Heuristics for the Design and Optimization of Streaming Content Distribution Networks

Bhulai, Sandjai; Mei, Rob van der; Wu, Mengxiao

doi:10.1109/glocom.2007.402

Cited by 2 publications

(3 citation statements)

References 22 publications

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“…The network performance parameters are either included in the objective function or considered as constraints. In this regard, latency [43] , hop-count [44], available bandwidth [45] and link quality [46] are the network parameters considered by the replica server placement algorithms proposed for CDNs.…”

Section: B Network Related Parametersmentioning

confidence: 99%

“…In [43] and [44], algorithms are proposed to address placement of streaming servers with optimized QoS. The placement involves optimally deciding the number and location of streaming servers to deliver the streaming content to end-users, such that the QoS is minimized.…”

Section: A Qos Awarementioning

confidence: 99%

“…In case of multicast, content distribution trees are built, which are rooted at the streaming servers and end-users are considered as the leaves of the trees. Bhulai et al [43] addresses the placement of streaming servers in CDN by considering two delivery protocols: Periodic Broadcast (PB) protocol and Hierarchical Multicast Stream Merging (HMSM) protocol. For PB protocol, the QoS metric is computed based on hop-count of the edges in the delivery trees.…”

Section: A Qos Awarementioning

confidence: 99%

See 2 more Smart Citations

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Sahoo

Salahuddin

Glitho

et al. 2017

IEEE Commun. Surv. Tutorials

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This paper has been accepted for publication in IEEE Communications Surveys and Tutorials. The copyrights are with IEEE. Abstract: Content Delivery Networks (CDNs) have gained immense popularity over the years. Replica server placement is a key design issue in CDNs. It entails placing replica servers at meticulous locations, such that cost is minimized and Quality of Service (QoS) of end-users is satisfied. Many replica server placement models have been proposed in the literature of traditional CDN. As the CDN architecture is evolving through the adoption of emerging paradigms, such as, cloud computing and Network Functions Virtualization (NFV), new algorithms are being proposed. In this paper, we present a comprehensive survey of replica server placement algorithms in traditional and emerging paradigm based CDNs. We categorize the algorithms and provide a summary of their characteristics. Besides, we identify requirements for an efficient replica server placement algorithm and perform a comparison in the light of the requirements. Finally, we discuss potential avenues for further research in replica server placement in CDNs.

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Section: B Network Related Parametersmentioning

confidence: 99%

Section: A Qos Awarementioning

confidence: 99%

Section: A Qos Awarementioning

confidence: 99%

See 1 more Smart Citation

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Sahoo

Salahuddin

Glitho

et al. 2017

IEEE Commun. Surv. Tutorials

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Dynamic QoE optimisation for streaming content in large-scale future networks

Famaey

Vleeschauwer

Wauters

et al. 2009

2009 IFIP/IEEE International Symposium on Integrated Network Management-Workshops

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Multimedia content sharing services, such as YouTube, usually offer only low quality video streams. Additionally, it is expected the popularity of these services will increase even further in the future. Therefore, current streaming- content delivery architectures, with centralised searching and management components, might not be able to keep up with the ever-growing user bases. In this paper, we propose a scalable and fully distributed end- to-end architecture for delivering streaming multimedia content. Additionally, we designed several algorithms that allow content servers to intelligently adapt content quality to the available access-link bandwidth and server resources. In this way, the service can improve quality of experience, by offering higher bit-rates at times of low load, while still being able to satisfy as many content requests as possible when the load increases. In depth simulations were performed to validate and evaluate these algorithms. The results show that the proposed platform is capable of increasing delivered stream quality and accepted content requests in various large-scale scenarios

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Heuristics for the Design and Optimization of Streaming Content Distribution Networks

Cited by 2 publications

References 22 publications

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Dynamic QoE optimisation for streaming content in large-scale future networks

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