Data-driven multimedia edge network and content delivery

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Abstract

Recently, network multimedia has undergone rapid developments. Compared with traditional end-to-end multimedia content services, user behaviors in emerging mobile multimedia services have experienced fundamental changes. For efficient mobile multimedia content services, the conventional content distribution architecture relies on a centralized infrastructure, in which global popularity trends cannot be effectively obtained. The use of edge network architecture combined with data-driven strategies to aid the dynamic mobile multimedia content has become a new choice for improved service quality. Using data-driven and cross-domain collaboration methods, this paper reveals a set of principles of mobile multimedia content service and system architecture design. This paper first discusses data-driven behavior patterns and network performance analysis. It shows the essential difference between edge multimedia content distribution and traditional content distribution. Further, this paper presents general edge multimedia research methodologies, including a framework of multimedia edge network content distribution using data-driven and cross-domain collaboration methods. Finally, this paper provides several representative frameworks, including SocialCDN, which uses social information for content distribution, CPCDN, in which a content-provider-based content delivery framework is proposed, EdgeCDN, which is an edge content delivery framework, and finally CrowdCDN, which uses user-based crowdfunding resources for efficient content distribution.

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APA

Zhu, W., & Wang, Z. (2021). Data-driven multimedia edge network and content delivery. Scientia Sinica Informationis, 51(3), 468–504. https://doi.org/10.1360/SSI-2020-0008

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