Dynamic Exception Handling for Partitioned Workflow on Federated Clouds

The aim of federated cloud computing is to allow applications to utilise a set of clouds in order to provide a better combination of properties, such as cost, security, performance and dependability, than can be achieved on a single cloud. In this paper we focus on security and dependability: introducing a new automatic method for dynamically partitioning applications across the set of clouds in an environment in which clouds can fail during workflow execution. The method deals with exceptions that occur when clouds fail, and selects the best way to repartition the workflow, whilst still meeting security requirements. This avoids the need for developers to have to code ad-hoc solutions to address cloud failure, or the alternative of simply accepting that an application will fail when a cloud fails. This paper's method builds on earlier work [1] on partitioning workflows over federated clouds to minimise cost while meeting security requirements. It extends it by pre-generating the graph of all possible ways to partition the workflow, and adding weights to the paths through the graph so that when a cloud fails, it is possible to quickly determine the cheapest possible way to make progress from that point to the completion of the workflow execution (if any path exists). The method has been implemented and evaluated through a tool which exploits e-Science Central: a portable, high-level cloud platform. The workflow application is created and distributed across a set of e-Science Central instances. By monitoring the state of each executing e-Science Central instance, the system handles exceptions as they occur at run-time. The paper describes the method and an evaluation that utilises a set of examples.