Maximizing Infrastructure Providers’ Revenue Through Network Slicing in 5G (original) (raw)

Admission Control and Resource Allocation in 5G Network Slicing

Anais Estendidos do XXXIX Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC Estendido 2021), 2021

This paper summarizes the research in the master thesis entitled "Admission Control and Resource Allocation in 5G Network Slicing". We propose two solutions, SARA and DSARA, based on Reinforcement Learning algorithms to learn the admission policy that optimizes the profit of providers. Resource allocation considers the QoS requirements. Results show the outstanding performance of our solutions to 5G Network Slicing in relation to profit and resource utilization.

Timely Admission Control for Network Slicing in 5G With Machine Learning

IEEE Access, 2021

For guaranteeing the strict requirements foreseen for 5G, network slicing has been proposed as a dynamic and scalable mechanism for the allocation of customized resources to service providers. Many solutions have been proposed in the literature for the scenario where multiple service providers share the same pool of resources, while the exclusive allocation to different providers is still an open issue due to the associated complexity. In this work, we define a policy-based admission mechanism for exclusive intraservice slice allocation, at fine and adaptable timescales. In particular, we consider the case where optimal admission strategies are pre-computed offline for network state conditions that are representative of typical traffic loads and resource availability. This offline phase is also used to train a Machine learning algorithm; a neural network (NN) learns the best admission policies from a more computationally expensive mechanism in previously studied network conditions. Thus, the NN is used for providing near-optimal admission decisions at runtime under network conditions for which no optimal policy has been computed. The potential of the 5G marketplace in terms of revenue and quality of service is demonstrated for the particular case of services with strict latency constraints by means of a proof of concept tested over network traces from a real network operator. Different strategies are compared for the computation of the admission strategies and results are provided in terms of efficiency in resource utilization, fairness to the service providers, network owners' revenue and complexity. This study confirms the feasibility of a policy-based approach for exclusive intra-service resource allocation, especially if computationally-efficient mechanisms are adopted in the case of missing information about network states. INDEX TERMS 5G networks, mobile networks, network slicing, admission control, machine learning, neural networks, clustering, Markov processes, pricing.

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

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.

5G Network Slicing -Revenue by Slice

Telecom Business Review, 2021

The majority of businesses have primarily relied on one shared network for non-critical work, including conference calls, email, online service portals, local office Wi-Fi, digital payments and other applications. However, as more devices require connectivity as part of the Internet of things (IoT), businesses are exploring connectivity use cases that align with high availability and scalability, charting the path to network slicing. Communication Service Providers (CSPs) are gearing to adopt/ explore new business potentials through end-to-end network slicing that will enable new and innovative use cases across all Industry verticals. From a business perspective, a slice can fulfil a specific business case or deliver focused outcomes for using a combination of all the relevant network resources, functions and other existing assets. When selecting target industry segments and corresponding use cases for CSPs, there are several things to consider. First of all, there needs to be a solid enterprise strategy around industries or verticals to target and the local market possibilities. With network slicing, CSPs can roll out services and support applications in quicker time to market mode, and this helps them address industry-specific services around Railways, Healthcare, Emergency services, Airways and Smart cities, to name a few. Slicing guarantees a certain level of QoS and allows service providers to configure the network to meet specific security needs. As service content varies across end customers, slicing provides more effortless scalability and simplified network management for enterprises. This paper captures the background, related work in network slicing, its benefits, delving into a few use cases, significant security issues and also highlighting its commercial potential.

Multi-Tenant Slicing for Spectrum Management on the Road to 5G

IEEE Wireless Communications, 2017

The explosive data traffic demand in the context of the 5G revolution has stressed the need for network capacity increase. As the network densification has almost reached its limits, mobile network operators are motivated to share their network infrastructure and the available resources through dynamic spectrum management. Although some initial efforts have been made to this direction by concluding sharing agreements at a coarse granularity (i.e., months or years), the 5G developments require fine timescale agreements, mainly enabled by network slicing. In this article, taking into account the radical changes foreseen for next generation networks, we provide a thorough discussion on the challenges that network slicing brings in the different network parts, while introducing a new entity capable of managing the end-to-end slicing in a coherent manner. In addition, according to the paradigm shift that operators share their resources in a common centralized pool, we design a cooperative game to study the potential cooperation aspects among the participants. The experimental results highlight the performance and financial gains achievable by operators through multi-tenant slicing, providing them with the necessary incentives for network upgrade towards 5G.

