Scheduling under dynamic speed-scaling for minimizing weighted completion time and energy consumption

TL;DR

This paper investigates scheduling on a single machine with dynamic speed-scaling to optimize a trade-off between weighted completion time and energy use, proposing mechanisms that are truthful and cost-effective.

Contribution

It introduces a reduction of the combined objective to a polynomial penalty scheduling problem and designs a truthful cost share mechanism with bounded overcharging.

Findings

Minimizing the combined objective reduces to a polynomial penalty scheduling problem.

The proposed mechanism is truthful and has bounded overcharging.

The approach balances energy consumption and service quality effectively.

Abstract

Since a few years there is an increasing interest in minimizing the energy consumption of computing systems. However in a shared computing system, users want to optimize their experienced quality of service, at the price of a high energy consumption. In this work, we address the problem of optimizing and designing mechanisms for a linear combination of weighted completion time and energy consumption on a single machine with dynamic speed-scaling. We show that minimizing linear combination reduces to a unit speed scheduling problem under a polynomial penalty function. In the mechanism design setting, we define a cost share mechanism and studied its properties, showing that it is truthful and the overcharging of total cost share is bounded by a constant.