摘要
There are several motivations, such as mobility, cost, and secu- rity, that are behind the trend of traditional desktop users transi- tioning to thin-client-based virtual desktop clouds （VDCs）. Such a trend has led to the rising importance of human-centric performance modeling and assessment within user communities that are increasingly making use of desktop virtualization. In this paper, we present a novel reference architecture and its eas- ily deployable implementation for modeling and assessing objec- tive user quality of experience （QoE） in VDCs. This architec- ture eliminates the need for expensive, time-consuming subjec- tive testing and incorporates finite-state machine representa- tions for user workload generation. It also incorporates slow-mo- tion benchmarking with deep-packet inspection of application task performance affected by QoS variations. In this way, a ＂composite-quality＂ metric model of user QoE can be derived. We show how this metric can be customized to a particular user group profile with different application sets and can be used to a） identify dominant performance indicators and troubleshoot bottlenecks and b） obtain both absolute and relative objective user QoE measurements needed for pertinent selection of thin-client encoding configurations in VDCs. We validate our composite-quality modeling and assessment methodology by us- ing subjective and objective user QoE measurements in a re- al-world VDC called VDPilot, which uses RDP and PCoIP thin-client protocols. In our case study, actual users are pres- ent in virtual classrooms within a regional federated university system.
There are several motivations, such as mobility, cost, and secu- rity, that are behind the trend of traditional desktop users transi- tioning to thin-client-based virtual desktop clouds （VDCs）. Such a trend has led to the rising importance of human-centric performance modeling and assessment within user communities that are increasingly making use of desktop virtualization. In this paper, we present a novel reference architecture and its eas- ily deployable implementation for modeling and assessing objec- tive user quality of experience （QoE） in VDCs. This architec- ture eliminates the need for expensive, time-consuming subjec- tive testing and incorporates finite-state machine representa- tions for user workload generation. It also incorporates slow-mo- tion benchmarking with deep-packet inspection of application task performance affected by QoS variations. In this way, a ＂composite-quality＂ metric model of user QoE can be derived. We show how this metric can be customized to a particular user group profile with different application sets and can be used to a） identify dominant performance indicators and troubleshoot bottlenecks and b） obtain both absolute and relative objective user QoE measurements needed for pertinent selection of thin-client encoding configurations in VDCs. We validate our composite-quality modeling and assessment methodology by us- ing subjective and objective user QoE measurements in a re- al-world VDC called VDPilot, which uses RDP and PCoIP thin-client protocols. In our case study, actual users are pres- ent in virtual classrooms within a regional federated university system.
基金
supported by VMware and the National Science Foundation under award numbers CNS-1050225 and CNS-1205658