Game theory for B5G upper-tier resource allocation using network slicing

Wireless Networks

Network slicing (NS) has emerged as a promising solution that enables network operators to slice network resources such as spectrum and bandwidth to adapt to different beyond 5G scenarios. This allows new operators to enter the market: the infrastructure provider (InP), who owns the infrastructure, and the mobile virtual network operator (MVNO), who may purchase a resource slice from the InP to provide a specific service to their end-users. To better deal with the resource allocation problem, efficient algorithms and methods have been done such as the auction model, bidding method, and game theory. This paper presents an upper-tier resource allocation based on game theory. This mechanism considers a single base station (BS) and multi MVNOs-users that share aggregated bandwidth radio access networks to maximize utilized BS resources. The proposed method takes both the bandwidth utilization of BS and the service requirements of MVNO users. Accordingly, the Game Theory solution takes two contradictory objectives: the InP aims to maximize its revenue while the MVNOs want to serve their users by paying the minimum amount. We prove that our proposal achieves an optimal solution from both InP and MVNOs' in terms of revenue and quality of service .

Optimization of the implementation of network slicing in 5G RAN

2018 IEEE Middle East and North Africa Communications Conference (MENACOMM)

Network slicing enables an infrastructure provider (InP) to support heterogeneous 5G services over a common platform (i.e., by creating a customized slice for each service). Once in operation, slices can be dynamically scaled up/down to match the variation of their service requirements. An InP generates revenue by accepting a slice request. If a slice cannot be scaled up when required, an InP has to also pay a penalty (proportional to the level of service degradation). It becomes then crucial for an InP to decide which slice requests should be accepted/rejected in order to increase its net profit. This paper presents a slice admission strategy based on reinforcement learning (RL) in the presence of services with different priorities. The use case considered is a 5G flexible radio access network (RAN), where slices of different mobile service providers are virtualized over the same RAN infrastructure. The proposed policy learns which are the services with the potential to bring high profit (i.e., high revenue with low degradation penalty), and hence should be accepted. The performance of the RL-based admission policy is compared against two deterministic heuristics. Results show that in the considered scenario, the proposed strategy outperforms the benchmark heuristics by at least 55%. Moreover, this paper shows how the policy is able to adapt to different conditions in terms of: (i) slice degradation penalty vs. slice revenue factors, and (ii) proportion of high vs. low priority services.

A Survey on Slice Admission Control Strategies and Optimization Schemes in 5G Network

IEEE Access, 2020

The Fifth Generation(5G) communication network is envisioned to provide heterogeneous services tailored to specific user demands. These services are diverse and can be generally categorized based on latency, bandwidth, reliability, and connection density requirements. The 5G infrastructure providers are expected to employ network function virtualization, software-defined networking, and network slicing for cost-effective and efficient network resource allocation. In the 5G network, when an infrastructure provider receives a slice request, a slice admission control scheme is applied and an optimization algorithm is used to achieve predefined objectives. To this end, a number of slice admission control objectives, strategies and algorithms have been proposed. However, there is a need to present a coherent review and bridge the gap between many aspects of slice admission control. In this paper, we present the latest developments in this research area. Thus, we begin by introducing slice admission control and discuss background concepts associated with slicing.We then extend our discussion to slice admission objectives followed by the strategies and optimization algorithms. Finally, we conclude with a summary of analysis containing the optimization algorithms.

From Network Sharing to Multi-tenancy: The 5G Network Slice Broker

The ever-increasing traffic demand is pushing network operators to find new cost-efficient solutions towards the deployment of future 5G mobile networks. The network sharing paradigm was explored in the past and partially deployed. Nowadays, advanced mobile network multi-tenancy approaches are increasingly gaining momentum paving the way towards further decreasing Capital Expenditures and Operational Expenditures (CAPEX/OPEX) costs, while enabling new business opportunities. This paper provides an overview of the 3GPP standard evolution from network sharing principles, mechanisms and architectures to future on-demand multi-tenant systems. In particular, it introduces the concept of the 5G Network Slice Broker in 5G systems, which enables mobile virtual network operators, over-the-top providers and industry vertical market players to request and lease resources from infrastructure providers dynamically via signaling means. Finally, it reviews the latest standardization efforts considering remaining open issues for enabling advanced network slicing solutions taking into account the allocation of virtualized network functions based on ETSI NFV, the introduction of shared network functions and flexible service chaining.