Cloud Native
Performance models identified at run-time can be used by self-adaptive software systems to execute decisions on a cloud environment. These performance models are built by measuring the control inputs, disturbances, and outputs of the controlled system. These models have been shown to accurately interpolate for data already seen by the model identification method. However, automation in cloud operations can push the environment into operational regions the system has not seen, thus the performance model may not accurately extrapolate into unseen regions.
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This dataset accompanies a paper that discusses the advantages of a 3GPP-compliant service-based architecture platform that demonstrates the concept of cloud-native service orchestration and routing for a media vertical sector application. Cloud-native service orchestration and routing is a complete end-to-end approach that enables virtualisation and management of multiple layers in the OSI model, which provides considerable flexibility and control to achieve delivery of QoS to users in the face of varying demand, at reasonable cost.
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