As part of 3GPP releases 15 and 16 Wi-Fi networks have been integrated with the 5G Core, which is a key feature in private network scenarios. Another important feature for private networks is multi-tenancy, whereby an infrastructure provider shares a common radio access network among several tenants subject to service level agreements (SLAs). 3GPP has defined network slicing on the radio access segment supporting multi-tenancy for 5GNR, but a similar feature is lacking in Wi-Fi networks. In this paper we present G-ADRR, which, to be best of our knowledge, is the first global slicing policy for Wi-Fi that delivers per-tenant radio level SLAs over a given geographical area. We extensively evaluate the performance of G-ADRR by means of an experimental prototype and packet level simulations, and demonstrate its advantages as compared to two alternative global scheduling strategies and a static slice configuration policy commonly used in the state-of-the-art.

Software Defined Wireless Networks offer an opportunity to enhance the performance of specific services by applying centralized mechanisms which make use of a global view of the network resources. This paper presents FALCON, a novel solution that jointly optimizes fair airtime allocation and rate recommendations for Server and Network Assisted DASH video streaming, providing proportional fairness among the clients. Since this problem is NP-hard, FALCON introduces a novel heuristic algorithm that is proved to achieve almost optimal results in a practical amount of time. The performance of FALCON is evaluated when used in conjunction with three referent Adaptive Bit Rate strategies (PANDA, BOLA and RobustMPC) in a simulated ultra-dense In-flight Entertainment System scenario. The obtained results show that FALCON provides significant benefits by minimizing instability and buffer underruns, while obtaining a fair video rate and airtime allocation among clients, thus contributing to an enhanced Quality of Experience.

To deliver on the vision of network slicing, future 5G networks will have to provide virtualization and isolation for a variety of Radio Access Network (RAN) technologies. In this paper we study how to implement RAN slicing in Wi-Fi networks. In particular, we present a scheduling algorithm that allocates airtime through a set of virtual Wi-Fi interfaces executing on the same or different physical radios, in order to fulfill each tenant's Service Level Agreement. We demonstrate a practical implementation of our scheduler on Linux systems based on the mac80211 driver that contrary to other existing solutions is independent from underlying hardware drivers. Finally, we experimentally evaluate the performance of our scheme through a set of realistic experiments.

Dense deployments of small cells (SCs) are key to fulfill the capacity requirements of future 5G networks. However, two roadblocks to the adoption of SCs are: 1) the limited availability and the cost of sites with wired backhaul resources and 2) the complexity to manage a dense deployment of wireless backhaul nodes. Towards these challenges we propose SODALITE, a novel system that applies software-defined networking (SDN) to a wireless backhaul network. We present, how SODALITE can be integrated to 3GPP's 4G and 5G architectures, and show the feasibility of SODALITE through LTE network testbed experiments. We substantiate the scalability of SODALITE through stochastic studies using real-life traffic traces from an LTE network and discuss the effects of cell densification and 5G system architecture on these studies. Further, a reliable backhauling solution for wireless links is introduced in SODALITE through SDN-enabled mechanisms that are capable of reconfiguring the data plane upon a link failure detection. Its reliability is shown through experiments on an LTE network testbed, and studied thoroughly via rigorous simulations and network emulator evaluations. As a result, we claim that SODALITE is a promising carrier-grade system to manage a wireless SC backhaul.

In this paper we present SWAM, a system that builds on commodity Wi-Fi routers with multiple wireless interfaces to provide a wireless access infrastructure supporting multi-tenancy, mobility, and integrated wireless access and backhaul. An infrastructure provider can deploy inexpensive SWAM nodes to cover a given geographical area providing on-demand connectivity for Mobile Network Operators. Our main contribution is the design of the SWAM datapath and control plane, which are inspired by the overlay techniques used to enable multi-tenancy in data-center networks. We prototype SWAM in an office wireless testbed and validate experimentally its functionality.

Dense Small Cell networks are considered the most effective way to cope with the exponential increase in mobile traffic demand expected for the upcoming years and are one of the foundations of the future 5G. However, novel architectures are required to enable cost-efficient deployments of very dense outdoor Small Cell networks, complementing the coverage layer provided by macro-cells. In this regard, two important challenges need to be solved to make this vision a reality: i) increased traffic dynamics, which are translated into more frequent handovers, and ii) cost-efficient deployment of large number of Small Cells. In this paper we propose and evaluate SENSEFUL, an novel architecture addressing the two problems highlighted above: Software-Defined Networking (SDN) as the key technology to promote adaptability to a varying environment and provide efficient mobility solutions in the dense access layer, and novel wireless backhauling technologies where traditional wired connectivity does not meet cost/efficiency restrictions.

The Constrained Application Protocol (CoAP) is a new Web protocol for the Internet of Things that allows to connect IoT devices directly to services hosted in the cloud. CoAP is based on UDP to better fit the requirements of constrained environments with resource-constrained nodes and low-power communication links. Being an Internet protocol, CoAP must still adhere to congestion control, primarily to keep the backbone network stable. Thus, the base specification uses conservative parameter values for the number of open requests, the retransmission timers, and the overall message rate. More powerful CoAP nodes, however, can use metrics to optimize these parameters to achieve a better quality of service. For this, the IETF CoRE working group is designing an advanced congestion control mechanism for CoAP called CoCoA. This paper presents first evaluation results for a mechanism that improves the communication between cloud services and resource-constrained IoT devices. We implement CoCoA for the Californium (Cf) CoAP framework and evaluate its performance on a wireless sensor network testbed that runs IPv6. Our results show that CoCoA can better utilize the available network capacity and can increase throughput by 19-112%.

The development of IPv6 stacks for wireless constrained devices that have limited hardware resources has paved the way for many new areas of applications and protocols. The Constrained Application Protocol (CoAP) has been designed by the IETF to enable the manipulation of resources for constrained devices that are capable of connecting to the Internet. Due to the limited radio channel capacities and hardware resources, congestion is a common phenomenon in networks of constrained devices. CoAP implements a basic congestion control mechanism for the transmission of reliable messages. Alternative CoAP congestion control approaches are a recent topic of interest in the IETF CoRE Working Group. New Internet-Drafts discuss the limitations of the default congestion control mechanisms and propose alternative ones, yet, there have been no studies in the literature that compare the original approach to the alternative ones. In this paper, we target this crucial study and perform evaluations that show how the default and alternative congestion control mechanisms compare to each other. We use the Cooja simulation environment, which is part of the Contiki development toolset, to simulate CoAP within a complete protocol stack that uses IETF protocols for constrained networks. Through simulations of different network topologies and varying traffic loads, we demonstrate how the advanced mechanisms proposed in the drafts perform relative to the basic congestion control mechanism.