Integrating GRID Tools to Build a Computing Resource Broker: Activities of DataGrid WP1

Resources on a computational Grid are geographically distributed, heterogeneous in nature, owned by different individuals or organizations with their own scheduling policies, have different access cost models with dynamically varying loads and availability conditions. This makes traditional approaches to workload management, load balancing and scheduling inappropriate. The first work package (WP1) of the EU-funded DataGrid project is addressing the issue of optimizing the distribution of jobs onto Grid resources based on a knowledge of the status and characteristics of these resources that is necessarily out-of-date (collected in a finite amount of time at a very loosely coupled site). We describe the DataGrid approach in integrating existing software components (from Condor, Globus, etc.) to build a Grid Resource Broker, and the early efforts to define a workable scheduling strategy

CREAM: A simple, Grid-accessible, Job Management System for local Computational Resources

Efficient and robust system for accessing computational resources and managing job operations is a key component of any Grid framework designed to support large distributed computing environment. Computing Resource Execution and Management (CREAM) is a simple, minimal system designed to provide efficient processing of a large number of requests for computation on managed resources. Requests are accepted from distributed clients via a Web Service based interface. The CREAM architecture is designed to be a robust, scalable and fault tolerant service of a Grid middleware. In this paper we describe the CREAM architecture and the provided functionality. We also discuss how CREAM is integrated within the EGEE gLite middleware in general, and with the gLite Workload Management System in particular