SPHINX: A scheduling middleware for data intensive applications on a grid

A grid consists of high-end computational, storage, and network resources that, while known a priori, are dynamic with respect to activity and availability. Efficient scheduling of requests to use grid resources must adapt to this dynamic environment while meeting administrative policies. This paper discusses the necessary requirements of such a scheduler and proposes a framework called SPHINX that can administrate grid policies and schedule complex and data intensive scientific applications. The SPHINX design allows for a number of functional modules to flexibly plan and schedule workflows representing multiple applications on the grids. It also allows for performance evaluation of multiple algorithms for each functional module. We present early experimental results for SPHINX that effectively utilises other grid infrastructures such as workflow management systems and execution systems. These results demonstrate that SPHINX can effectively schedule work across a large number of distributed clusters that are owned by multiple units in a virtual organisation.