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    Data Intensive and Network Aware (DIANA) grid scheduling

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    Authors
    McClatchey, Richard
    Anjum, Ashiq cc
    Stockinger, Heinz
    Ali, Arshad
    Willers, Ian
    Thomas, Michael
    Affiliation
    University of West England
    Swiss Institute of Bioinformatics
    National University of Sciences and Technology
    CERN
    California Institute of Technology
    Issue Date
    2007-01-27
    
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    Abstract
    In Grids scheduling decisions are often made on the basis of jobs being either data or computation intensive: in data intensive situations jobs may be pushed to the data and in computation intensive situations data may be pulled to the jobs. This kind of scheduling, in which there is no consideration of network characteristics, can lead to performance degradation in a Grid environment and may result in large processing queues and job execution delays due to site overloads. In this paper we describe a Data Intensive and Network Aware (DIANA) meta-scheduling approach, which takes into account data, processing power and network characteristics when making scheduling decisions across multiple sites. Through a practical implementation on a Grid testbed, we demonstrate that queue and execution times of data-intensive jobs can be significantly improved when we introduce our proposed DIANA scheduler. The basic scheduling decisions are dictated by a weighting factor for each potential target location which is a calculated function of network characteristics, processing cycles and data location and size. The job scheduler provides a global ranking of the computing resources and then selects an optimal one on the basis of this overall access and execution cost. The DIANA approach considers the Grid as a combination of active network elements and takes network characteristics as a first class criterion in the scheduling decision matrix along with computations and data. The scheduler can then make informed decisions by taking into account the changing state of the network, locality and size of the data and the pool of available processing cycles.
    Citation
    McClatchey, R. et al (2007) 'Data Intensive and Network Aware (DIANA) Grid Scheduling', Journal of Grid Computing, 5 (1):43
    Publisher
    Springer
    Journal
    Journal of Grid Computing
    URI
    http://hdl.handle.net/10545/621407
    DOI
    10.1007/s10723-006-9059-z
    Additional Links
    http://link.springer.com/10.1007/s10723-006-9059-z
    Type
    Article
    Language
    en
    ISSN
    15707873
    EISSN
    15729184
    ae974a485f413a2113503eed53cd6c53
    10.1007/s10723-006-9059-z
    Scopus Count
    Collections
    Department of Electronics, Computing & Maths

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