Statistical Multiplexing and Traffic Shaping Games for Network Slicing

Next generation wireless architectures are expected to enable slices of shared wireless infrastructure which are customized to specific mobile operators/services. Given infrastructure costs and the stochastic nature of mobile services' spatial loads, it is highly desirable to achieve efficient statistical multiplexing amongst such slices. We study a simple dynamic resource sharing policy which allocates a 'share' of a pool of (distributed) resources to each slice-Share Constrained Proportionally Fair (SCPF). We give a characterization of SCPF's performance gains over static slicing and general processor sharing. We show that higher gains are obtained when a slice's spatial load is more 'imbalanced' than, and/or 'orthogonal' to, the aggregate network load, and that the overall gain across slices is positive. We then address the associated dimensioning problem. Under SCPF, traditional network dimensioning translates to a coupled share dimensioning problem, which characterizes the existence of a feasible share allocation given slices' expected loads and performance requirements. We provide a solution to robust share dimensioning for SCPF-based network slicing. Slices may wish to unilaterally manage their users' performance via admission control which maximizes their carried loads subject to performance requirements. We show this can be modeled as a 'traffic shaping' game with an achievable Nash equilibrium. Under high loads, the equilibrium is explicitly characterized, as are the gains in the carried load under SCPF vs. static slicing. Detailed simulations of a wireless infrastructure supporting multiple slices with heterogeneous mobile loads show the fidelity of our models and range of validity of our high load equilibrium analysis

Constrained Network Slicing Games: Achieving service guarantees and network efficiency

Network slicing is a key capability for next generation mobile networks. It enables one to cost effectively customize logical networks over a shared infrastructure. A critical component of network slicing is resource allocation, which needs to ensure that slices receive the resources needed to support their mobiles/services while optimizing network efficiency. In this paper, we propose a novel approach to slice-based resource allocation named Guaranteed seRvice Efficient nETwork slicing (GREET). The underlying concept is to set up a constrained resource allocation game, where (i) slices unilaterally optimize their allocations to best meet their (dynamic) customer loads, while (ii) constraints are imposed to guarantee that, if they wish so, slices receive a pre-agreed share of the network resources. The resulting game is a variation of the well-known Fisher market, where slices are provided a budget to contend for network resources (as in a traditional Fisher market), but (unlike a Fisher market) prices are constrained for some resources to provide the desired guarantees. In this way, GREET combines the advantages of a share-based approach (high efficiency by flexible sharing) and reservation-based ones (which provide guarantees by assigning a fixed amount of resources). We characterize the Nash equilibrium, best response dynamics, and propose a practical slice strategy with provable convergence properties. Extensive simulations exhibit substantial improvements over network slicing state-of-the-art benchmarks

Dynamic Pricing for Tenants in an Automated Slicing Marketplace

The paradigm shift from a one-size-fits-all architecture to a service-oriented network infrastructure promised by network slicing will demand novel technical solutions, as well as new business models. In particular, the role separation between infrastructure providers, i.e. the ones owning the network, and slice tenants, i.e. the ones providing specialized services tailored to their vertical segments, may encourage the definition of a shared platform (or marketplace) where the former can monetize their network infrastructure by leasing network resources at a market price, and the latter can rent on-demand the network resources needed to offer their services at the desired quality. This also enables the flexibility for the slice tenants to optimize the management of their slices by adapting their resource demand to fluctuations of their traffic or variations of the price in the market. In this paper, we extend the market mechanism scheme developed in previous works by including intra-slice radio admission control policies in the utility definition of the tenants in the slicing market game. Moreover, we characterize the mathematical properties of the game with respect to slice configuration, i.e. how diverse strategical behavior of the tenants affects the market operation, in terms of slice resource allocation and performance. Our analysis offers insights to the slice tenants on how they could reconfigure their techno-economic performance indicators in response to the dynamics of network and of the market, namely how to adapt their long-term (and/or real-time) strategies to the fluctuations of the traffic to enhance network performance and increase profits

Elastic Multi-resource Network Slicing: Can Protection Lead to Improved Performance?

In order to meet the performance/privacy requirements of future data-intensive mobile applications, e.g., self-driving cars, mobile data analytics, and AR/VR, service providers are expected to draw on shared storage/computation/connectivity resources at the network "edge". To be cost-effective, a key functional requirement for such infrastructure is enabling the sharing of heterogeneous resources amongst tenants/service providers supporting spatially varying and dynamic user demands. This paper proposes a resource allocation criterion, namely, Share Constrained Slicing (SCS), for slices allocated predefined shares of the network's resources, which extends the traditional alpha-fairness criterion, by striking a balance among inter- and intra-slice fairness vs. overall efficiency. We show that SCS has several desirable properties including slice-level protection, envyfreeness, and load driven elasticity. In practice, mobile users' dynamics could make the cost of implementing SCS high, so we discuss the feasibility of using a simpler (dynamically) weighted max-min as a surrogate resource allocation scheme. For a setting with stochastic loads and elastic user requirements, we establish a sufficient condition for the stability of the associated coupled network system. Finally, and perhaps surprisingly, we show via extensive simulations that while SCS (and/or the surrogate weighted max-min allocation) provides inter-slice protection, they can achieve improved job delay and/or perceived throughput, as compared to other weighted max-min based allocation schemes whose intra-slice weight allocation is not share-constrained, e.g., traditional max-min or discriminatory processor sharing

