Joint Resource Allocation and Content Caching in Virtualized Content-Centric Wireless Networks

Efficient content caching plays a crucial role in quality of service enhancement and congestion mitigation of the backhaul and core networks for the fifth-generation (5G) wireless network, which must support a large amount of multimedia and video content. Wireless network virtualization provides a n...

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Veröffentlicht in:IEEE access 2018-01, Vol.6, p.11329-11341
Hauptverfasser: Tran, Thinh Duy, Le, Long Bao
Format: Artikel
Sprache:eng
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Zusammenfassung:Efficient content caching plays a crucial role in quality of service enhancement and congestion mitigation of the backhaul and core networks for the fifth-generation (5G) wireless network, which must support a large amount of multimedia and video content. Wireless network virtualization provides a novel paradigm shift in 5G system design which enables to better utilize network resources, rapid development of new services, and reduce the operation cost. Harmonized deployment of a content caching strategy in the virtualized wireless network environment, however, requires a suitable radio resource allocation framework to realize the great benefits of these technologies. In this paper, we study the joint resource allocation and content caching problem which aims to efficiently utilize the radio and content storage resources in the highly congested backhaul scenario. In this design, we minimize the maximum content request rejection rate experienced by users of different mobile virtual network operators in different cells, which results in a mixed-integer non-linear program. We solve this difficult optimization problem by proposing a bisection-search-based algorithm that iteratively optimizes the resource allocation and content caching placement. We further propose a low-complexity heuristic algorithm which achieves moderate performance loss compared to the bisection-search based algorithm. Extensive numerical results confirm the efficacy of our proposed framework which significantly reduces the maximum request outage probability compared with other benchmark algorithms.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2804902