Auspice: Automatic Service Planning in Cloud/Grid Environments

  • David ChiuEmail author
  • Gagan Agrawal
Part of the Computer Communications and Networks book series (CCN)


Recent scientific advances have fostered a mounting number of services and data sets available for utilization. These resources, though scattered across disparate locations, are often loosely coupled both semantically and operationally. This loosely coupled relationship implies the possibility of linking together operations and data sets to answer queries. This task, generally known as automatic service composition, therefore abstracts the process of complex scientific workflow planning from the user. We have been exploring a metadata-driven approach toward automatic service workflow composition, among other enabling mechanisms, in our system, Auspice: Automatic Service Planning in Cloud/Grid Environments. In this paper, we present a complete overview of our system’s unique features and outlooks for future deployment as the Cloud computing paradigm becomes increasingly eminent in enabling scientific computing.


Execution Time Keyword Query Derivation Graph Query Request Query Execution Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is supported by NSF grants 0541058, 0619041, and 0833101. The equipment used for the experiments reported here was purchased under the grant 0403342.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.School of Engineering and Computer ScienceWashington State UniversityVancouverUSA
  2. 2.Department of Computer Science and EngineeringThe Ohio State UniversityColumbusUSA

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