need for batch processing or task group deployment in order to minimise overall application turnaround time. When deciding the granularity of a batch, the processing requirements of each task should be considered as well as the utilisation constraints of the interconnecting network and the designated resources. However, the dynamic nature of a grid requires the batch size to be adaptable to the latest grid status. In this paper, we describe the policies and the specific techniques involved in the batch resizing process. We explain the nuts and bolts of these techniques in order to maximise the resulting benefits of batch processing. We conduct experiments to determine the nature of the policies and techniques in response to a real grid environment. The techniques are further investigated to highlight the important parameters for obtaining the appropriate task granularity for a grid resource.

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Section: Related Workmentioning

confidence: 99%

Batch Resizing Policies and Techniques for Fine-Grain Grid Tasks: The Nuts and Bolts

Muthuvelu¹,

Chai²,

Eswaran³

et al. 2011

Journal of Information Processing Systems

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“…First is grouping strategies does not utilize resource sufficiently, and second, consideration of bandwidth strategy is not efficient to transfer the job. T.F.Ang et al presents Bandwidth-Aware Job Grouping-Based scheduling strategy, that groups the jobs according to the MIPS and bandwidth of resources, but shortcomings of the algorithm is first, the model sends group jobs to the resource whose network bandwidth has highest communication or transmission rate, but the algorithm does not ensure that resource having a sufficient bandwidth will be able to transfer the group jobs within required time [7]. In [8], Muthuvelu et al proposed a dynamic job groupingbased scheduling algorithm that groups the jobs according to MIPS of the available resources.…”

Section: Related Workmentioning

confidence: 99%

Cost-based Job grouping and Scheduling Algorithm for Grid computing Environments

Yadav¹,

Agarwal²,

Rastogi³

2014

IJCA

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The integration of remote and diverse resources and the increasing computational needs of Grand challenges problems combined with faster growth of the internet and communication technologies leads to the development of global computational grids. Grid computing is a prevailing technology, which unites underutilized resources in order to support sharing of resources and services distributed across numerous administrative region. An efficient and effective scheduling system is essentially required in order to achieve the promising capacity of grids. The main goal of scheduling is to maximize the resource utilization and minimize processing time and cost of the jobs. In this research, the objective is to prioritize the jobs based on execution cost and then allocate over the resources with minimum cost by merging it with conventional job grouping strategy to provide solution for better and more efficient job scheduling which is beneficial to both user and resource broker. The proposed scheduling approach in grid computing employs a dynamic cost-based job scheduling algorithm for making efficient mapping of job to available resources in grid. It also improves communication to computation ratio (CCR) and utilization of available resources by grouping the user jobs before resource allocation. General TermsAlgorithm, GridSim.

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“…A matchmaking strategy that base on job execution time was proposed for resource allocation in [16]. Goudarzi, H. et al, Hien Nguyen, V. et al, and Ang Tan Fong et al proposed the SLA-Based resource allocation that mainly focus on the number and type of computing, data storage and communication resources [17][18][19][20]. The utility based resource allocation strategy that maximize the service providers profit was proposed by Goudarzi, H. et al and Minarolli, D. et al [21][22].…”

Section: Related Workmentioning

confidence: 99%

“…There exist quite a number of researches that enhanced the research allocation in cloud [16][17][18][19][20][21][22][23]. A matchmaking strategy that base on job execution time was proposed for resource allocation in [16].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Pricing Scheme for Resource Allocation in Multi-Cloud Environment

Shaari

Ang

Por

et al. 2017

MJCS

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Cloud computing has taken the IT and business world by storm through its cost savings and quick-and-easy adoption. Currently, fixed price model is dominating the pricing schemes in the cloud market. However, this model is unable to reflect the current market needs for cost savings as the number of cloud provider and user increases. As a result, a dynamic pricing scheme has emerged as an attractive strategy to better cope with the unpredictable cloud demand. This paper proposed a dynamic pricing scheme that provides fairness among the service providers in a multi-cloud environment. The scheme adjusts the price accordingly to encourage the low utilized resources' usage and discourage over utilized resources' usage. The evaluation results showed that the proposed scheme is able to reduce the cost of the end user when running compute-intensive and data-intensive jobs in the multi-cloud environment.

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A Bandwidth-Aware Job Grouping-Based Scheduling on Grid Environment

Cited by 32 publications

References 5 publications

Batch Resizing Policies and Techniques for Fine-Grain Grid Tasks: The Nuts and Bolts

Batch Resizing Policies and Techniques for Fine-Grain Grid Tasks: The Nuts and Bolts

Cost-based Job grouping and Scheduling Algorithm for Grid computing Environments

Dynamic Pricing Scheme for Resource Allocation in Multi-Cloud Environment

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