2 research outputs found
A Multi Interface Grid Discovery System
Discovery Systems (DS) can be considered as entry points for global loosely coupled distributed systems. An efficient Discovery System in essence increases the performance, reliability and decision making capability of distributed systems. With the rapid increase in scale of distributed applications, existing solutions for discovery systems are fast becoming either obsolete or incapable of handling such complexity. They are particularly ineffective when handling service lifetimes and providing up-to-date information, poor at enabling dynamic service access and they can also impose unwanted restrictions on interfaces to widely available information repositories. In this paper we present essential the design characteristics, an implementation and a performance analysis for a discovery system capable of overcoming these deficiencies in large, globally distributed environments
Bulk Scheduling with the DIANA Scheduler
Results from the research and development of a Data Intensive and Network
Aware (DIANA) scheduling engine, to be used primarily for data intensive
sciences such as physics analysis, are described. In Grid analyses, tasks can
involve thousands of computing, data handling, and network resources. The
central problem in the scheduling of these resources is the coordinated
management of computation and data at multiple locations and not just data
replication or movement. However, this can prove to be a rather costly
operation and efficient sing can be a challenge if compute and data resources
are mapped without considering network costs. We have implemented an adaptive
algorithm within the so-called DIANA Scheduler which takes into account data
location and size, network performance and computation capability in order to
enable efficient global scheduling. DIANA is a performance-aware and
economy-guided Meta Scheduler. It iteratively allocates each job to the site
that is most likely to produce the best performance as well as optimizing the
global queue for any remaining jobs. Therefore it is equally suitable whether a
single job is being submitted or bulk scheduling is being performed. Results
indicate that considerable performance improvements can be gained by adopting
the DIANA scheduling approach.Comment: 12 pages, 11 figures. To be published in the IEEE Transactions in
Nuclear Science, IEEE Press. 200