A Stochastic Bin Packing Approach for Server Consolidation with Conflicts

John Martinovic (), Markus Hähnel (), Waltenegus Dargie () and Guntram Scheithauer ()
Additional contact information
John Martinovic: Technische Universität Dresden
Markus Hähnel: Technische Universität Dresden
Waltenegus Dargie: Technische Universität Dresden
Guntram Scheithauer: Technische Universität Dresden

A chapter in Operations Research Proceedings 2019, 2020, pp 159-165 from Springer

Abstract: Abstract The energy consumption of large-scale data centers or server clusters is expected to grow significantly in the next couple of years contributing to up to 13% of the worldwide energy demand in 2030. As the involved processing units require a disproportional amount of energy when they are idle, underutilized or overloaded, balancing the supply of and the demand for computing resources is a key issue to obtain energy-efficient server consolidations. Whereas traditional concepts mostly consider deterministic predictions of the future workloads or only aim at finding approximate solutions, here we propose an exact bin packing based approach to tackle the problem of assigning jobs with (not necessarily independent) stochastic characteristics to a minimal amount of servers subject to further practical constraints. Finally, this new approach is tested against real-world instances obtained from a Google data center.

Keywords: Cutting and packing; Server consolidation; Bin packing problem; Normal distribution; HAEC (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-48439-2_19

Ordering information: This item can be ordered from
http://www.springer.com/9783030484392

DOI: 10.1007/978-3-030-48439-2_19

Access Statistics for this chapter

More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().