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Cost-Efficient Scheduling on Machines from the Cloud

  • Alexander MäckerEmail author
  • Manuel Malatyali
  • Friedhelm Meyer auf der Heide
  • Sören Riechers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10043)

Abstract

We consider a scheduling problem where machines need to be rented from the cloud in order to process jobs. There are two types of machines available which can be rented for machine-type dependent prices and for arbitrary durations. However, a machine-type dependent setup time is required before a machine is available for processing. Jobs arrive online over time, have machine-type dependent sizes and have individual deadlines. The objective is to rent machines and schedule jobs so as to meet all deadlines while minimizing the rental cost.

Since we observe the slack of jobs to have a fundamental influence on the competitiveness, we study the model when instances are parameterized by their (minimum) slack. An instance is called to have a slack of \(\beta \) if, for all jobs, the difference between the job’s release time and the latest point in time at which it needs to be started is at least \(\beta \). While for \(\beta < s\) no finite competitiveness is possible, our main result is an Open image in new window -competitive online algorithm for \(\beta = (1+\varepsilon )s\) with Open image in new window , where s and c denotes the largest setup time and the cost ratio of the machine-types, respectively. It is complemented by a lower bound of Open image in new window .

Keywords

Setup Time Integer Linear Program Online Algorithm Setup Cost Machine Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Alexander Mäcker
    • 1
    Email author
  • Manuel Malatyali
    • 1
  • Friedhelm Meyer auf der Heide
    • 1
  • Sören Riechers
    • 1
  1. 1.Heinz Nixdorf Institute & Computer Science DepartmentPaderborn UniversityPaderbornGermany

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