Large-scale Experimentation with Network Abstraction for Network Configuration Management

Meer, Sven van der; Keeney, John; Fallon, Liam; Feghhi, Saman; Buitléir, Amy de

doi:10.1109/icin.2019.8685922

Cited by 5 publications

(3 citation statements)

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“…There are two types of DIFs: shim DIFs and normal DIFs. The shim DIFs are adaptations of existing protocols such as Wi-Fi [22], VLAN [23], and TCP/UDP [24]. The shims facilitate the underlying protocol layer with the IPC service interface.…”

Section: Rina-based Networkmentioning

confidence: 99%

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Progressive Adoption of RINA in IoT Networks: Enhancing Scalability and Network Management via SDN Integration

Sarabia-Jácome,

Giménez-Antón,

Liatifis

et al. 2024

Applied Sciences

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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.

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Section: Rina-based Networkmentioning

confidence: 99%

“…On the other hand, ref. [24] presents and discusses several Key Performance Indicators (KPIs) regarding configuration management, software complexity, and automation in large-scale networks.…”

Section: Rina-based Networkmentioning

confidence: 99%

Progressive Adoption of RINA in IoT Networks: Enhancing Scalability and Network Management via SDN Integration

Sarabia-Jácome,

Giménez-Antón,

Liatifis

et al. 2024

Applied Sciences

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“…RINA provides two protocols: the Error and Flow Control Protocol (EFCP) for data transfer and the Common Distributed Application Protocol (CDAP) for management. This simplification reduces the network complexity in comparison to TCP/IP stack [5] [10].…”

Section: Related Workmentioning

confidence: 99%

Fine-Grained Traffic Differentiation in Tactile Internet Scenarios Using RINA

Sarabia-Jácome,

Grasa,

Catalán

2023

2023 IEEE 9th World Forum on Internet of Things (WF-IoT)

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The tactile Internet (TI) has emerged as an advanced communication technology that enables interaction between humans and machines. However, TI use cases demand low latency, high reliability, and high-capacity requirements to achieve high quality of experience (QoE) in their applications. IoT networks provide transmission services to heterogeneous applications, and the inclusion of high-demand Quality of Service (QoS) requirements by TI applications will increase the difficulty of guaranteeing end-to-end QoS. We proposed a fine-grained traffic differentiation in tactile Internet scenarios using the Recursive Inter-Networking Architecture (RINA) QoS cubes and the Quantitative Timeliness Agreement Multiplexor (QTA-Mux) flow prioritization scheme. We designed four RINA QoS cubes to meet the delay and packet loss requirements of TI, Augmented Reality/Virtual Reality (AR/VR), and IoT applications and to provide fine-grained traffic differentiation. Also, we designed the QTA-Mux policy to enable a trade-off between delay and packet loss and adequately scheduling the service data unit (SDU) for delivering. We implemented a RINA network to test the proposed schemes in IoT environments and conducted several experiments to evaluate the delay and packet loss. The results showed that RINA-based prioritization and traffic differentiation proposed guaranteed end-to-end QoS to support TI applications. Thus, the next generation of IoT networks can use RINA to guarantee the QoS requirements of TI applications.

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