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.
Moreover, @cite_1 , @cite_6 , and @cite_0 focused on deployment of network slicing over the RAN architecture of mobile networks. Authors in @cite_1 analyzed network slicing in multi-cell RAN in order to support radio resource splitting among various slices. This paper further proposed four types of RAN slicing approaches along with their detailed comparison. However, authors in @cite_6 explained how network slicing may impact various aspects of design and functions of RAN architecture of 5G mobile networks. The paper thoroughly covered RAN requirements for network slicing implementation. In @cite_0 , authors provided a comprehensive discussion on deployment of network slicing in heterogeneous Cloud-RAN (C-RAN) in order to improve throughput through computation and communication resource sharing.
@cite_0 @cite_1 @cite_6
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Network slicing addresses the deployment of multiple logical networks as independent business operations on a common physical infrastructure. The concept has initially been proposed for the 5 th Generation (5G) core network (CN) however, it has not been investigated yet what network slicing would represent to the design of the 5G radio access network (RAN). The paper explains how network slicing may impact several aspects of the 5G RAN design such as the protocol architecture, the design of network functions (NFs) and the management framework that needs to support both the management of the infrastructure to be shared among the slices and the slice operation. Network slicing is a fundamental capability for future 5G networks to properly support current and envisioned future application scenarios. Network slicing facilitates a cost-effective deployment and operation of multiple logical networks over a common physical network infrastructure such that each network is customized to best serve the needs of specific applications (e.g., mobile broadband, Internet of Things applications) and or communications service providers (e.g., special purpose service providers for different sectors such as public safety, utilities, smart city, and automobiles). Slicing a RAN becomes particularly challenging due to the inherently shared nature of the radio channel and the potential influence that any transmitter may have on any receiver. In this respect, this article analyzes the RAN slicing problem in a multi-cell network in relation to the RRM functionalities that can be used as a support for splitting the radio resources among the RAN slices. Four different RAN slicing approaches are presented and compared from different perspectives, such as the granularity in the assignment of radio resources and the degrees of isolation and customization. Radio access network (RAN) slicing is an effective methodology to dynamically allocate networking resources in 5G networks. One of the main challenges of RAN slicing is that it is provably an NP-Hard problem. For this reason, we design near-optimal low-complexity distributed RAN slicing algorithms. First, we model the slicing problem as a congestion game, and demonstrate that such game admits a unique Nash equilibrium (NE). Then, we evaluate the Price of Anarchy (PoA) of the NE, i.e., the efficiency of the NE as compared with the social optimum, and demonstrate that the PoA is upper-bounded by 3 2. Next, we propose two fully-distributed algorithms that provably converge to the unique NE without revealing privacy-sensitive parameters from the slice tenants. Moreover, we introduce an adaptive pricing mechanism of the wireless resources to improve the network owner’s profit. We evaluate the performance of our algorithms through simulations and an experimental testbed deployed on the Amazon EC2 cloud, both based on a real-world dataset of base stations from the OpenCellID project. Results conclude that our algorithms converge to the NE rapidly and achieve near-optimal performance, while our pricing mechanism effectively improves the profit of the network owner. Network slicing represents a new paradigm to operate mobile networks. With network slicing, the underlying infrastructure is "sliced" into logically separate networks that can be customized to the specific needs of their tenant. Hands-on experiments on this technology are essential to understand its benefits and limits, and to validate the design and deployment choices. While some network slicing prototypes have been built for RANs, leveraging on the wide availability of radio hardware and open source software, there is currently no open source suite for end-to-end network slicing available to the research community. In this article we fill this gap by developing an end-to-end network slicing protocol stack, POSENS, which relies on a slice-aware shared RAN solution. We design the required algorithms and protocols, and provide a full implementation leveraging on state-of-the-art software components. We validate the effectiveness of POSENS in achieving tenant isolation and network slices customization, showing that no price in performance is paid toward this end. We believe that our tool will prove very useful to researchers and practitioners working on this novel architectural paradigm.