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Software Defined Networking (SDN) paradigm is introducing novel approaches for many unresolved issues of networking. These new outlooks are imperative in emerging scenarios where user requirements keep growing, the required bandwidth keeps increasing, and so does the variety of applications (e.g. Big data analytics) that suggest the network plays a more prominent role. As such, our research aims to...
In the presence of scale, dynamism, uncertainty and elasticity, cloud software engineers faces several challenges when modeling Quality of Service (QoS) for cloud-based software services. These challenges can be best managed through self-adaptivity because engineers’ intervention is difficult, if not impossible, given the dynamic and uncertain QoS sensitivity to the environment and control knobs in...
Promoting self-aware autoscaling to intelligently handle the dynamics and uncertainty of changing workloads, configurations, and demands on resources at runtime can facilitate more scalable, elastic, and dependable cloud-based services.
As VoD systems migrate to the Cloud, new challenges emerge in managing user Quality-of- Experience (QoE). The complexity of the cloud system due to virtualization and resource sharing complicates the QoE management. Operational failures in the Cloud could be challenging for QoE as well. We believe that end users have the best perception of system performance in terms of their QoE. We propose a QoE...
Given the elasticity, dynamicity and on-demand nature of the cloud, cloud-based applications require dynamic models for Quality of Service (QoS), especially when the sensitivity of QoS tends to fluctuate at runtime. These models can be autonomically used by the cloud-based application to correctly self-adapt its QoS provision. We present a novel dynamic and self-adaptive sensitivity-aware QoS modeling...
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