Online scheduling of equal-length jobs: Randomization and restarts help

We consider the following scheduling problem. The input is a set of jobs with equal processing times, where each job is specified by its release time and deadline. The goal is to determine a single-processor nonpreemptive schedule that maximizes the number of completed jobs. In the online version, each job arrives at its release time. We give two online algorithms with competitive ratios below 2 and show several lower bounds on the competitive ratios. First, we give a barely random 5/3-competitive algorithm that uses only one random bit. We also show a lower bound of 3/2 on the competitive ratio of barely random algorithms that randomly choose one of two deterministic algorithms. If the two algorithms are selected with equal probability, we can further improve the bound to 8/5. Second, we give a deterministic 3/2-competitive algorithm in the model that allows restarts, and we show that in this model the ratio 3/2 is optimal. For randomized algorithms with restarts we show a lower bound of 6/5.