Optimizing Resource Allocation for Scientific Workflows Using Advance Reservations

Langguth, Christoph; Schuldt, Heiko

doi:10.1007/978-3-642-13818-8_30

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…In Russell et al [2005], a novel framework of resource patterns for workflow resource management is proposed. Some approaches such as Ashraf and Erlebach [2010], Decker and Schneider [2007], and Langguth and Schuldt [2010] consider resource reservation when scheduling the workflow/business processes. In contrast, the second category is to plan resource for certain number of workflow instances at the build time.…”

Section: Related Workmentioning

confidence: 99%

“…Another category is workflow scheduling/planning, which considers the workflow structure in resource allocation. Yu et al in Yu and Buyya [2005] compared some significant workflow scheduling algorithms and systems [Ashraf and Erlebach 2010;Decker and Schneider 2007;Langguth and Schuldt 2010;Senkul and Toroslu 2005;Yarkhan and Dongarra 2002;Yu and Buyya 2006] under the Grid environment. These approaches mainly deal with the run-time workflow scheduling problems.…”

Section: Introductionmentioning

confidence: 99%

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Resource Management for Business Process Scheduling in the Presence of Availability Constraints

Liu

Zhao

et al. 2016

ACM Trans. Manage. Inf. Syst.

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In the context of business process management, the resources required by business processes, such as workshop staff, manufacturing machines, etc., tend to follow certain availability patterns, due to maintenance cycles, work shifts and other factors. Such availability patterns heavily influence the efficiency and effectiveness of enterprise resource management. Most existing process scheduling and resource management approaches tend to tune the process structure to seek better resource utilisation, yet neglect the constraints on resource availability. In this article, we investigate the scheduling of business process instances in accordance with resource availability patterns, to find out how enterprise resources can be rationally and sufficiently used. Three heuristic-based planning strategies are proposed to maximise the process instance throughput together with another strategy based on a genetic algorithm. The performance of these strategies has been evaluated by conducting experiments of different settings and analysing the strategy characteristics.

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