Most news on quantum computers (QCs) consists of outstanding
experiments, and thereby we may overlook how typical usages of QCs have been. Such oversight,
if exists, could lead to an insufficient understanding of the present situation in the research and development of QCs and may
result in possible obstacles to long-term research design. In other words, we need an alternative perspective based on typical
usages as well as the standard one based on monumental experiments.
Architecture determines what and how the network services are provided, as well as the overall system efficiency, scalability, etc. This article proposes high-level designs of the 6G architecture. Three key innovation motivations are analysed and the gaps of 5G network are identified according to the operator’s experience in real large-scale network deployment. Those observations help to generate the key “Design Principles” about the 6G architecture.
Edge learning is a new and powerful approach to training models across distributed clients while protecting the privacy of their data.
This approach is expected to be embedded within future network infrastructures, including 6G, to solve challenging problems such as resource management and behaviour prediction. However, edge learning in general, and distributed deep learning, in particular, have been discovered to be susceptible to tampering and manipulation. This survey article provides a holistic review of the most recent research focused on edge learning vulnerabilities and defenses for 6G-enabled IoT.
Aided by Artificial Intelligence (AI) and Machine Learning (ML), novel solutions targeting traditionally unsolved RAN management issues can be devised. Nevertheless, the adoption of such smart and autonomous systems is limited by the current inability of human operators to understand the decision process of such AI/ML solutions, affecting their trust in such novel tools. eXplainable AI (XAI) aims at solving this issue, enabling human users to better understand and effectively manage the emerging generation of artificially intelligent schemes, reducing the human-to machine barrier.
6G networks are expected to achieve full autonomous operation through the adoption of intelligent algorithms. This calls for
the introduction of an additional stratum in the network devoted to the management and orchestration of network intelligence. This paper outlines such a layer, its composition and function.
Modern mobile communication networks and new service applications are deployed on cloud-native platforms.
Kubernetes (K8s) is the de facto distributed operating system for container orchestration, and the extended version of the Berkeley Packet Filter (eBPF) is to the Linux and Microsoft Windows kernel what JavaScript is to the web browser.
In this paper, we introduce what eBPF is – referring to some of the most important open-source projects (such as Cilium and Calico), books (e.g. the recent one by Liz Rice) and presentations (e.g., the ones by Thomas Graf and his team members at Isovalent) – its potential for Telco cloud, and review some of the most promising pricing and billing models applied to this revolutionary operating system (OS) technology.
The work presented in this paper outlines the role of Optical Transport Networks (OTNs) in future networking generations. Furthermore, key emerging OTN technologies are discussed. Additionally, the role intelligence will play in the Management and Orchestration (MANO) of next-generation OTNs is discussed. Moreover, a set of challenges and opportunities for innovation to guide the development of future OTNs is considered.
Herein, a method to find security strategies for intrusion prevention in SDP network is presented based on modeling the interaction between an attacker and an SDP Controller as a stochastic game. These security strategies evolve through reinforcement learning and can emerge from self-play.