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Scheduling with Deadline Constraint of Healthcare Applications on Cloud-Based Workflow

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Cloud-based workflow technology has played an important role in the development of large scale healthcare applications with high flexibility to meet variety of healthcare process requirements. Among all the factors affecting the healthcare applications on cloud-based workflow, the tasks scheduling is the crucial one. This paper aims at the cloud-based workflow tasks scheduling with deadline constraints and its implementation in two approaches: heuristic scheduling algorithm (HSA) and meta heuristic scheduling algorithm (HSA-ACO). HSA decomposes the workflow according to its structure and divide the deadline into the level deadlines. Tasks in each level get scheduling priority according to the earliest start time under the constraint of level deadline. In another method, HSA-ACO integrates HSA with ant colony algorithm to achieve better performance. In the last part, we launch the experiment to compare HSA and HSA-ACO with algorithms like Prolis, LACO and ICPCP in three types of workflow with different scales. The experiment results show that HSA-ACO is better than the other algorithms.

Keywords: CLOUD COMPUTING; HSA; HSA-ACO; WORKFLOW SCHEDULING

Document Type: Research Article

Publication date: 01 October 2020

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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