Learning to Schedule Online Tasks with Bandit Feedback

arXiv:2402.16463v1 Announce Type: new
Abstract: Online task scheduling serves an integral role for task-intensive applications in cloud computing and crowdsourcing. Optimal scheduling can enhance system performance, typically measured by the reward-to-cost ratio, under some task arrival distribution. On one hand, both reward and cost are dependent on task context (e.g., evaluation metric) and remain black-box in practice. These render reward and cost hard to model thus unknown before decision making. On the other hand, task arrival behaviors remain sensitive to …

abstract applications arxiv cloud cloud computing computing context cost crowdsourcing cs.dc cs.lg distribution evaluation feedback integral performance role scheduling tasks task scheduling type