Multiple Workflow Scheduling Strategies with User Run Time Estimates on a Grid

Hirales-Carbajal, Adán; Tchernykh, Andrei; Yahyapour, Ramin; González-García, José Luis; Röblitz, Thomas; Ramírez-Alcaraz, Juan Manuel

doi:10.1007/s10723-012-9215-6

Cited by 71 publications

(29 citation statements)

References 37 publications

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“…The development of computer technology for large-scale problem solving in grid computing is a rapidly developing area and is presented in the form of a workflow of series-parallel tasks with a specific chart of computing synchronization [25]. The computational tasks are represented in the form of a directed acyclic graph (DAG) [26,27,28,29].…”

Section: Methods and Algorithms For Task Schedulingmentioning

confidence: 99%

Modified Hierarchical Method for Task Scheduling in Grid Systems

AlZubi¹

2017

ijacsa

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Abstract-This study aims to increase the productivity of grid systems by an improved scheduling method. A brief overview and analysis of the main scheduling methods in grid systems are presented. A method for increasing efficiency by optimizing the task graph structure considering the grid system node structure is proposed. Task granularity (the ratio between the amount of computation and transferred data) is considered to increase the efficiency of planning. An analysis of the impact on task scheduling efficiency in a grid system is presented. A correspondence of the task graph structure considering the node structure (in which the task is immersed) to the effectiveness of scheduling in a grid system is shown. A modified method for scheduling tasks while considering their granularity is proposed. The relevant algorithm for task scheduling in a grid system is developed. Simulation of the proposed algorithm using the modeling system GridSim is conducted. A comparative analysis between the modified algorithm and the algorithm of the hierarchical scheduler Maui is shown. The general advantages and disadvantages of the proposed algorithm are discussed.

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Section: Methods and Algorithms For Task Schedulingmentioning

confidence: 99%

Modified Hierarchical Method for Task Scheduling in Grid Systems

AlZubi¹

2017

ijacsa

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“…In the field of Grid computing, Yu et al [7] and HiralesCarbajal et al [8] presented surveys comparing and describing algorithms for scheduling of workflows in Grid computing environments. These algorithms either assume a cooperation model free of financial cost or are based on an economic model that differs from the model adopted by Cloud providers.…”

Section: Related Workmentioning

confidence: 99%

Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replication

Calheiros

Buyya

2014

IEEE Trans. Parallel Distrib. Syst.

205

118

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Abstract-The elasticity of Cloud infrastructures makes them a suitable platform for execution of deadline-constrained workflow applications, because resources available to the application can be dynamically increased to enable application speedup. Existing research in execution of scientific workflows in Clouds either try to minimize the workflow execution time ignoring deadlines and budgets or focus on the minimization of cost while trying to meet the application deadline. However, they implement limited contingency strategies to correct delays caused by underestimation of tasks execution time or fluctuations in the delivered performance of leased public Cloud resources. To mitigate effects of performance variation of resources on soft deadlines of workflow applications, we propose an algorithm that uses idle time of provisioned resources and budget surplus to replicate tasks. Simulation experiments with four well-known scientific workflows show that the proposed algorithm increases the likelihood of deadlines being met and reduces the total execution time of applications as the budget available for replication increases.

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“…The state-of-the-art approaches for executing parameter study workflows show high diversity based on their application area and execution environments. HiralesCarbajal et al [5] present an experimental study of 22 deterministic non-preemptive multiple workflow scheduling strategies in Grids. While their objective is to schedule and execute the whole workflow, and minimize its makespan, we restrict ourselves to parameter study jobs of such workflows.…”

Section: Related Workmentioning

confidence: 99%

A Meta-Brokering Framework for Science Gateways

2016

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Recently scientific communities produce a growing number of computation-intensive applications, which calls for the interoperation of distributed infrastructures including Clouds, Grids and private clusters. The European SHIWA and ER-flow projects have enabled the combination of heterogeneous scientific workflows, and their execution in a large-scale system consisting of multiple Distributed Computing Infrastructures. One of the resource management challenges of these projects is called parameter study job scheduling. A parameter study job of a workflow generally has a large number of input files to be consumed by independent job instances. In this paper we propose a meta-brokering framework for science gateways to support the execution of such workflows. In order to cope with the high uncertainty and unpredictable load of the utilized distributed infrastructures, we introduce the so called resource priority services. These tools are capable of determining and dynamically updating priorities of the available infrastructures to be selected for job instances. Our evaluations show that this approach implies an efficient distribution of job

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Multiple Workflow Scheduling Strategies with User Run Time Estimates on a Grid

Cited by 71 publications

References 37 publications

Modified Hierarchical Method for Task Scheduling in Grid Systems

Modified Hierarchical Method for Task Scheduling in Grid Systems

Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replication

A Meta-Brokering Framework for Science Gateways

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