Reusable Resource Allocation under Adversarial Arrivals: Learning with Delayed Feedback
We study an online reusable resource allocation problem motivated by mobile edge AI platforms, where sequentially arriving requests must be immediately admitted and assigned to one of multiple edge service options with limited reusable capacities or offloaded to a remote central server. If accepted, a request occupies...