Resource-sharing Policy in Multi-tenant Scientific Workflow-as-a-Service Cloud Platform

Increased adoption of scientific workflows in the community has urged for the development of multi-tenant platforms that provide these workflow executions as a service. As a result, Workflow-as-a-Service (WaaS) concept has been created by researchers to address the future design of Workflow Management Systems (WMS) that can serve a large number of users from a single point of service. These platforms differ from traditional WMS in that they handle a workload of workflows at runtime. A traditional WMS is usually designed to execute a single workflow in a dedicated process while WaaS cloud platforms enhance the process by exploiting multiple workflows execution in a multi-tenant environment model. In this paper, we explore a novel resource-sharing policy to improve system utilization and to fulfil various Quality of Service (QoS) requirements from multiple users in WaaS cloud platforms. We propose an Elastic Budget-constrained resource Provisioning and Scheduling algorithm for Multiple workflows that can reduce the computational overhead by encouraging resource sharing to minimize workflows' makespan while meeting a user-defined budget. Our experiments show that the EBPSM algorithm can utilize the resource-sharing policy to achieve higher performance in terms of minimizing the makespan compared to the state-of-the-art budget-constraint scheduling algorithm.