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Performance analysis of job dissemination techniques in Grid systems
Author(s) -
Bruneo Dario,
Longo Francesco,
Scarpa Marco,
Puliafito Antonio
Publication year - 2011
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1697
Subject(s) - computer science , grid , set (abstract data type) , distributed computing , service (business) , operations research , grid computing , quality of service , stochastic petri net , petri net , risk analysis (engineering) , computer network , engineering , geometry , mathematics , economy , economics , programming language , medicine
In the last few years, remarkable efforts have been made to extend the Grid paradigm to commercial solutions. Business‐oriented grids call for effective Quality of Service strategies able to adapt to different user requirements and to address Service Level Agreements. Performance analysis and prediction with respect to different load conditions or management policies are required to define such strategies. However, the highly distributed nature of Grid systems and the presence of distinct administrative domains make it difficult to carry out performance estimations. In fact, several parameters are involved and the autonomy of each site could make it complex to set them in a proper way. In this paper, we present a non‐Markovian Stochastic Petri Net methodology that allows to conduct performance analysis of Grid systems focusing on aspects related to the Virtual Organization as a whole. In particular, different job allocation techniques can be evaluated with respect to both user and provider points‐of‐view. The influence of different information update policies on the accuracy of the allocation schemes can also be investigated, highlighting the costs/benefits in terms of job waiting time, service availability, and system utilization. The proposed methodology is designed to be as general as possible and it can be applied to analyze a gLite Grid infrastructure taken as case study. Copyright © 2011 John Wiley & Sons, Ltd.