🤖 AI Summary
本文针对云数据中心节能问题，通过新方法改进了任务调度算法，减少了机器总忙时，提出了2.445近似和2.5竞争在线算法。
📝 Abstract
We study the Busy Machine Time with Preemption and Migration and One Resource Requirement problem, motivated by energy minimization in cloud data centers. Given unlimited identical-capacity machines and jobs with release times, deadlines, processing times, and resource requirements, we allow free preemption and migration at integer times and seek to minimize total machine busy time. The problem is NP-hard, and previous results consist of a 2-approximation, 2-competitive algorithm for the case of uniform heights.
We obtain a 22/9 < 2.445-approximation algorithm and a 2.5-competitive online algorithm, both running in O(n^2 log n) time. Our methods are based on new non-asymptotic performance bounds for the First Fit Decreasing algorithm for Bin Packing, and a new generalization of Span Minimization, the Huge-Tiny Busy Time problem, for which we present an exact offline algorithm and an optimal (3/2)-competitive deterministic online algorithm.