Network Slicing in 5G Mobile Communication Architecture, Profit Modeling, and Challenges

TL;DR

This paper discusses the concept, architecture, business implications, and challenges of network slicing in 5G, emphasizing its potential for efficient resource utilization and new profit models.

Contribution

It provides a comprehensive overview of network slicing architecture, focusing on profit modeling and addressing open research challenges in 5G networks.

Findings

Network slicing enables energy-efficient and cost-effective resource allocation.

Two profit models are analyzed: Own-Slice Implementation and Resource Leasing.

The paper highlights open challenges and future research directions in network slicing.

Abstract

Efficient flexibility and higher system scalability call for enhanced network performance, better energy consumption, lower infrastructure cost, and effective resource utilization. To accomplish this, an architectural optimization and reconstruction of existing cellular network is required. Network slicing is considered to be one of the key enablers and an architectural answer of communication system of 2020 and beyond. Traditional mobile operators provide all types of services to various kinds of customers through a single network, however, with the deployment of network slicing operators are now able to divide entire network into different slices each with its own configuration and specific Quality of Service (QoS) requirements. In a slice-based network, each slice will be considered as a separate logical network. In this way, the infrastructure utilization and resource allocation will be much more energy and cost efficient in comparison to traditional network. In this paper, we provided a comprehensive discussion on concept and system architecture of network slicing with particular focus on its business aspect and profit modeling. We throughly discussed two different dimensions of profit modeling, so called Own-Slice Implementation and Resource Leasing for Outsourced Slices. We further addressed open research directions and existing challenges with the purpose of motivating new advances and adding realistic solutions to this emerging technology.