AI-powered edge computing evolution for beyond 5G communication networks

Edge computing is a key enabling technology that is expected to play a crucial role in beyond 5G (B5G) and 6G communication networks. By bringing computation closer to where the data is generated, and leveraging Artificial Intelligence (AI) capabilities for advanced automation and orchestration, edge computing can enable a wide range of emerging applications with extreme requirements in terms of latency and computation, across multiple vertical domains. In this context, this paper first discusses the key technological challenges for the seamless integration of edge computing within B5G/6G and then presents a roadmap for the edge computing evolution, proposing a novel design approach for an open, intelligent, trustworthy, and distributed edge architecture.VERGE has received funding from the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union’s Horizon Europe research and innovation programme under Grant Agreement No 101096034.Peer ReviewedPostprint (author's final draft

Cross-layer latency-aware and -predictable data communication

Cyber-physical systems are making their way into more aspects of everyday life. These systems are increasingly distributed and hence require networked communication to coordinatively fulfil control tasks. Providing this in a robust and resilient manner demands for latency-awareness and -predictability at all layers of the communication and computation stack. This thesis addresses how these two latency-related properties can be implemented at the transport layer to serve control applications in ways that traditional approaches such as TCP or RTP cannot. Thereto, the Predictably Reliable Real-time Transport (PRRT) protocol is presented, including its unique features (e.g. partially reliable, ordered, in-time delivery, and latency-avoiding congestion control) and unconventional APIs. This protocol has been intensively evaluated using the X-Lap toolkit that has been specifically developed to support protocol designers in improving latency, timing, and energy characteristics of protocols in a cross-layer, intra-host fashion. PRRT effectively circumvents latency-inducing bufferbloat using X-Pace, an implementation of the cross-layer pacing approach presented in this thesis. This is shown using experimental evaluations on real Internet paths. Apart from PRRT, this thesis presents means to make TCP-based transport aware of individual link latencies and increases the predictability of the end-to-end delays using Transparent Transmission Segmentation.Cyber-physikalische Systeme werden immer relevanter für viele Aspekte des Alltages. Sie sind zunehmend verteilt und benötigen daher Netzwerktechnik zur koordinierten Erfüllung von Regelungsaufgaben. Um dies auf eine robuste und zuverlässige Art zu tun, ist Latenz-Bewusstsein und -Prädizierbarkeit auf allen Ebenen der Informations- und Kommunikationstechnik nötig. Diese Dissertation beschäftigt sich mit der Implementierung dieser zwei Latenz-Eigenschaften auf der Transport-Schicht, sodass Regelungsanwendungen deutlich besser unterstützt werden als es traditionelle Ansätze, wie TCP oder RTP, können. Hierzu wird das PRRT-Protokoll vorgestellt, inklusive seiner besonderen Eigenschaften (z.B. partiell zuverlässige, geordnete, rechtzeitige Auslieferung sowie Latenz-vermeidende Staukontrolle) und unkonventioneller API. Das Protokoll wird mit Hilfe von X-Lap evaluiert, welches speziell dafür entwickelt wurde Protokoll-Designer dabei zu unterstützen die Latenz-, Timing- und Energie-Eigenschaften von Protokollen zu verbessern. PRRT vermeidet Latenz-verursachenden Bufferbloat mit Hilfe von X-Pace, einer Cross-Layer Pacing Implementierung, die in dieser Arbeit präsentiert und mit Experimenten auf realen Internet-Pfaden evaluiert wird. Neben PRRT behandelt diese Arbeit transparente Übertragungssegmentierung, welche dazu dient dem TCP-basierten Transport individuelle Link-Latenzen bewusst zu machen und so die Vorhersagbarkeit der Ende-zu-Ende Latenz zu erhöhen

VirtuWind: Virtual and programmable industrial network prototype deployed in operational wind park.

With anticipated exponential growth of connected devices, future industrial networks require an open solutions architecture facilitated by standards and a strong ecosystem. Such solutions should also deal with range of quality of service requirements imposed by industrial networks. Preserving strict quality of service is particularly challenging when services pass across domains of multiple provides. VirtuWind aims to develop and demonstrate a Software Defined Networking and Network Function Virtualization ecosystem, based on an open, modular and secure framework to address stringent requirements of the industrial networks. A prototype of the framework for intra-domain and inter-domain scenarios will be showcased in real Wind Parks, as a representative use case of industrial networks. This paper details this vision and explains steps forward

VirtuWind: Virtual and Programmable Industrial Network Prototype Deployed in Operational Wind Park

With anticipated exponential growth of connected devices, future industrial networks require an open solutions architecture facilitated by standards and a strong ecosystem.VirtuWind aims to develop and demonstrate an SDN and NFV ecosystem, based on an open, modular and secure framework.A prototype of the framework for intra-domain and inter-domain scenarios will be showcased in real wind parks,as a representative use case of industrial networks. Validate the economic viability of the demonstrated solution is paramount for VirtuWind. This paper details this vision and explains steps forward

Self-healing and SDN: bridging the gap

Achieving high programmability has become an essential aim of network research due to the ever-increasing internet traffic. Software-Defined Network (SDN) is an emerging architecture aimed to address this need. However, maintaining accurate knowledge of the network after a failure is one of the largest challenges in the SDN. Motivated by this reality, this paper focuses on the use of self-healing properties to boost the SDN robustness. This approach, unlike traditional schemes, is not based on proactively configuring multiple (and memory-intensive) backup paths in each switch or performing a reactive and time-consuming routing computation at the controller level. Instead, the control paths are quickly recovered by local switch actions and subsequently optimized by global controller knowledge. Obtained results show that the proposed approach recovers the control topology effectively in terms of time and message load over a wide range of generated networks. Consequently, scalability issues of traditional fault recovery strategies are avoided.Postprint (published version