Metascheduling and Heuristic Co-Allocation Strategies in Distributed Computing


  • Victor Toporkov National Research University "MPEI", Moscow
  • Dmitry Yemelyanov National Research University "MPEI", Moscow
  • Petr Potekhin National Research University "MPEI", Moscow
  • Anna Toporkova National Research University Higher School of Economics, Moscow State Institute of Electronics and Mathematics, Moscow
  • Alexey Tselishchev European Organization for Nuclear Research (CERN), Geneva


Distributed computing, economic scheduling, resource management, co-allocation, slot, job, task, batch


In this paper, we address problems of efficient computing in distributed systems with non-dedicated resources including utility grid. There are global job flows from external users along with resource owner's local tasks upon the resource non-dedication condition. Competition for resource reservation between independent users, local and global job flows substantially complicates scheduling and the requirement to provide the necessary quality of service. A metascheduling concept, justified in this work, assumes a complex combination of job flow dispatching and application-level scheduling methods for parallel jobs, as well as resource sharing and consumption policies established in virtual organizations and based on economic principles. We introduce heuristic slot selection and co-allocation strategies for parallel jobs. They are formalized by given criteria and implemented by algorithms of linear complexity on an available slots number.


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How to Cite

Toporkov, V., Yemelyanov, D., Potekhin, P., Toporkova, A., & Tselishchev, A. (2015). Metascheduling and Heuristic Co-Allocation Strategies in Distributed Computing. COMPUTING AND INFORMATICS, 34(1), 45–76. Retrieved from



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