A Grid Service Broker for Scheduling Distributed Data-Oriented Applications on Global Grids
Srikumar Venugopal, Rajkumar Buyya, Lyle Winton

TL;DR
This paper introduces a grid service broker that efficiently manages data and computational resources for distributed data-oriented applications in global grid environments, enhancing e-Science collaborations.
Contribution
It presents a novel grid broker that automates resource discovery, job mapping, deployment, and data access for distributed scientific applications, supporting dynamic parametric programming.
Findings
Successfully deployed high energy physics analysis on a global grid
Enhanced data access and job scheduling efficiency
Demonstrated scalability across international resources
Abstract
The next generation of scientific experiments and studies, popularly called as e-Science, is carried out by large collaborations of researchers distributed around the world engaged in analysis of huge collections of data generated by scientific instruments. Grid computing has emerged as an enabler for e-Science as it permits the creation of virtual organizations that bring together communities with common objectives. Within a community, data collections are stored or replicated on distributed resources to enhance storage capability or efficiency of access. In such an environment, scientists need to have the ability to carry out their studies by transparently accessing distributed data and computational resources. In this paper, we propose and develop a Grid broker that mediates access to distributed resources by (a) discovering suitable data sources for a given analysis scenario, (b)…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Parallel Computing and Optimization Techniques · Cloud Computing and Resource Management
