工作流即服务云平台及生物信息学工作流应用部署
Workflow-as-a-Service Cloud Platform and Deployment of Bioinformatics Workflow Applications
摘要：
工作流管理系统（WMS）支持在分布式计算环境中组合和部署面向工作流的应用程序。它们隐藏了管理大规模应用程序的复杂性，包括控制任务之间的数据流水线，确保应用程序的执行，以及编排分布式计算资源以获得合理的处理时间。随着科学工作流采用趋势的增加，使用第三方服务部署它们的需求开始增加。工作流即服务（WaaS）是一个术语，代表为需要在第三方云管理服务上部署工作流应用程序的用户提供服务的平台。这一概念推动现有的WMS技术向WaaS云平台发展。基于这一需求，我们扩展了CloudBus WMS功能，以处理多个工作流的工作负载，并开发了WaaS云平台原型。我们实现了弹性预算约束的多工作流资源配置和调度算法（EBPSM）算法，该算法能够调度多个工作流，并使用两个生物信息学工作流对平台进行了评估。我们的实验结果表明，该平台是能够有效地处理多个工作流的执行，并获得其目的，以最大限度地减少完工时间，同时满足预算。
英文摘要：
Workflow management systems (WMS) support the composition and deployment of workflow-oriented applications in distributed computing environments. They hide the complexity of managing large-scale applications, which includes the controlling data pipelining between tasks, ensuring the application's execution, and orchestrating the distributed computational resources to get a reasonable processing time. With the increasing trends of scientific workflow adoption, the demand to deploy them using a third-party service begins to increase. Workflow-as-a-service (WaaS) is a term representing the platform that serves the users who require to deploy their workflow applications on third-party cloud-managed services. This concept drives the existing WMS technology to evolve towards the development of the WaaS cloud platform. Based on this requirement, we extend CloudBus WMS functionality to handle the workload of multiple workflows and develop the WaaS cloud platform prototype. We implemented the Elastic Budget-constrained resource Provisioning and Scheduling algorithm for Multiple workflows (EBPSM) algorithm that is capable of scheduling multiple workflows and evaluated the platform using two bioinformatics workflows. Our experimental results show that the platform is capable of efficiently handling multiple workflows execution and gaining its purpose to minimize the makespan while meeting the budget.
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