QoS-Oriented Cloud Workflow Engine
Infrastructure-as-a-Service (IaaS) clouds offer several advantages for the deployment of scientific workflows. They enable Workflow Management Systems (WMSs) to access a flexible and scalable infrastructure by leasing Virtual Machines (VMs). This allows workflows to be easily packaged and deployed and more importantly, enables WMSs to access a virtually infinite pool of VMs that can be elastically acquired and released and are charged on a pay-per-use basis. In this way, cloud resources can be used opportunistically based on the number and type of tasks that need to be processed at a given point in time. This is a convenient feature as it is common for the task parallelism of scientific workflows to significantly change throughout their execution. The resource pool can be scaled out and in to adjust the number of resources as the execution of the workflow progresses. This facilitates the fulfilment of the quality-of-service (QoS) requirements by allowing WMSs to fine-tune performance while ensuring the available resources are efficiently used.
In this project we extend the Cloudbus WMS as a PaaS (Platform-as-a-Service) to support the cloud-computing paradigm. Specifically, the project aims to:
· Define an architectural framework and principles for the development of QoS-based workflow management in cloud environments,
· Develop QoS-based algorithms for scheduling scientific workflow applications,
· Develop policies and resource management algorithms tailored for the cloud resource model,
· Implement a prototype system by incorporating the algorithms and policies developed above, and
· Develop real world demonstrators in various scientific domains such as astronomy.
Leader: Rajkumar Buyya
Cloud Computing and Distributed Systems (CLOUDS) Laboratory
Computing and Information Systems
Networks and data in society, Optimisation of resources and infrastructure
cloud computing; distributed computing; software engineering