Resource allocation for network slicing in mobile networks

This paper provides a survey of resource allocation for network slicing. We focus on two classes of existing solutions: (i) reservation-based approaches, which allocate resources on a reservation basis, and (ii) share-based approaches, which allocate resources based on static overall shares associated to individual slices. We identify the requirements that a slice-based resource allocation mechanism should satisfy, and evaluate the performance of both approaches against these requirements. Our analysis reveals that reservation-based approaches provide a better level of isolation as well as stricter guarantees, by enabling tenants to explicitly reserve resources, but one must pay a price in terms of efficiency unless reservations can be updated very dynamically; in particular, efficiency falls below 50\% when reservations are performed over long timescales. We provide further comparisons in terms of customizability, complexity, privacy and cost predictability, and discuss which approach might be more suitable depending on the network slices' characteristics. We also describe the additional mechanisms required to implement the desired resource allocations while meeting the latency and reliability requirements of the different slice types, and outline some issues for future work.The work of Albert Banchs was supported in part by the H2020 5G-TOURS European project under Grant 856950, and in part by the Spanish State Research Agency (TRUE5G project) under Grant PID2019-108713RB-C52/AEI/10.13039/501100011033. The work of Gustavo de Veciana was supported by NSF Grant CNS-1910112

Joint Pricing and Resources Allocation for 5G Network Slicing

International audienceSlicing is emerging as a promising technique to support new differentiated services in 5G networks. It provides the necessary flexility and scalability associated with future services. To maintain satisfactory services requirements and high profit for service providers, a slice may be designing according to the varying demands and resource availability. This paper develops a framework for resources allocation between slicing and business layer for multi-tenant slicing, e.g. virtual wireless operators, service providers and smart cities services. This paper proposes a flexible mechanism based on a biding scheme for slicing allocation, which achieve desirable fairness and efficiency among the network slices of the different tenants and their associated users. We then design a practical algorithms to realise the proposed desired solution. We also show through the simulation the efficiency of our approach in term of efficiency and fairness

Strategic Resource Management in 5G Network Slicing. (Invited paper)

International audienceNetwork Slicing is one of the essential concepts that has been introduced in 5G networks design to support demand expressed by next generation services. Network slicing will also bring new business opportunities for service providers (SPs) and virtual network operators, allowing them to run their virtual, independent business operations on shared physical infrastructure. We consider a marketplace where service providers (SPs) i.e., slice tenants lease the resources from an infrastructure provider (InP) through a network slicing mechanism. They compete to offer a certain communication service to end-users. We show that the competition between SPs can be model using the multiresource Tullock contest (TC) framework, where SPs exert effort by expending costly resource to attract users. We study the competition between the SPs under a static and dynamic resource sharing scheme. In a dynamic resource sharing scheme, SPs are pre-assigned with fixed shares (budgets) of infrastructure, and they are allowed to redistribute their shares and customise their allocation to maximise their profit. The decision problem of SPs is analysed using non-cooperative game theory, and it is shown that the resultant game admits a unique Nash Equilibrium (NE). Furthermore, a distributed reinforcement algorithm is proposed that allows each SP to reach the game's unique Nash equilibrium. Finally, simulations results are conducted to analyse the interaction between market players and the economic efficacy of the network sharing mechanism

Network slicing for guaranteed rate services: admission control and resource allocation games

Technologies that enable network slicing are expected to be a key component of next generation mobile networks. Their promise lies in enabling tenants (such as mobile operators and/or services) to reap the cost and performance benefits of sharing resources while retaining the ability to customize their own allocations. When employing dynamic sharing mechanisms, tenants may exhibit strategic behavior, optimizing their choices in response to those of other tenants. This paper analyzes dynamic sharing in network slicing when tenants support inelastic users with minimum rate requirements. We propose a NEtwork Slicing (NES) framework combining: 1) admission control; 2) resource allocation; and 3) user dropping. We model the network slicing system with admitted users as a NES game; this is a new class of game where the inelastic nature of the traffic may lead to dropping users whose requirements cannot be met. We show that, as long as admission control guarantees that slices can satisfy the rate requirements of all their users, this game possesses a Nash equilibrium. Admission control policies (a conservative and an aggressive one) are considered, along with a resource allocation scheme and a user dropping algorithm, geared at maintaining the system in Nash equilibria. We analyze our NES framework's performance in equilibrium, showing that it achieves the same or better utility than static resource partitioning, and bound the difference between NES and the socially optimal performance. Simulation results confirm the effectiveness of the proposed approach.The work of University of Texas at Austin was supported in part by a gift from Cisco. The work of University Carlos III of Madrid was supported by the H2020 5G-MoNArch project (Grant Agreement No. 761445) and the 5GCity project of the Spanish Ministry of Economy and Competitiveness (TEC2016-76795-C6-3-R). The work of NEC Europe Ltd. was supported by the H2020 5G-Transformer project (Grant agreement no. 761536)