Content service has become the most popular service that occupies plenty of caching and networking resources. In order to deliver content to end users with high QoE and low infrastructure cost, network function virtualization is deemed as a promising solution for operators to provide content service with geographically dispersed nodes in large scale, which paves the way towards the virtualized content network. In this paper, from the point of view of information-centric networking and service provision, an information-centric virtual content network (IVCN) slicing framework is proposed. A method on the VNF partition from the point of view of information-centric networking and service provision is put forward. The service function chaining and optimization of IVCN are investigated both on the data plane and on the control plane. The IVCN slicing is modeled as a use case in heterogeneous fog-enabled RAN. A method of performance optimization on the IVCN slicing is proposed based on SFC, which aims to optimize the mapping of virtual network functions and virtual content placement. A heuristic approach called IVCN-RANO is proposed to solve the NP-hard problem based on ant colony optimization algorithm. The performance of the IVCN-RANO is evaluated comparing with CEE-LRU, Prob-LRU, and popularity-based schemes. The simulation results reveal that IVCN-RANO outperforms on performances including hit rate, average weighted hops, and average content redundancy. INDEX TERMS Fog computing, content network, network function virtualization, service function chain, heterogeneous radio access network.
With the development of smart mobile devices and various mobile applications, content-oriented service has become the most popular service which occupies network resources and results in high traffic load. In order to improve quality of experience in radio access network and reduce the OpEx and CapEx of operators, wireless network virtualization and network slicing come into the vision and are deemed as promising solutions to radio access networks to provide tailored services. Therefore, network slicing and optimization based on content-oriented service become a challenging research direction. In this paper, network slicing and resource optimization on content-oriented application in cache-enabled hybrid radio access network based on complex network are investigated. A Cooperative Network Slicing Framework Based on Content in RAN (CNSC-RAN) is presented. Based on CNSC-RAN, procedures of content-oriented static network slicing and dynamic slicing are proposed. Content-oriented slicing is modeled and analyzed which includes slicing on content cache resources and communication resources. In order to obtain the optimized resources sliced for each content, the optimization problem is formulated to minimize the average system cost to get the contents required by users. The problem is solved by a heuristic algorithm called CCSOA (Content-Centric Slicing Optimization Algorithm) in a dynamic content-oriented network slicing procedure enabling UEs with self-evicting contents. The performance of CCSOA is evaluated by performance metrics including hit rate, average cache occupation, average system cost, and request traffic reduction to macro cell base station comparing with CEE and ProbCache. Simulation results reveal the effectiveness of CCSOA.
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