The Internet has made several giant leaps over the years, from a fixed to a mobile Internet, then to the Internet of Things, and now to a Tactile Internet. The Tactile Internet goes far beyond data, audio and video delivery over fixed and mobile networks, and even beyond allowing communication and collaboration among things. It is expected to enable haptic communications and allow skill set delivery over networks. Some examples of potential applications are tele-surgery, vehicle fleets, augmented reality and industrial process automation. Several papers already cover many of the Tactile Internet-related concepts and technologies, such as haptic codecs, applications, and supporting technologies. However, none of them offers a comprehensive survey of the Tactile Internet, including its architectures and algorithms. Furthermore, none of them provides a systematic and critical review of the existing solutions. To address these lacunae, we provide a comprehensive survey of the architectures and algorithms proposed to date for the Tactile Internet. In addition, we critically review them using a well-defined set of requirements and discuss some of the lessons learned as well as the most promising research directions.

Historically, research efforts in optical networks have focused on the goal of continuously increasing capacity rather than on lowering end-to-end latency. This slowly started to change in the access environment with post-Next-Generation Passive Optical Network 2 research. The emphasis on latency grew in importance with the introduction of 5G ultra-reliable and low-latency communication requirements. In this paper, we focus on the emerging Tactile Internet as one of the most interesting 5G low-latency applications enabling novel immersive experiences. After describing the Tactile Internet’s human-in-the-loop-centric design principles and haptic communications models, we elaborate on the development of decentralized cooperative dynamic bandwidth allocation algorithms for end-to-end resource coordination in fiber-wireless (FiWi) access networks. We then use machine learning in the context of FiWi enhanced heterogeneous networks to decouple haptic feedback from the impact of extensive propagation delays. This enables humans to perceive remote task environments in time at a 1-ms granularity.

Next-generation 6G networks are envisioned to be a key enabler for low-latency services (e.g., extended reality, remote surgery), which cannot be potentially realized by currently deployed networks. Network function virtualization (NFV) and software-defined networking (SDN) are going to continue playing their key role as two promising technologies in 6G to realize these services due to flexibility, agility, scalability, and cost-efficiency. Although NFV and SDN bring several benefits, provisioning latency-sensitive network services (NSs) in an NFV-based infrastructure remains a challenge, as they require stringent service deadlines. To efficiently meet such stringent service deadlines, VNF placement and scheduling need to be carried out jointly. Most of the existing studies tackle these two problems separately. In this paper, we study the joint VNF placement and scheduling problem for latency-sensitive NSs. We aim at optimally determining whether to place new VNFs or to reuse the already deployed VNFs to optimize profits while guaranteeing stringent deadlines. To solve the problem, we formulate it as an integer linear programming (ILP) problem. Due to its complexity, we also propose two efficient heuristics, namely, greedy-based and Tabu search-based algorithms to solve the problem. The simulation results show that our proposed algorithms achieve higher profits than the existing benchmarks.

The opening Optical Fiber Communication Conference and Exhibition 2021 plenary talk on how technologies and applications drive the evolution of networking concluded by presenting the equation Networking = Art + Science + Engineering. Due to their growing complexity, modern networks may be better viewed as techno-social systems that resemble biological superorganisms. In this paper, we expand on the aforementioned equation in the context of future 6G mobile networks, putting a focus on its first part, the Art of 6G (TAO 6G). To set the stage, we first elaborate on the 6G vision from an optical fiber fixed networks perspective, taking into account the respective viewpoints of the International Telecommunication Union-Telecommunication Standardization Sector and the FTTH Council Europe as well as the European Telecommunications Standards Institute’s recently launched fifth-generation fixed network initiative of bringing fiber to everywhere and everything, which is supposed to be the foundation of the new digital age and is a prerequisite for the digital transformation of the whole society. Towards this end, we present our ideas on what the digital society of the future will or potentially could look like. After briefly reviewing our work on tactile immersive use cases of so-called cyber-physical-social systems (CPSS), we inquire into the emerging human-centric Industry 5.0 and its mutually beneficial underlying principles of digitalization and, more interestingly, biologization. Specifically, we borrow ideas from biological superorganisms with brain-like cognitive capabilities found in natural societies for a stigmergy-enhanced Society 5.0, using tokenized digital twins for advancing collective intelligence in CPSS via indirect communication. Finally, we present our CPSS-based bottom-up token engineering framework designed for Society 5.0.

To ensure reliability and service availability, nextgeneration networks are expected to rely on automated anomaly detection systems powered by advanced machine learning methods with the capability of handling multi-dimensional data. Such multi-dimensional, heterogeneous data occurs mostly in todays Industrial Internet of Things (IIoT), where real-time detection of anomalies is critical to prevent impending failures and resolve them in a timely manner. However, existing anomaly detection methods often fall short of effectively coping with the complexity and dynamism of multi-dimensional data streams in IIoT. In this paper, we propose an adaptive method for detecting anomalies in IIoT streaming data utilizing a multi-source prediction model and concept drift adaptation. The proposed anomaly detection algorithm merges a prediction model into a novel drift adaptation method resulting in accurate and efficient anomaly detection that exhibits improved scalability. Our trace-driven evaluations indicate that the proposed method outperforms the state-of-theart anomaly detection methods by achieving up to an 89.71 accuracy (in terms of Area under the Curve (AUC)) while meeting the given efficiency and scalability requirements.

Remote robotic surgery, one of the most interesting 5G-enabled Tactile Internet applications, requires an ultra-low latency of 1 ms and high reliability of 99.999%. Communication disruptions such as packet loss and delay in remote robotic surgery can prevent messages between the surgeon and patient from arriving within the required deadline. In this paper, we advocate for scalable Gaussian process regression (GPR) to predict the contents of delayed and/or lost messages. Specifically, two kernel versions of the sequential randomized low-rank and sparse matrix factorization method ( $\ell _{1}$ -SRLSMF and SRLSMF) are proposed to scale GPR and address the issue of delayed and/or lost data in the training dataset. Given that the standard eigen decomposition for online GPR covariance update is cost-prohibitive, we employ incremental eigen decomposition in $\ell _{1}$ -SRLSMF and SRLSMF GPR methods. Simulations were conducted to evaluate the performance of our proposed $\ell _{1}$ -SRLSMF and SRLSMF GPR methods to compensate for the detrimental impacts of excessive delay and packet loss associated with 5G-enabled Tactile Internet remote robotic surgery. The results demonstrate that our proposed framework can outperform state-of-the-art approaches in terms of haptic data generalization performance. Finally, we assess the proposed framework’s ability to meet the Tactile Internet requirement for remote robotic surgery and discuss future research directions.