Abstract
We study high-performance Real-Time Online Interactive Applications (ROIAs), with use cases like product configurators in the Configure-Price-Quote market, e-learning, multiplayer online gaming, and digital twins of production facilities for the Industry 4.0 market. While core components of ROIAs, e.g., interactive real-time 3D rendering, still widely run on local devices, it is very desirable to run them on cloud resources to benefit from the advantages of cloud computing, e.g., better quality provided by high-performance compute resources and accessibility. In this paper, we design and implement a novel cloud service deployment architecture for ROIAs, which addresses three major challenges: meeting the high Quality of Service (QoS) requirements, auto-scalability, and resource usage optimization. Compared to previous work, our deployment approach is based on the concept of session slots that combines a high level of QoS with the economic use of resources like CPU, GPU, and memory. We describe a prototype implementation of a ROIA use case - a car configurator running on a Kubernetes cluster. Experimental evaluation demonstrates that our architecture avoids the traffic and latency bottleneck of a classical cloud load balancer, provides significantly more efficient resource usage, and can autoscale well.
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Jarrous-Holtrup, S., Schamel, F., Hofer, K., Gorlatch, S. (2021). A Scalable Cloud Deployment Architecture for High-Performance Real-Time Online Applications. In: Jagode, H., Anzt, H., Ltaief, H., Luszczek, P. (eds) High Performance Computing. ISC High Performance 2021. Lecture Notes in Computer Science(), vol 12761. Springer, Cham. https://doi.org/10.1007/978-3-030-90539-2_26
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DOI: https://doi.org/10.1007/978-3-030-90539-2_26
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