Title
Online cost-efficient scheduling of deadline-constrained workloads on hybrid clouds Online cost-efficient scheduling of deadline-constrained workloads on hybrid clouds
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
Amsterdam ,
Subject
Computer. Automation
Source (journal)
Future generation computer systems: the international journal of grid computing: theory, methods & applications. - Amsterdam
Volume/pages
29(2013) :4 , p. 973-985
ISSN
0167-739X
ISI
000315546800005
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Cloud computing has found broad acceptance in both industry and research, with public cloud offerings now often used in conjunction with privately owned infrastructure. Technical aspects such as the impact of network latency, bandwidth constraints, data confidentiality and security, as well as economic aspects such as sunk costs and price uncertainty are key drivers towards the adoption of such a hybrid cloud model. The use of hybrid clouds introduces the need to determine which workloads are to be outsourced, and to what cloud provider. These decisions should minimize the cost of running a partition of the total workload on one or multiple public cloud providers while taking into account the application requirements such as deadline constraints and data requirements. The variety of cost factors, pricing models and cloud provider offerings to consider, further calls for an automated scheduling approach in hybrid clouds. In this work, we tackle this problem by proposing a set of algorithms to cost-efficiently schedule the deadline-constrained bag-of-tasks applications on both public cloud providers and private infrastructure. Our algorithms take into account both computational and data transfer costs as well as network bandwidth constraints. We evaluate their performance in a realistic setting with respect to cost savings, deadlines met and computational efficiency, and investigate the impact of errors in runtime estimates on these performance metrics.
E-info
https://repository.uantwerpen.be/docman/iruaauth/fcd9ac/f7212a06a5b.pdf
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000315546800005&DestLinkType=RelatedRecords&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000315546800005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000315546800005&DestLinkType=CitingArticles&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
Handle