Parallel Machine Scheduling to Minimize Energy Consumption

TL;DR

This paper addresses the challenge of scheduling jobs on multiple parallel machines to minimize total energy consumption, introducing a novel approximation algorithm that accounts for sleep states, preemption, and migration.

Contribution

It presents the first constant approximation algorithm for energy-efficient scheduling on parallel machines with sleep states, preemption, and migration.

Findings

Developed a constant approximation algorithm for the problem.

Analyzed energy consumption considering sleep and active states.

Demonstrated effectiveness through theoretical guarantees.

Abstract

Given n jobs with release dates, deadlines and processing times we consider the problem of scheduling them on m parallel machines so as to minimize the total energy consumed. Machines can enter a sleep state and they consume no energy in this state. Each machine requires Q units of energy to awaken from the sleep state and in its active state the machine can process jobs and consumes a unit of energy per unit time. We allow for preemption and migration of jobs and provide the first constant approximation algorithm for this problem.