Motivated by the potentially high downlink traffic demands of commuters in future autonomous vehicles, we study a network architecture where vehicles use Vehicle-to-Vehicle (V2V) links to form relay network clusters, which in turn use Vehicle-to-Infrastructure (V2I) links to connect to one or more Road Side Units (RSUs). Such cluster-based multihoming offers improved performance, e.g., in coverage and per user shared rate, but depends on the penetration of V2V+V2I capable vehicles and possible blockage, by legacy vehicles, of line of sight based V2V links, such as those based on millimeter-wave and visible light technologies. This paper provides a performance analysis of a typical vehicle's connectivity and throughput on a highway in the free-flow regime, exploring its dependence on vehicle density, sensitivity to blockages, number of lanes and heterogeneity across lanes. The results, backed up by simulations of realistic vehicular traffic, show that even with moderate vehicle densities and penetration of V2V+V2I capable vehicles, such architectures can achieve substantial improvements in connectivity and reduction in per-user rate variability as compared to V2I based networks. The typical vehicle's performance is also shown to improve considerably in the multilane highway setting as compared to a single lane road. This paper also sheds light on how the network performance is affected when vehicles can control their relative positions, by characterizing the connectivity-throughput tradeoff faced by the clusters of vehicles.

This paper focuses on optimizing resource allocation amongst a set of tenants, network slices, supporting dynamic customer loads over a set of distributed resources, e.g., base stations. The aim is to reap the benefits of statistical multiplexing resulting from flexible sharing of `pooled' resources, while enabling tenants to differentiate and protect their performance from one another's load fluctuations. To that end we consider a setting where resources are grouped into Virtual Resource Pools (VRPs) wherein resource allocation is jointly and dynamically managed. Specifically for each VRP we adopt a Share-Constrained Proportionally Fair (SCPF) allocation scheme where each tenant is allocated a fixed share (budget). This budget is to be distributed equally amongst its active customers which in turn are granted fractions of their associated VRP resources in proportion to customer shares. For a VRP with a single resource, this translates to the well known Generalized Processor Sharing (GPS) policy. For VRPs with multiple resources SCPF provides a flexible means to achieve load elastic allocations across tenants sharing the pool. Given tenants' per resource shares and expected loads, this paper formulates the problem of determining optimal VRP partitions which maximize the overall expected shared weighted utility while ensuring protection guarantees. For a high load/capacity setting we exhibit this network utility function explicitly, quantifying the benefits and penalties of any VRP partition, in terms of network slices' ability to achieve performance differentiation, load balancing, and statistical multiplexing. Although the problem is shown to be NP-Hard, a simple greedy heuristic is shown to be effective. Analysis and simulations confirm that the selection of optimal VRP partitions provide a practical avenue towards improving network utility in network slicing scenarios with dynamic loads.

Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered as a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the share-constrained proportional allocation mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, for elastic traffic, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same or better performance than that of a static partitioning of resources, thus providing the same level of protection as static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fills a gap in the analysis of this resource allocation model under strategic players.

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 among 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 that 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 versus static slicing. Detailed simulations of a wireless infrastructure supporting multiple slices with heterogeneous mobile loads show the fidelity of our models and the range of validity of our high-load equilibrium analysis.

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.

Network slicing to enable resource sharing among multiple tenants-network operators and/or services-is considered a key functionality for next generation mobile networks. This paper provides an analysis of a well-known model for resource sharing, the `share-constrained proportional allocation' mechanism, to realize network slicing. This mechanism enables tenants to reap the performance benefits of sharing, while retaining the ability to customize their own users' allocation. This results in a network slicing game in which each tenant reacts to the user allocations of the other tenants so as to maximize its own utility. We show that, under appropriate conditions, the game associated with such strategic behavior converges to a Nash equilibrium. At the Nash equilibrium, a tenant always achieves the same, or better, performance than under a static partitioning of resources, hence providing the same level of protection as such static partitioning. We further analyze the efficiency and fairness of the resulting allocations, providing tight bounds for the price of anarchy and envy-freeness. Our analysis and extensive simulation results confirm that the mechanism provides a comprehensive practical solution to realize network slicing. Our theoretical results also fill a gap in the literature regarding the analysis of this resource allocation model under strategic players.

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 network 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 the achievable performance gains over static slicing, showing higher gains when a slice's spatial load is more `imbalanced' than, and/or `orthogonal' to, the aggregate network load. Under SCPF, traditional network dimensioning translates to a coupled share dimensioning problem, addressing 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.

This paper addresses the slicing of radio access network resources by multiple tenants, e.g., virtual wireless operators and service providers. We consider a criterion for dynamic resource allocation amongst tenants, based on a weighted proportionally fair objective, which achieves desirable fairness/protection across the network slices of the different tenants and their associated users. Several key properties are established, including: the Pareto-optimality of user association to base stations, the fair allocation of base stations' resources, and the gains resulting from dynamic resource sharing across slices, both in terms of utility gains and capacity savings. We then address algorithmic and practical challenges in realizing the proposed criterion. We show that the objective is NP-hard, making an exact solution impractical, and design a distributed semi-online algorithm, which meets performance guarantees in equilibrium and can be shown to quickly converge to a region around the equilibrium point. Building on this algorithm, we devise a practical approach with limited computational information and handoff overheads. We use detailed simulations to show that our approach is indeed near-optimal and provides substantial gains both to tenants (in terms of capacity savings) and end users (in terms of improved performance).

The traditional model of single ownership of the mobile network infrastructure is being challenged by the forecasted mobile data tsunami and the resulting CAPEX and OPEX costs. In this context, the sharing of network infrastructure among operators has emerged as a way to ensure operators' future cost competitiveness. While the elementary concepts related to passive network sharing are already being exploited today, active network sharing is raising in importance to enable further reduction of network expenses in a substantial and sustainable way. The work presented in this paper addresses this challenge by designing a RAN Multi- tenant cell Slicing Controller (RMSC) that allows to flexibly share the RAN resources among multiple virtual operators (tenants). Three different possible designs for the RMSC controller are proposed, ranging from a fully distributed system with no inter-base station communication to a fully centralized solution with all information available. The proposed solutions are benchmarked against a distributed static slicing solution and a centralized load balancing solution, considering realistic scenarios of uneven user location distribution per tenant. The performance results obtained indicate that the proposed RMSC schemes can significantly outperform traditional solutions for multi-tenant mobile networks.