Is there self-similarity in cloud QoS data?

Rehman, ZU; Hussain, FK; Hussain, OK; Singh, J

Is there self-similarity in cloud QoS data?

Rehman, ZU Hussain, FK

Hussain, OK Singh, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2013 IEEE 10th International Conference on e-Business Engineering, ICEBE 2013, 2013, pp. 76 - 81
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Rehman, ZU	en_US
dc.contributor.author	Hussain, FK https://orcid.org/0000-0003-1513-8072	en_US
dc.contributor.author	Hussain, OK	en_US
dc.contributor.author	Singh, J	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	Proceedings - 2013 IEEE 10th International Conference on e-Business Engineering, ICEBE 2013, 2013, pp. 76 - 81	en_US
dc.identifier.isbn	9780769551111	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28375
dc.description.abstract	Monitoring and forecasting of QoS of cloud services is becoming increasingly important with increasing use of cloud computing. Cloud service selection, SLA compliance, service migration and many other areas in current cloud computing research rely on QoS data collected thorough cloud service monitoring. In this paper we have presented the results of our experiments for estimating the self-similarity in cloud service QoS data. © 2013 IEEE.	en_US
dc.relation.ispartof	Proceedings - 2013 IEEE 10th International Conference on e-Business Engineering, ICEBE 2013	en_US
dc.relation.isbasedon	10.1109/ICEBE.2013.12	en_US
dc.title	Is there self-similarity in cloud QoS data?	en_US
dc.type	Conference Proceeding
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	Coventry, UK	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Monitoring and forecasting of QoS of cloud services is becoming increasingly important with increasing use of cloud computing. Cloud service selection, SLA compliance, service migration and many other areas in current cloud computing research rely on QoS data collected thorough cloud service monitoring. In this paper we have presented the results of our experiments for estimating the self-similarity in cloud service QoS data. © 2013 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/28375