Benchmarking in virtual desktops for end-to-end performance traceability

Nguyen, Trung; Calyam, Prasad; Antequera, Ronny Bazan

doi:10.1109/inm.2015.7140479

Cited by 5 publications

(3 citation statements)

References 7 publications

(7 reference statements)

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“…Several proposals used slow-motion benchmarking as the core of their research. Among them is the work carried out by Nguyen et al [51]. The authors proposed a tool (VDBench) to evaluate and compare different remote desktop solutions.…”

Section: Strategies Based On the Use Of Slow-motion Benchmarkingmentioning

confidence: 99%

“…Thus, the visual quality is the ratio between the traffic generated by the CIA at a normal FPS rate and its ideal reference obtained by the tool with a single frame on the network. Some of the proposals mentioned above used this expression in their research to complement the information provided by the VD-DUT metric, for instance, Alali et al [33] and Nguyen et al [51].…”

Section: Strategies Based On Audiovisual Degradation Measuresmentioning

confidence: 99%

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Survey on Quality of Experience Evaluation for Cloud-Based Interactive Applications

Arellano-Uson,

Magaña,

Morato

et al. 2024

Applied Sciences

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A cloud-based interactive application (CIA) is an application running in the cloud with stringent interactivity requirements, such as remote desktop and cloud gaming. These services have experienced a surge in usage, primarily due to the adoption of new remote work practices during the pandemic and the emergence of entertainment schemes similar to cloud gaming platforms. Evaluating the quality of experience (QoE) in these applications requires specific metrics, including interactivity time, responsiveness, and the assessment of video- and audio-quality degradation. Despite existing studies that evaluate QoE and compare features of general cloud applications, systematic research into QoE for CIAs is lacking. Previous surveys often narrow their focus, overlooking a comprehensive assessment. They touch on QoE in broader contexts but fall short in detailed metric analysis. Some emphasise areas like mobile cloud computing, omitting CIA-specific nuances. This paper offers a comprehensive survey of QoE measurement techniques in CIAs, providing a taxonomy of input metrics, strategies, and evaluation architectures. State-of-the-art proposals are assessed, enabling a comparative analysis of their strengths and weaknesses and identifying future research directions.

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Section: Strategies Based On the Use Of Slow-motion Benchmarkingmentioning

confidence: 99%

Section: Strategies Based On Audiovisual Degradation Measuresmentioning

confidence: 99%

Survey on Quality of Experience Evaluation for Cloud-Based Interactive Applications

Arellano-Uson,

Magaña,

Morato

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…To this end, our 3Q interplay model dynamically adapts the 3Q interplay based on the feedback from both user (optional, if available) and application (required), where the former and the latter can be considered as classical open-loop and closed-loop control systems [8], respectively. Note that an application's feedback can be obtained from tools such as VDBench [23] in operational environments. This is how the 3Q model varies from common QoE profiles where this interplay is assumed to be static [9].…”

Section: B Asp Optimization Problem Within Data Planementioning

confidence: 99%

On QoE-Oriented Cloud Service Orchestration for Application Providers

Chemodanov

Calyam

Valluripally

et al. 2021

IEEE Trans. Serv. Comput.

Self Cite

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New virtualization technologies allow Infrastructure Providers (InPs) to lease their resources to Application Service Providers (ASPs) for highly scalable delivery of cloud services to end-users. However, existing literature lacks knowledge on Quality of Experience (QoE)-oriented cloud service orchestration algorithms that can guide ASPs on how to plan their budget to enhance satisfactory QoE delivery to end-users. In contrast to the InP's cloud service orchestration, the ASP's orchestration should not rely on expensive infrastructure control mechanisms such as Software-Defined Networking (SDN), or require apriori knowledge on the number of services to be instantiated and their anticipated placement location within InP's infrastructure. In this paper, we address this issue of delivering satisfactory user QoE by synergistically optimizing both ASP's management and data planes. The optimization within the ASP management plane first maximizes Service Level Objective (SLO) coverage of users when application services are being deployed, and are not yet operational. The optimization of the ASP data plane then enhances satisfactory user QoE delivery when applications services are operational with real user access. Our evaluation of QoE-oriented algorithms using realistic numerical simulations, real-world cloud testbed experiments with actual users and ASP case studies show notably improved performance over existing cloud service orchestration solutions.Index Terms-QoE-oriented cloud service orchestration, multiconstrained path-aware possibilistic C-mean clustering, 3Q interplay model, least cost-disruptive decision tree.

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Interactivity Anomaly Detection in Remote Work Scenarios Using LSTM

Arellano-Uson,

Magaña,

Morató

et al. 2024

IEEE Access

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In recent years, there has been a notable surge in the utilization of remote desktop services, largely driven by the emergence of new remote work models introduced during the pandemic. These services cater to interactive cloud-based applications (CIAs), whose core functionality operates in the cloud, demanding strict end-user interactivity requirements. This boom has led to a significant increase in their deployment, accompanied by a corresponding increase in associated maintenance costs. Service administrators aim to guarantee a satisfactory Quality of Experience (QoE) by monitoring metrics like interactivity time, particularly in cloud environments where variables such as network performance and shared resources come into play. This paper analyses anomaly detection state of the art and proposes a novel system for detecting interactivity time anomalies in cloud-based remote desktop environments. We employ an automatic model based on LSTM neural networks that achieves an accuracy of up to 99.97%.INDEX TERMS remote work, interactivity time, anomaly detection, LSTM, cloud-based interactive applications, remote desktop, QoE.

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Benchmarking in virtual desktops for end-to-end performance traceability

Cited by 5 publications

References 7 publications

Survey on Quality of Experience Evaluation for Cloud-Based Interactive Applications

Survey on Quality of Experience Evaluation for Cloud-Based Interactive Applications

On QoE-Oriented Cloud Service Orchestration for Application Providers

Interactivity Anomaly Detection in Remote Work Scenarios Using LSTM

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