Amortized efficiency of list update and paging rules
Communications of the ACM
Online computation and competitive analysis
Online computation and competitive analysis
Online scheduling with hard deadlines
Journal of Algorithms
Admission control with immediate notification
Journal of Scheduling - Special issue: On-line scheduling
Competitive online scheduling for server systems
ACM SIGMETRICS Performance Evaluation Review
Online Scheduling of Equal-Length Jobs: Randomization and Restarts Help
SIAM Journal on Computing
A simpler competitive analysis for scheduling equal-length jobs on one machine with restarts
Information Processing Letters
Online nonpreemptive scheduling of equal-length jobs on two identical machines
ACM Transactions on Algorithms (TALG)
A Lower Bound for Scheduling of Unit Jobs with Immediate Decision on Parallel Machines
Approximation and Online Algorithms
Online scheduling of equal-length jobs on parallel machines
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Online scheduling with hard deadlines on parallel machines
AAIM'06 Proceedings of the Second international conference on Algorithmic Aspects in Information and Management
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We consider online, nonpreemptive scheduling of equal-length jobs on parallel machines. Jobs have arbitrary release times and deadlines and a scheduler's goal is to maximize the number of completed jobs (Pm | rj,pj=p |∑1−Uj). This problem has been previously studied under two distinct models. In the first, a scheduler must provide immediate notification to a released job as to whether it is accepted into the system. In a stricter model, a scheduler must provide an immediate decision for an accepted job, selecting both the time interval and machine on which it will run. We examine an intermediate model in which a scheduler immediately dispatches an accepted job to a machine, but without committing it to a specific time interval. We present a natural algorithm that is optimally competitive for m=2. For the special case of unit-length jobs, it achieves competitive ratios for m≥2 that are strictly better than lower bounds for the immediate decision model.