Bundling of multiple access technologies is currently being standardized by 3GPP in the 5G access traffic steering, switching and splitting (ATSSS) framework, with the goal to increase robustness, resiliency and capacity of wireless access. A key part of an ATSSS framework is the packet scheduler, which decides the access network over which each packet is to be transmitted. As wireless channels are highly dynamic, a challenge for any scheduler is to correctly estimate the capacity of each path, and thereby avoid congesting the paths. In this paper, we further develop a recent packet scheduler that exploits cross-layer information from the congestion control state of individual transport layer tunnels when making scheduling decisions. Our aim is to achieve good path utilization while keeping the congestion delay low. Extensive emulations show that our approach reduces the excess delay at the bottleneck to as little as 34%. We furthermore show that our approach improves the performance of end-to-end applications including WebRTC and YouTube compared to state-of-the art. 

The Access Traffic Steering, Switching, and Splitting (ATSSS) technology, currently under standardization by the 3rd Generation Partnership Project (3GPP), is designed to enhance wireless access through the bundling of both 3GPP and non-3GPP access. One implementation option involves tunneling data through the Multipath QUIC (MP-QUIC) protocol. The decision of which access network each packet is transmitted on can greatly impact the performance of a network flow, and may also impact the performance of other flows. While Active Queue Management (AQM) in the network could normally manage such interactions, such techniques are limited in a shared multipath-tunnel context, since all traffic in the tunnel share a single connection. This paper introduces a multi-flow, multipath tunneling framework using MP-QUIC. It employs four distinct scheduling policies for packet scheduling decisions. We investigate how such scheduling policies interact with each other, and how they may be combined in order to achieve trade-offs in terms of latency, interactivity, and throughput. Through an extensive investigation in both emulated and real-world environments, we show that Quality of Service (QoS) can be significantly improved by smart combinations of scheduling policies.

The Internet of today is very different from how it used to be. Modern networked applications are becoming increasingly diverse. Consequently, a variety of requirements must be met by the network. Efforts to make the underlying mechanisms of the Internet more flexible have therefore been made to adapt to this diversification. In this thesis, we explore how information about application requirements can be leveraged to optimize the network protocol stack of end-hosts during run-time. In addition, we improve the visibility of the network to the end-host in order to enable additional flexibility in the usage of the network's resources.

We conduct tests in real-world testbeds and examine how services might be developed to optimize latency, throughput, and availability for various network traffic scenarios, including 360-degree video streaming, drone autopilots, and connected vehicles. We show how multi-connectivity, where the end-host is connected via multiple network paths simultaneously, may be used to significantly reduce latency and increase availability, while minimizing the overhead imposed on the network by carefully considering the network selection process. Furthermore, we describe an architecture that allows the user equipment and network functionality inside the 5G core network to cooperatively optimize the resource usage of the network.

The Internet of today is very different from how it used to be. Modern networked applications are becoming increasingly diverse. Consequently, a variety of requirements must be met by the network. This presents a massive challenge, since the Internet was originally designed on best-effort principle. 

To address this challenge, we explore how Internet end-hosts can flexibly adapt to the needs of individual applications, by dynamically configuring the network protocol stack during run-time. In addition, we improve the visibility of the network, allowing end-hosts to better utilize the resources of the network. 

We conduct tests in real-world testbeds and examine how services might be developed to optimize latency, throughput, and availability for various network traffic scenarios. We also show how multiple network paths can be used simultaneously to significantly reduce latency and increase availability, while minimizing the overhead imposed on the network. Furthermore, we describe an architecture that allows the user equipment and network functionality inside the 5G core network to cooperatively optimize the resource usage of the network.

This deliverable presents the third and final cycle of trials and experimentation activities executed over 5GENESIS facilities. The document is the continuation of deliverables D6.1 and D6.2, in the sense that it captures tests carried out over the evolved infrastructures hosting 5GENESIS facilities following the methodology defined in the previous editions of this deliverable. The tests reported in this document focus on i) the final 5G infrastructure deployments that includes radio and core elements mostly in Stand-Alone (SA) deployment configurations based on commercial and open implementations, and ii) the various use cases/applications, some of them also involving field trials. Most of the tests described herein, especially the generic/lab ones are performed using the Open5GENESIS experimentation suite. 

5G mobile networks introduce the concept of network slicing, the functionality of creating virtual networks on top of shared physical infrastructure. Such slices can be tailored to various vertical services. A single User Equipment (UE) may be served by multiple network slice instances simultaneously, which opens up the possibility of dynamically steering traffic in response to the specific needs of individual applications -- and as a reaction to events inside the network, e.g., network failures. 

