• DocumentCode
    3009966
  • Title

    Looking-Ahead Algorithms for Single Machine Schedulers to Support Advance Reservation of Grid Jobs

  • Author

    Li, Bo ; Chen, Jun ; Zhao, Dongfeng

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming
  • fYear
    2008
  • fDate
    25-27 Sept. 2008
  • Firstpage
    335
  • Lastpage
    341
  • Abstract
    Advance reservations are usually adopted to guarantee the QoS of grid applications by reserving a particular resource capability over a defined time interval on local resources. Single machine scheduling is the basis of more complicated parallel machine scheduling. Assume the information (e.g., arrival time, required processing time) on queued AR and non-AR jobs is known before scheduling, it is NP-hard to allocate non-resumable non-AR jobs into available intervals left by AR jobs to minimize the makespan. This paper investigates the cases with lookahead k in which the scheduler can preview the durations of the sequent k-1 available intervals as the current available interval arrives. By transforming this deterministic scheduling problem into a variant of the standard variable-sized bin packing problem, this paper proposed four looking-ahead algorithms and investigated their performances from both of the worst case and the average case viewpoints.
  • Keywords
    bin packing; computational complexity; grid computing; quality of service; single machine scheduling; NP-hard problem; QoS; advance reservation; grid jobs; looking-ahead algorithm; parallel machine scheduling; single machine schedulers; variable-sized bin packing problem; Grid computing; High performance computing; Information science; Internet; Parallel machines; Processor scheduling; Resource management; Scheduling algorithm; Single machine scheduling; Standards publication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing and Communications, 2008. HPCC '08. 10th IEEE International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-0-7695-3352-0
  • Type

    conf

  • DOI
    10.1109/HPCC.2008.69
  • Filename
    4637716