dc.contributor.author | Uras Balkanli, Emel | |
dc.date.accessioned | 2017-08-15T15:05:48Z | |
dc.date.available | 2017-08-15T15:05:48Z | |
dc.date.issued | 2017-08-15T15:05:48Z | |
dc.identifier.uri | http://hdl.handle.net/10222/73106 | |
dc.description.abstract | This work offers in-depth analysis of network properties to employ them for service
deployment on cloud systems. The proposed analysis is evaluated on three different
data sets from different locations, captured in 2012, 2013 and 2014 to provide insights
into network properties and how to use them while deploying services. This research
proposes the employment of a Self-Organizing Map as a type of Artificial Neural
Network that generates a low-dimensional representation of high dimensional data
using unsupervised learning methods. My analysis shows that there are significant
effects of selected network properties, namely latency, success status, hop count and
time-to-live, on the optimal location for the service to be deployed. In summary, using
the proposed technique for analysis of network properties to choose the location for
service deployment on the cloud could help to understand where to deploy the service
to increase efficiency with respect to the selected properties. | en_US |
dc.language.iso | en | en_US |
dc.subject | SOM | en_US |
dc.subject | KMENAS | en_US |
dc.subject | OPTIMIZATION | en_US |
dc.title | ANALYSIS OF NETWORK PROPERTIES USING SELF ORGANIZING MAPS FOR SERVICE DEPLOYMENT ON THE CLOUD | en_US |
dc.type | Thesis | en_US |
dc.date.defence | 2017-08-04 | |
dc.contributor.department | Faculty of Computer Science | en_US |
dc.contributor.degree | Master of Computer Science | en_US |
dc.contributor.external-examiner | n/a | en_US |
dc.contributor.graduate-coordinator | Norbert Zeh | en_US |
dc.contributor.thesis-reader | Malcolm Heywood | en_US |
dc.contributor.thesis-reader | Andrew McIntyre | en_US |
dc.contributor.thesis-supervisor | Nur Zincir-Heywood | en_US |
dc.contributor.ethics-approval | Not Applicable | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.copyright-release | Not Applicable | en_US |