Min-energy scheduling for aligned jobs in accelerate model

Dynamic voltage scaling technique provides the capability for processors to adjust the speed and control the energy consumption. We study the pessimistic accelerate model where the acceleration rate of the processor speed is at most K and jobs cannot be executed during the speed transition period. The objective is to find a min-energy (optimal) schedule that finishes every job within its deadline. The job set we study in this paper is aligned jobs where earlier released jobs have earlier deadlines. We start by investigating a special case where all jobs have common arrival time and design an O(n ²) algorithm to compute the optimal schedule based on some nice properties of the optimal schedule. Then, we study the general aligned jobs and obtain an O(n ²) algorithm to compute the optimal schedule by using the algorithm for the common arrival time case as a building block. Because our algorithm relies on the computation of the optimal schedule in the ideal model (K=∞), in order to achieve O(n ²) complexity, we improve the complexity of computing the optimal schedule in the ideal model for aligned jobs from the currently best known O(n ²logn) to O(n ²).