IVCN: Information-Centric Network Slicing Optimization Based on NFV in Fog-Enabled RAN

Abstract

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.

A Review on Green Caching Strategies for Next Generation Communication Networks

“…NFV technique decouples different networking services from conventional hardware and utilize virtual machines to provide same service using software [224], [237]. A server can operate multiple virtual machines and ensure optimal utilization of resources.…”

“…A server can operate multiple virtual machines and ensure optimal utilization of resources. As a result, the deployment and configuration process of these services become not only less time consuming but also efficient and cost-effective [237]. Even the changes in user demands can be addressed instantly.…”

On the Feasibility of 5G Slice Resource Allocation With Spectral Efficiency: A Probabilistic Characterization

“…In particular, the problem of how to efficiently allocate the available radio resources to slices has attracted significant attention and can be studied at different layer levels, as pointed out by Sallent et al [17], [18] and in [19]. Strictly speaking, network slicing implies grouping network resources into different sets or slices with the objective of determining the number of resources that the slices require to meet service specifications, with allocated resources ranging from bandwidth to computing and storage [20]- [28] Nevertheless, a more global approach considers also the allocation of resources to users, i.e., the resources allocated to each slice are internally managed by its owner and assigned to final users. This allocation is known as intra-slice allocation, while the previous allocation of resources to slices is denoted as inter-slice allocation.…”

Optimization of Network-Based Caching and Forwarding Using Mobile Edge Computing

“…MEC can be thought of as a cloud server running on the edge of a mobile network to perform special tasks that are not possible in traditional network infrastructure. MEC transforms base stations into intelligent service centers that deliver highly personalized, diverse network services directly at the edge of the network and at the same time, optimal mobile network performance is ensured [30], [31]. MEC is the natural evolution of mobile base station development and the convergence of internet technology and telecommunications networks.…”