Cloud Computing and Quality of Service: Issues and Developments

Cloud computing is a dynamic information technology (IT) paradigm that delivers on demand computing resources to a user over a network infrastructure. The Cloud Service Provider (CSP) offers applications which can be accessed online to users. Such applications can be shared by more than one user. CSPs provides programming interfaces that allows customers to build and deploy applications on the cloud; as well as providing massive storage and computing infrastructure to users. Users usually have no control on how data is stored on the cloud or where the underlying resources are located. With this limited control, customers’ requirements and Quality of Service (QoS) expectations from CSPs are spelt out using a Service Level Agreement (SLA). It is thus imperative to have the adequate QoS guarantees from a CSP. This paper examines trends in the area of Cloud computing QoS and provides a guide for future research. A review and survey of existing works in literature is done in order to identify these Cloud QoS trends. The finding is that the ultimate expectation of any QoS metrics or model is the related to cost concern for both the CSP and user

Load-Balancing for Edge QoE-Based VNF Placement for OTT Video Streaming

© 2018 IEEE. Over The Top (OTT) service providers require platforms to support distributed, complex, cloud-oriented, scalable, micro-service based systems. Such systems require on-the-fly placement of Virtual Network Functions (VNF) to support streaming and transcoding of content based on QoE feedback provided by the end-user. This paper proposes a QoE Scheme to support on-the-fly virtual network functions deployment for OTT video streaming and transcoding. The QoE feedback considers limited cloud resources, transcoding requirements, throughput and latency. Both horizontal and vertical scaling strategies (including VM migration) are discussed to cover up availability and reliability of intermediate and edge Content Delivery Network (CDN) cache nodes

On the Load Balancing of Edge Computing Resources for On-Line Video Delivery

Online video broadcasting platforms are distributed, complex, cloud oriented, scalable, micro-service-based systems that are intended to provide over-the-top and live content to audience in scattered geographic locations. Due to the nature of cloud VM hosting costs, the subscribers are usually served under limited resources in order to minimize delivery budget. However, operations including transcoding require high-computational capacity and any disturbance in supplying requested demand might result in quality of experience (QoE) deterioration. For any online delivery deployment, understanding user's QoE plays a crucial role for rebalancing cloud resources. In this paper, a methodology for estimating QoE is provided for a scalable cloud-based online video platform. The model will provide an adeptness guideline regarding limited cloud resources and relate computational capacity, memory, transcoding and throughput capability, and finally latency competence of the cloud service to QoE. Scalability and efficiency of the system are optimized through reckoning sufficient number of VMs and containers to satisfy the user requests even on peak demand durations with minimum number of VMs. Both horizontal and vertical scaling strategies (including VM migration) are modeled to cover up availability and reliability of intermediate and edge content delivery network cache nodes