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Energy-efficient resource allocation and provisioning for in-memory database clusters

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Title: Energy-efficient resource allocation and provisioning for in-memory database clusters
Authors: Karsten, M
Casale, G
Item Type: Conference Paper
Abstract: Systems for processing large scale analytical work- loads are increasingly moving from on-premise setups to on- demand configurations deployed on scalable cloud infrastruc- tures. To reduce the cost of such infrastructures, existing research focuses on developing novel methods for workload and server consolidation. In this paper, we combine analytical modeling and non-linear optimization to help cloud providers increase the energy-efficiency of in-memory database clusters in cloud environments. We model this scenario as a multi-dimensional bin- packing problem and propose a new approach based on a hybrid genetic algorithm that efficiently handles resource allocation and server assignment for a given set of in-memory databases. Our trace-driven evaluation is based on measurements from an SAP HANA in-memory system and indicates improvements between 6% and 32% over the popular best-fit decreasing heuristic.
Issue Date: 24-Jul-2017
Date of Acceptance: 11-Nov-2016
URI: http://hdl.handle.net/10044/1/43616
DOI: 10.23919/inm.2017.7987260
Publisher: IEEE
Journal / Book Title: 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)
Copyright Statement: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 644869
Conference Name: IEEE/IFIP IM International Symposium on Integrated Network Management
Publication Status: Published
Start Date: 2017-05-08
Finish Date: 2017-05-12
Conference Place: Lisbon
Appears in Collections:Computing
Faculty of Engineering