This paper presents the PoLicy-based Architecture for Network Slicing (PLANS). In this policy framework, the network slice management entity in the 5G core and the UE can cooperatively optimize the usage of the available network slices via policy systems installed both inside the network and on the UE. The PLANS architecture has been implemented and evaluated in a 5G testbed. For two different case studies, we show how such a system can be leveraged to provide optimized services and increased robustness against network failures. First, we consider a drone autopilot scenario, and demonstrate how PLANS can reduce network-slice recovery time by more than 90%. Second, we illustrate for a 360-degree video streaming scenario how PLANS can help prevent video quality degradation when a network slice becomes unavailable.

Cooperative Intelligent Transport Systems (C-ITS) enable information to be shared wirelessly between vehicles and infrastructure in order to improve transport safety and efficiency. Delivering C-ITS services using existing cellular networks offers both financial and technological advantages, not least since these networks already offer many of the features needed by C-ITS, and since many vehicles on our roads are already connected to cellular networks. Still, C-ITS pose stringent requirements in terms of availability and latency on the underlying communication system; requirements that will be hard to meet for currently deployed 3G, LTE, and early-generation 5G systems. Through a series of experiments in the MONROE testbed (a cross-national, mobile broadband testbed), the present study demonstrates how cellular multi-access selection algorithms can provide close to 100% availability, and significantly reduce C-ITS transaction times. The study also proposes and evaluates a number of low-complexity, low-overhead single-access selection algorithms, and shows that it is possible to design such solutions so that they offer transaction times and availability levels that rival those of multi-access solutions.

Bundling multiple access technologies increases capacity, resiliency and robustness of network connections. Multi-access is currently being standardized in the ATSSS framework in 3GPP, supporting different access bundling strategies. Within ATSSS, a multipath scheduler needs to decide which path to use for each user packet based on path characteristics. The Cheapest Path First (CPF) scheduler aims to utilize the cheapest path (e.g. WiFi) before sending packets over other paths (e.g. cellular). In this paper, we demonstrate that using CPF with an MP-DCCP tunnel may lead to sub-optimal performance. This is due to adverse interactions between the scheduler and end-to-end and tunnel congestion control. Hence, we design the Adaptive Cheapest Path First (ACPF) scheduler that limits queue buildup in the primary bottleneck and moves traffic to the secondary path earlier. We implement ACPF over both TCP and DCCP congestion controlled tunnels. Our evaluation shows that ACPF improves the average throughput over CPF between 24% to 86%.

The network slicing concept of 5G aims to provide the flexibility and scalability required to support a wide array of vertical services. To coordinate the coexistence of network slices, and to guarantee that the required resources are available for each one of them, the 5G core employs a slicing management entity, a slice manager. In this paper, we propose an architecture where the network slicing concept is extended beyond the core and access networks to also include the configuration of the UE’s network stack.We exploit the slice manager’s global view on the network to feed fine-grained information on slice configuration, health, and status to the UE. This information, together with local policies on the UE, is then used to dynamically create services tailored to the requirements of individual applications. We implement this architecture in a 5G testbed, and show how it can be leveraged in order to enable optimized services through dynamic network protocol configuration, application-to-slice mapping, and network protocol selection.

This document describes the design and implementation of the 5GENESIS Monitoring & Analytics (M&A) framework in its Release B, developed within Task T3.3 of the project work plan. M&A Release B leverages and extends M&A Release A, which has been documented in the previous Deliverable D3.5 [1]. In particular, we present new features and enhancements introduced in this new Release compared to the Release A. We also report some examples of usage of the M&A framework, in order to showcase its integrated in the 5GENESIS Reference Architecture. 

Multipath communication is an attractive solution to the increasing need for improving web performance, by allowing devices to aggregate the capacity of different network paths, which can thus lead to lower latencies. However, path asymmetry is known to incur performance issues for multipath transport protocols, such as head-of-line blocking (HoLB), as well as other issues. We propose a proof-of-concept algorithm for a stream-aware packet scheduler for Multipath QUIC, called Stream-Aware Earliest Completion First (SA-ECF). SA-ECF schedules the sending of stream data so that the completion of individual streams are not delayed by slower paths, while providing a fair allocation of the aggregated bandwidth based on stream priority information from HTTP/2. We compare the performance of SA-ECF with other packet schedulers for MPQUIC using measurements from a virtualized testbed. Our results show that SA-ECF is able to handle path heterogeneity well, and can provide lower stream completion times than non stream-aware schedulers.