Robust resource allocation in a cluster based imaging system

Academic Article


  • Recently there has been an increased demand for imaging systems in support of high-speed digital printing. The required increase in performance in support of such systems can be accomplished through an effective parallel execution of image processing applications in a distributed cluster computing environment. The output of the system must be presented to a raster based display at regular intervals, effectively establishing a hard deadline for the production of each image. Failure to complete a rasterization task before its deadline will result in an interruption of service that is unacceptable. The goal of this research was to derive a metric for measuring robustness in this environment and to design a resource allocation heuristic capable of completing each rasterization task before its assigned deadline, thus, preventing any service interruptions. We present a mathematical model of such a cluster based raster imaging system, derive a robustness metric for evaluating heuristics in this environment, and demonstrate using the metric to make resource allocation decisions. The heuristics are evaluated within a simulation of the studied raster imaging system. We clearly demonstrate the effectiveness of the heuristics by comparing their results with the results of a resource allocation heuristic commonly used in this type of system. © 2009 Elsevier B.V.
  • Authors

    Published In

  • Parallel Computing  Journal
  • Digital Object Identifier (doi)

    Author List

  • Smith J; Shestak V; Siegel HJ; Price S; Teklits L; Sugavanam P
  • Start Page

  • 389
  • End Page

  • 400
  • Volume

  • 35
  • Issue

  • 7