Budget-Deadline Constrained Workflow Planning for Admission Control

Zheng, Wei; Sakellariou, Rizos

doi:10.1007/s10723-013-9257-4

Cited by 127 publications

(66 citation statements)

References 33 publications

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“…The BPSO algorithm represents the trade-off between the execution time and the execution cost under the user's predefined budget and deadline constraints. The proposed scheduling algorithm significantly reduces the execution cost and the makespan through selecting the best-known scheduling solution from the heuristic solutions under the predefined deadline and budget constraints compared to BHEFT (Budgetconstrained Heterogeneous Earliest Finish Time) [31] and PSO algorithms [22,26]. However, the BPSO algorithm does not consider the various loads of the available resources.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

Manasrah

Ali

2018

Wireless Communications and Mobile Computing

180

106

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Cloud computing environment provides several on-demand services and resource sharing for clients. Business processes are managed using the workflow technology over the cloud, which represents one of the challenges in using the resources in an efficient manner due to the dependencies between the tasks. In this paper, a Hybrid GA-PSO algorithm is proposed to allocate tasks to the resources efficiently. The Hybrid GA-PSO algorithm aims to reduce the makespan and the cost and balance the load of the dependent tasks over the heterogonous resources in cloud computing environments. The experiment results show that the GA-PSO algorithm decreases the total execution time of the workflow tasks, in comparison with GA, PSO, HSGA, WSGA, and MTCT algorithms. Furthermore, it reduces the execution cost. In addition, it improves the load balancing of the workflow application over the available resources. Finally, the obtained results also proved that the proposed algorithm converges to optimal solutions faster and with higher quality compared to other algorithms.

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Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

Manasrah

Ali

2018

Wireless Communications and Mobile Computing

180

106

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“…Wei Zheng et al [6] 'Budget-Deadline Constrained Workflow Planning used for Admission Control for Bi-criteria DAG scheduling'…”

Section: Authormentioning

confidence: 99%

List Scheduling Algorithms Classification: An Analytical Study

Akanksha¹

2018

ijarcs

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Multiprocessor scheduling is another name of task scheduling in form of algorithms that are mostly utilized in systematic as well as engineering appliance that is also known as the issue of NP-complete. The main aim of scheduling is the reduction of execution time. The illustration of task scheduling for multiprocessor scheduling is shown by DAG (Directed Acyclic graph). The categorization for this is into Static as well as dynamic scheduling. The list task scheduling is the example of static task scheduling algorithm. Varied task scheduling algorithms, like ISH, HLFET, MCP, ETF, CNPT and DLS are reviewed in this paper. The comparison of list task scheduling isdependent on metrics, termed as SLR, load balancing, efficiency and speed up.

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“…Recently, Zheng and Sakellariou [29] proposed budget and deadline constrained, BHEFT, which is the extension of HEFT algorithm that gives Budget and Deadline Constrained (BDC) plan to check whether a workflow request should be accepted or not while considering the confirmed resource reservations from the other users. During creation of a BDC plan, the authors considered the spare budget for each task of workflow while selecting the resource.…”

Section: Related Workmentioning

confidence: 99%

“…From these variables, SWB, CTB and BAF are same as defined in [29] and SWD, CTD, and DAF are proposed by us. For a task t i , the value of these variables is given by (8) to (13), as follows:…”

Section: Spare Workflow Budget (Swb) Spare Workflow Deadline (Swd) mentioning

confidence: 99%

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Cost-Time Efficient Scheduling Plan for Executing Workflows in the Cloud

Verma

Kaushal

2015

J Grid Computing

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The emergence of Cloud Computing as a model of service provisioning in distributed systems instigated researchers to explore its pros and cons on executing different large scale scientific applications, i.e., Workflows. One of the most challenging problems in clouds is to execute workflows while minimizing the execution time as well as cost incurred by using a set of heterogeneous resources over the cloud simultaneously. In this paper, we present, Budget and Deadline Constrained Heuristic based upon Heterogeneous Earliest Finish Time (HEFT) to schedule workflow tasks over the available cloud resources. The proposed heuristic presents a beneficial trade-off between execution time and execution cost under given constraints. The proposed heuristic is evaluated for different synthetic workflow applications by a simulation process and comparison is done with state-of-art algorithm i.e. BHEFT. The simulation results show that our proposed scheduling heuristic can significantly decrease the execution cost while producing makespan as good as the best known scheduling heuristic under the same deadline and budget constraints.A. Verma ( ) · S. Kaushal

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Budget-Deadline Constrained Workflow Planning for Admission Control

Cited by 127 publications

References 33 publications

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

Workflow Scheduling Using Hybrid GA‐PSO Algorithm in Cloud Computing

List Scheduling Algorithms Classification: An Analytical Study

Cost-Time Efficient Scheduling Plan for Executing Workflows in the Cloud

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