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On Optimal Allocation in a Distributed Processing Environment

Author

Listed:
  • Amitava Dutta

    (University of Rochester)

  • Gary Koehler

    (Micro Data Base Systems, Inc., Lafayette, Indiana)

  • Andrew Whinston

    (Purdue University)

Abstract

Distributed processing has been motivated by many objectives. Among these are a desire to share resources, reduce communications costs (as compared to a centralized processing scheme), increase performance and decrease response time by partitioning tasks and achieve higher system availability (fault tolerance). Typically, processes (tasks) within a single processor and across processors will communicate among themselves in such a distributed environment. It is desirable to be able to assign tasks to processors in some optimal manner. In this paper, a quadratic partitioning model is developed to represent this interaction of tasks in a distributed processing environment. Initially, no capacity constraints are considered at any processor. An optimal solution (in a probabilistic sense) is found for this uncapacitated problem using a probabilistic branch and bound technique. Capacity constraints for processors are then introduced. Three intuitively appealing heuristics are developed to obtain good, though not necessarily optimal, solutions to the capacitated problem.

Suggested Citation

  • Amitava Dutta & Gary Koehler & Andrew Whinston, 1982. "On Optimal Allocation in a Distributed Processing Environment," Management Science, INFORMS, vol. 28(8), pages 839-853, August.
    • Handle: RePEc:inm:ormnsc:v:28:y:1982:i:8:p:839-853
    DOI: 10.1287/mnsc.28.8.839
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    Citations

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    Cited by:

    1. Bolte, Andreas & Thonemann, Ulrich Wilhelm, 1996. "Optimizing simulated annealing schedules with genetic programming," European Journal of Operational Research, Elsevier, vol. 92(2), pages 402-416, July.
    2. Andreas Ernst & Houyuan Jiang & Mohan Krishnamoorthy, 2006. "Exact Solutions to Task Allocation Problems," Management Science, INFORMS, vol. 52(10), pages 1634-1646, October.
    3. Gudmundsson, Jens & Hougaard, Jens Leth & Platz, Trine Tornøe, 2023. "Decentralized task coordination," European Journal of Operational Research, Elsevier, vol. 304(2), pages 851-864.

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