  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.
