Title :
Optimal deadline scheduling with commitment
Author :
Chen, Shiyao ; Tong, Lang ; He, Ting
Author_Institution :
Sch. of ECE, Cornell Univ., Ithaca, NY, USA
Abstract :
We consider an online preemptive scheduling problem where jobs with deadlines arrive sporadically. A commitment requirement is imposed such that the scheduler has to either accept or decline a job immediately upon arrival. The scheduler´s decision to accept an arriving job constitutes a contract with the customer; if the accepted job is not completed by its deadline as promised, the scheduler loses the value of the corresponding job and has to pay an additional penalty depending on the amount of unfinished workload. The objective of the online scheduler is to maximize the overall profit, i.e., the total value of the admitted jobs completed before their deadlines less the penalty paid for the admitted jobs that miss their deadlines. We show that the maximum competitive ratio is 3 - 2√2 and propose a simple online algorithm to achieve this competitive ratio. The optimal scheduling includes a threshold admission and a greedy scheduling policies. The proposed algorithm has direct applications to the charging of plug-in hybrid electrical vehicles (PHEV) at garages or parking lots.
Keywords :
contracts; greedy algorithms; hybrid electric vehicles; scheduling; commitment requirement; customer contract; garage; greedy scheduling policies; online algorithm; online preemptive scheduling problem; online scheduler; optimal deadline scheduling; parking lots; penalty; plug-in hybrid electrical vehicle charging; profit maximization; threshold admission; Algorithm design and analysis; Optimal scheduling; Schedules; Scheduling; Scheduling algorithm; Upper bound; Deadline scheduling; PHEV charging scheduling; commitment requirement; competitive ratio analysis;
Conference_Titel :
Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on
Conference_Location :
Monticello, IL
Print_ISBN :
978-1-4577-1817-5
DOI :
10.1109/Allerton.2011.6120157