2024/03/26 by Rahul Vaze, Vaze, Rahul, Jayakrishnan Nair +1
Computer Science · Engineering · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #IoT and Edge/Fog Computing #Machine Learning (cs.LG) #Optimization and Search Problems #Smart Parking Systems Research
paper · pdf · doi:10.48550/arxiv.2403.17480
openalex publication_date 2024/03/26 · openalex created_date 2024/03/28 · openalex updated_date 2026/07/28
An online non-convex optimization problem is considered where the goal is to minimize the flow time (total delay) of a set of jobs by modulating the number of active servers, but with a switching cost associated with changing the number of active servers over time. Each job can be processed by at most one fixed speed server at any time. Compared to the usual online convex optimization (OCO) problem with switching cost, the objective function considered is non-convex and more importantly, at each time, it depends on all past decisions and not just the present one. Both worst-case and stochastic inputs are considered; for both cases, competitive algorithms are derived.