Predicting SLA conformance for cluster-based services Show others and affiliations
2017 (English) In: 2017 IFIP Networking Conference, IFIP Networking 2017 and Workshops, 2017, p. 1-2Conference paper, Published paper (Refereed)
Abstract [en]
The ability to predict conformance or violation for given Service-level Agreements (SLAs) is critical for service assurance. We demonstrate a prototype for real-time conformance prediction based on the concept of the capacity region, which abstracts the underlying ICT infrastructure with respect to the load it can carry for a given SLA. The capacity region is estimated through measurements and statistical learning. We demonstrate prediction for a key-value store (Voldemort) that runs on a server cluster located at KTH.
Place, publisher, year, edition, pages 2017. p. 1-2
Keywords [en]
Capacity Region, Feasible Region, Real-time Prediction, Service-level Agreement (SLA), Statistical Learning, Network architecture, Quality of service, Capacity regions, Feasible regions, Service Level Agreement (SLA), Forecasting
National Category
Computer and Information Sciences
Identifiers URN: urn:nbn:se:ri:diva-34627 DOI: 10.23919/IFIPNetworking.2017.8264873 Scopus ID: 2-s2.0-85050566272 ISBN: 9783901882944 (print) OAI: oai:DiVA.org:ri-34627 DiVA, id: diva2:1238745
Conference 2017 IFIP Networking Conference and Workshops, IFIP Networking 2017, 12 June 2017 through 16 June 2017
Note Funding details: VINNOVA; Funding details: VR, Vetenskapsrådet;
2018-08-142018-08-142021-11-26 Bibliographically approved