학술논문
DIANA Scheduling Hierarchies for Optimizing Bulk Job Scheduling
Document Type
Conference
Author
Source
2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06) e-Science and Grid Computing, 2006. e-Science '06. Second IEEE International Conference on. :89-89 Dec, 2006
Subject
Language
Abstract
The use of meta-schedulers for resource management in large-scale distributed systems often leads to a hierarchy of schedulers. In this paper, we discuss why existing meta-scheduling hierarchies are sometimes not sufficient for Grid systems due to their inability to re-organise jobs already scheduled locally. Such a job re-organisation is required to adapt to evolving loads which are common in heavily used Grid infrastructures. We propose a peer-topeer scheduling model and evaluate it using case studies and mathematical modelling. We detail the DIANA (Data Intensive and Network Aware) scheduling algorithm and its queue management system for coping with the load distribution and for supporting bulk job scheduling. We demonstrate that such a system is beneficial for dynamic, distributed and self-organizing resource management and can assist in optimizing load or job distribution in complex Grid infrastructures.