Cost-Minimizing Scheduling of Workflows on a Cloud of Memory Managed Multicore Machines

Grounds, Nicolas G.; Antonio, John K.; Muehring, Jeff

doi:10.1007/978-3-642-10665-1_40

Cited by 23 publications

(18 citation statements)

References 12 publications

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“…The scheduler needs to allocate the workload to available resources, while dynamically balancing the workload [88]. Consequently, it helps in maximum resource utilization, which results in improving the overall system performance [3,18,72,96,97]. However, the scheduler also needs to consider all QoS constraints as requested by the cloud users [40].…”

Section: Load Balancingmentioning

confidence: 98%

“…However, SLA usually defines cost penalties when the terms for SLA are violated (e.g. a deadline is missed) [72].…”

Section: Service Level Agreement (Sla)mentioning

confidence: 99%

“…Cost-Minimizing Scheduling Algorithm (CMSA) [72] Workflow requirements are allocated based on Service-Oriented Architecture to be managed by the multicore machines memory for execution. Implementation is feasible for mapping requirements of multilevel workflows with various complication levels, to minimize the overall execution cost.…”

Section: Market-orientedmentioning

confidence: 99%

“…The time required for all workflow computations is defined as the workflow deadline [5,62,72,86]. In most cases, users only specify a deadline for the entire workflow execution [73].…”

Section: Deadlinementioning

confidence: 99%

See 3 more Smart Citations

Cost-aware challenges for workflow scheduling approaches in cloud computing environments: Taxonomy and opportunities

Alkhanak

Lee

Khan

2015

Future Generation Computer Systems

140

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Section: Load Balancingmentioning

confidence: 98%

“…However, SLA usually defines cost penalties when the terms for SLA are violated (e.g. a deadline is missed) [72].…”

Section: Service Level Agreement (Sla)mentioning

confidence: 99%

Section: Market-orientedmentioning

confidence: 99%

“…The time required for all workflow computations is defined as the workflow deadline [5,62,72,86]. In most cases, users only specify a deadline for the entire workflow execution [73].…”

Section: Deadlinementioning

confidence: 99%

See 2 more Smart Citations

Cost-aware challenges for workflow scheduling approaches in cloud computing environments: Taxonomy and opportunities

Alkhanak

Lee

Khan

2015

Future Generation Computer Systems

140

View full text Add to dashboard Cite

“…So cost can be minimized by scheduling these workflows on the cloud. Several researches have been conducted on scheduling workflows on cloud for cost minimization [36], [37]. Several scheduling algorithms [47]- [52] have already been implemented in this area.…”

Section: Scheduling Of Workflows On a Cloudmentioning

confidence: 99%

D2i2D: A Novel Secure Approach for Cloud Storage with Cost Minimization

Saha¹,

Ali²

2016

JSW

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Nowadays Cloud computing has made a revolutionary change in the concept of computation on the web. It has been able to provide low cost services to its users all over the world. Millions of users are using the service of cloud either by IaaS, PaaS and SaaS. Now the main concern of cloud service providers and users how to preserve security in these low cost services. Throughout this research we have first reviewed some cost minimization technique and data security approaches used in the cloud. Then we propose a novel data hiding approach called 'D2i2D' which is able to provide security to any data stored in the cloud as well as reduce the file size in cloud storage. Our technique is based on data to RGB image and RGB image to data conversion technique with multiple-key-cryptography (MKC) to provide more security on cloud data. We have been able to show that this technique is able to reduce 38.82% of storage where file size is less than 1 MB and 30.34% of storage where file size is within 1 to 2 MB. Lastly we propose a framework to implement this technique in cloud.

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Bandwidth‐aware divisible task scheduling for cloud computing

et al. 2012

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SUMMARYTask scheduling is a fundamental issue in achieving high efficiency in cloud computing. However, it is a big challenge for efficient scheduling algorithm design and implementation (as general scheduling problem is NP-complete). Most existing task-scheduling methods of cloud computing only consider task resource requirements for CPU and memory, without considering bandwidth requirements. In order to obtain better performance, in this paper, we propose a bandwidth-aware algorithm for divisible task scheduling in cloudcomputing environments. A nonlinear programming model for the divisible task-scheduling problem under the bounded multi-port model is presented. By solving this model, the optimized allocation scheme that determines proper number of tasks assigned to each virtual resource node is obtained. On the basis of the optimized allocation scheme, a heuristic algorithm for divisible load scheduling, called bandwidth-aware task-scheduling (BATS) algorithm, is proposed. The performance of algorithm is evaluated using CloudSim toolkit. Experimental result shows that, compared with the fair-based task-scheduling algorithm, the bandwidthonly task-scheduling algorithm, and the computation-only task-scheduling algorithm, the proposed algorithm (BATS) has better performance.

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Cost-Minimizing Scheduling of Workflows on a Cloud of Memory Managed Multicore Machines

Cited by 23 publications

References 12 publications

Cost-aware challenges for workflow scheduling approaches in cloud computing environments: Taxonomy and opportunities

Cost-aware challenges for workflow scheduling approaches in cloud computing environments: Taxonomy and opportunities

D2i2D: A Novel Secure Approach for Cloud Storage with Cost Minimization

Bandwidth‐aware divisible task scheduling for cloud computing

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