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A Dynamic Resource Controller for a Lambda Architecture
Sch. of IT, Univ. of Sydney, Sydney, NSW, Australia.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO, Computer Networking)ORCID iD: 0000-0001-9194-010X
Sch. of Sci., RMIT Univ., Melbourne, VIC, Australia.
School of Information Technologies, University of Sydney.
2017 (English)In: 2017 46th International Conference on Parallel Processing (ICPP), Piscataway: IEEE, 2017, p. 332-341Conference paper, Published paper (Refereed)
Abstract [en]

Lambda architecture is a novel event-driven serverless paradigm that allows companies to build scalable and reliable enterprise applications. As an attractive alternative to traditional service oriented architecture (SOA), Lambda architecture can be used in many use cases including BI tools, in-memory graph databases, OLAP, and streaming data processing. In practice, an important aim of Lambda's service providers is devising an efficient way to co-locate multiple Lambda functions with different attributes into a set of available computing resources. However, previous studies showed that consolidated workloads can compete fiercely for shared resources, resulting in severe performance variability/degradation. This paper proposes a resource allocation mechanism for a Lambda platform based on the model predictive control framework. Performance evaluation is carried out by comparing the proposed solution with multiple resource allocation heuristics, namely enhanced versions of spread and binpack, and best-effort approaches. Results confirm that the proposed controller increases the overall resource utilization by 37% on average and achieves a significant improvement in preventing QoS violation incidents compared to others.

Place, publisher, year, edition, pages
Piscataway: IEEE, 2017. p. 332-341
National Category
Computer Sciences Software Engineering Computer Systems Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-66138DOI: 10.1109/ICPP.2017.42ISBN: 978-1-5386-1042-8 (electronic)ISBN: 978-1-5386-1043-5 (print)OAI: oai:DiVA.org:kau-66138DiVA, id: diva2:1180738
Conference
ICCP 2017, 46th International Conference om Parallel Processing, 14-17 August Bristol, United Kingdom
Available from: 2018-02-06 Created: 2018-02-06 Last updated: 2018-07-06Bibliographically approved

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Taheri, Javid

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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