Joint Resource Allocation and Content Caching in Virtualized Content-Centric Wireless Networks
Author(s) -
Thinh Duy Tran,
Long Bao Le
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2804902
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
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.
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