Software-defined Networking (SDN) marked the beginning of a new era in the field of networking by decoupling the control and forwarding processes through the OpenFlow protocol. The Next Generation SDN is defined by Open Interfaces and full programmability of the data plane. P4 is a domain-specific language that fulfills these requirements and has known wide adoption over recent years from Academia and Industry. This work is an extensive survey of the P4 language covering domains of application, a detailed overview of the language, and future directions.

Thousands of devices are connected to the Internet as part of the Internet of Things (IoT) ecosystems. The next generation of IoT networks is expected to support this growing number of Intelligent IoT devices and tactile Internet solutions to provide real-time applications. In view of this, IoT networks require innovative network architectures that offer scalability, security, and adaptability. The Recursive InterNetwork Architecture (RINA) is a clean slate network architecture that provides a scalable, secure, and flexible framework for interconnecting computers. SDN technology is becoming a de facto solution to overcome network requirements, making RINA adoption difficult. This paper presents an architecture for integrating RINA with SDN technologies to lower the barriers of adopting RINA in IoT environments. The architecture relies on a RINA-based distributed application facility (DAF), a RINA southbound driver (SBI), and the RINA L2VPN. The RINA-based DAF manages RINA nodes along the edge–fog–cloud continuum. The SBI driver SDN enables the hybrid centralized management of SDN switches and RINA nodes. Meanwhile, the RINA L2VPN allows seamless communication between edge nodes and the cloud to facilitate the data exchange between network functions (NFs). Such integration has enabled a progressive deployment of RINA in current IoT networks without affecting their operations and performance.

The evolution from the Edge-Cloud Continuum to the Cognitive Computing Continuum (CCC) has introduced new challenges which necessitate advanced frameworks that integrate cognitive capabilities to enhance interoperability, adaptability, and resource efficiency. Considering insights from ongoing research and initiatives on the cognitive cloud, we identify the core concepts essential for transitioning to the CCC, including cognitive orchestration, distributed AI, and sovereign data management. We then introduce ENACT, a novel framework designed to embrace these concepts aiming to provide cognitive, highly adaptive orchestration to support modern hyper-distributed and data-intensive applications. Furthermore, ENACT employs bespoke mechanisms to enable dynamic continuum modelling and visibility as well as to facilitate application-level automation and adaptability. This paper presents the motivation behind the ENACT approach, reviews the state-of-the-art across its fundamental technological concepts and highlights its key innovations. Overall, it contributes to the formalization of the CCC architectural principles and, ultimately, to the realization of CCC.

This paper presents a telemetry dataset capturing resource utilization and power consumption metrics across the ENACT edge-cloud continuum.

The rapid growth of the Internet of Things has shaped the design and deployment of mobile networks to accommodate the need for ubiquitous connectivity and novel applications. The recent advancements in wireless communications and computing technologies allow the connection of a wider range and number of devices and systems, thereby enabling the design and development of next-generation Internet of Things applications. However, current networking technologies cannot accommodate the increasing number of IoT devices as well as satisfy the heterogeneous and stringent requirements in terms of bandwidth, connectivity, latency, and reliability. Motivated by these remarks, this chapter aims to provide an overview of key novel technologies, which are expected to be integral components of future networks 4and can effectively address the challenges associated with satisfying the aforementioned requirements. <!----> <!----> <!----> <!---->