A Task-Type-Based Algorithm for the Energy-Aware Profit Maximizing Scheduling Problem in Heterogeneous Computing Systems

TL;DR

This paper introduces an efficient, task-type-based algorithm for energy-aware profit maximization in heterogeneous computing systems, improving speed and accuracy over previous task-dependent algorithms.

Contribution

The paper presents a novel algorithm whose runtime depends on task types rather than individual tasks, with proven near-optimal performance ratio.

Findings

The proposed algorithm is faster than previous methods.

Simulation results show higher accuracy in profit maximization.

Performance ratio is close to 2, indicating near-optimality.

Abstract

In this paper, we design an efficient algorithm for the energy-aware profit maximizing scheduling problem, where the high performance computing system administrator is to maximize the profit per unit time. The running time of the proposed algorithm is depending on the number of task types, while the running time of the previous algorithm is depending on the number of tasks. Moreover, we prove that the worst-case performance ratio is close to 2, which maybe the best result. Simulation experiments show that the proposed algorithm is more accurate than the previous method.