MM3C: Multi-Source Mobile Streaming in Cache-Enabled Content-Centric Networks

Mau, Dung Ong; Taleb, Tarik; Chen, Min

doi:10.1109/glocom.2015.7417045

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…3) Web acceleration: A Web-page may contain large files in size, which may affect the loading time of the Webpage. A CDN-based edge can help reducing the loading time by caching particular content [55]. Once content is stored in the CDN edge, it can no longer change.…”

Section: Web Performance Enhancementsmentioning

confidence: 99%

On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

Taleb

Samdanis

Mada

et al. 2017

IEEE Commun. Surv. Tutorials

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1,510

746

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Multi-access edge computing (MEC) is an emerging ecosystem, which aims at converging telecommunication and IT services, providing a cloud computing platform at the edge of the radio access network. MEC offers storage and computational resources at the edge, reducing latency for mobile end users and utilizing more efficiently the mobile backhaul and core networks. This paper introduces a survey on MEC and focuses on the fundamental key enabling technologies. It elaborates MEC orchestration considering both individual services and a network of MEC platforms supporting mobility, bringing light into the different orchestration deployment options. In addition, this paper analyzes the MEC reference architecture and main deployment scenarios, which offer multitenancy support for application developers, content providers, and third parties. Finally, this paper overviews the current standardization activities and elaborates further on open research challenges.

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Section: Web Performance Enhancementsmentioning

confidence: 99%

On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

Taleb

Samdanis

Mada

et al. 2017

IEEE Commun. Surv. Tutorials

Self Cite

1,510

746

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“…Mau et al integrated content centric network with caching scheme that works for mobile multimedia streaming and radio access networks. The congestion and trace load were controlled by avoiding unnecessary pathways/routes and request.…”

Section: Reviewmentioning

confidence: 99%

Efficient content retrieval in fog zone using Nano‐Caches

Singh

Kumar

Sharma

2019

Concurrency and Computation

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Summary It is always desired to improve the response time from cloud servers, which deliver contents without buffering. As the penetration of mobile/fog devices is increasing, the limits of cellular ranges come under question. This question arises in spite of the fact that the current Internet Service Providers and data operators are adding cellular towers frequently to reduce delay and enhance performance. This performance can be improved by increasing Nano‐Cache(s) at the edges of the network for forwarding interrelated contents to remote corner of the earth. In this research work, Nano‐Caches are integrated for delivering contents efficiently, using search‐based optimization techniques, which are energy and response aware in nature. An algorithm, namely, Modified Teaching Learning‐Based Optimization(MTLBO), is devised and implemented in fog zone to find efficient route for forwarding contents using Nano‐Caches and subsequently to improve content retrieval time. Mathematical distribution model of traffic is used for simulation process. MTLBO is compared with existing algorithms, namely, Teaching Learning‐Based Optimization (TLBO) Algorithm and Simulated Annealing (SA) Algorithm. The design of experiments (DOE) was carried out to observe number of iterations, learning rate, and by changing the network size. Java library was used for observing values of memory and execution time. The results show that Modified Teaching Learning‐Based Optimization (MTLBO) approach is better than Teaching Learning‐Based Optimization (TLBO) approach as it has less overheads in terms of memory (considering number of fog caches) and network size for delivering contents at remote areas. In comparison to the Simulated Annealing (SA) algorithm, MTLBO performs better in terms of execution time, overhead in terms of memory, and scalability as function of network size.

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“…In-network storage is introduced in ICN to reduce the overall network traffic. Accordingly, data copies, called replicas, are dynamically created and cached within the network [10].…”

Section: Introductionmentioning

confidence: 99%

Integrated ICN and CDN Slice as a Service

Benkacem¹,

Bagaa²,

Taleb³

et al. 2018

2018 IEEE Global Communications Conference (GLOBECOM)

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In this article, we leverage Network Function Virtualization (NFV) and Multi-Access Edge Computing (MEC) technologies, proposing a system which integrates ICN (Information-Centric Network) with CDN (Content Delivery Network) to provide an efficient content delivery service. The proposed system combines the dynamic CDN slicing concept with the NDN (Named Data Network) based ICN slicing concept to avoid core network congestion. A dynamic CDN slice is deployed to cache content at optimal locations depending on the nature of the content and the geographical distributions of potential viewers. Virtual cache servers, along with supporting virtual transcoders, are placed across a cloud belonging to multiple-administrative domains, forming a CDN slice. The ICN slice is, in turn, used for the regional distribution of content, leveraging the namebased access and the autonomic in-network content caching. This enables the delivery of content from nearby network nodes, avoiding the duplicate transfer of content and also ensuring shorter response times. Our experiments demonstrate that integrated ICN/CDN is better than traditional CDN in almost all aspects, including service scalability, reliability, and quality of service.

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MM3C: Multi-Source Mobile Streaming in Cache-Enabled Content-Centric Networks

Cited by 5 publications

References 13 publications

On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration

Efficient content retrieval in fog zone using Nano‐Caches

Integrated ICN and CDN Slice as a Service

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