%0 Conference Paper %1 Chemodanov2016 %A Chemodanov, Dmitrii %A Calyam, Prasad %B QCMan 2016 (QCMan 2016) %C Würzburg, Germany %D 2016 %K itc itc28 %T Application-Aware Infrastructure Clustering for Cloud Service Placement to Enhance User QoE %U https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc28/Chemodanov2016.pdf?inline=true %X Cloud services placement can be suboptimal in certain cases due to inefficient network design, which in turn impacts user Quality of Experience (QoE). Consequently, Application Service Providers (ASPs) need to manage cloud network infrastructures with efficient designs that fully satisfy Service Level Objectives (SLOs) of their data/video-intensive applications of users. To proactively avoid this problem, a straightforward solution used by ASPs is to have many replicas of their services by renting more resources from Infrastructure Providers (InPs) which can lead to an expensive service delivery proposition. In this paper, we present a novel possibilistic C-Means (PCM) approach to enhance user QoE in cloud service placement by clustering network infrastructure with awareness of user SLO satisfaction amidst network path constraints. Our evaluation results obtained using numerical simulations as well as in a real-world cloud testbed with actual users prove that our multi-constrained path aware PCM approach outperforms existing solutions. Specifically, we show how our proposed infrastructure clustering with the PCM approach allows ASPs to rent less resources from InPs that reduces user cost, while still delivering satisfactory user QoE.

@inproceedings{Chemodanov2016, abstract = {Cloud services placement can be suboptimal in certain cases due to inefficient network design, which in turn impacts user Quality of Experience (QoE). Consequently, Application Service Providers (ASPs) need to manage cloud network infrastructures with efficient designs that fully satisfy Service Level Objectives (SLOs) of their data/video-intensive applications of users. To proactively avoid this problem, a straightforward solution used by ASPs is to have many replicas of their services by renting more resources from Infrastructure Providers (InPs) which can lead to an expensive service delivery proposition. In this paper, we present a novel possibilistic C-Means (PCM) approach to enhance user QoE in cloud service placement by clustering network infrastructure with awareness of user SLO satisfaction amidst network path constraints. Our evaluation results obtained using numerical simulations as well as in a real-world cloud testbed with actual users prove that our multi-constrained path aware PCM approach outperforms existing solutions. Specifically, we show how our proposed infrastructure clustering with the PCM approach allows ASPs to rent less resources from InPs that reduces user cost, while still delivering satisfactory user QoE.}, added-at = {2016-08-31T16:30:53.000+0200}, address = {Würzburg, Germany}, author = {Chemodanov, Dmitrii and Calyam, Prasad}, biburl = {https://www.bibsonomy.org/bibtex/20c653594a51cf92a6bde14ea8f0706c4/itc}, booktitle = {QCMan 2016 (QCMan 2016)}, days = {12}, interhash = {fa9be042107af9e4a4a0cd116fb6b95f}, intrahash = {0c653594a51cf92a6bde14ea8f0706c4}, keywords = {itc itc28}, month = {Sept}, timestamp = {2020-05-26T16:53:35.000+0200}, title = {Application-Aware Infrastructure Clustering for Cloud Service Placement to Enhance User QoE}, url = {https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc28/Chemodanov2016.pdf?inline=true}, year = 2016 }