Semantic Interoperability in the IoT

Novo, Oscar; Francesco, Mario Di

doi:10.1145/3375838

Cited by 30 publications

(9 citation statements)

References 55 publications

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“…To achieve semantic interoperability between IoT frameworks, recent efforts such as IEEE P2413-2019 Standard for an Architectural Framework for the Internet of Things (IoT) have produced a report for IoT Semantic Interoperability. These efforts standardize ontologies for internet-of-things-based systems, such as domain ontologies, task ontologies, and user ontologies [571,572]. A formal explanation of the connections and concepts in a particular field is called an ontology.…”

Section: Ongoing Researchmentioning

confidence: 99%

A Comprehensive Survey on Knowledge-Defined Networking

Wijesekara

Gunawardena

2023

Telecom

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Traditional networking is hardware-based, having the control plane coupled with the data plane. Software-Defined Networking (SDN), which has a logically centralized control plane, has been introduced to increase the programmability and flexibility of networks. Knowledge-Defined Networking (KDN) is an advanced version of SDN that takes one step forward by decoupling the management plane from control logic and introducing a new plane, called a knowledge plane, decoupled from control logic for generating knowledge based on data collected from the network. KDN is the next-generation architecture for self-learning, self-organizing, and self-evolving networks with high automation and intelligence. Even though KDN was introduced about two decades ago, it had not gained much attention among researchers until recently. The reasons for delayed recognition could be due to the technology gap and difficulty in direct transformation from traditional networks to KDN. Communication networks around the globe have already begun to transform from SDNs into KDNs. Machine learning models are typically used to generate knowledge using the data collected from network devices and sensors, where the generated knowledge may be further composed to create knowledge ontologies that can be used in generating rules, where rules and/or knowledge can be provided to the control, management, and application planes for use in decision-making processes, for network monitoring and configuration, and for dynamic adjustment of network policies, respectively. Among the numerous advantages that KDN brings compared to SDN, enhanced automation and intelligence, higher flexibility, and improved security stand tall. However, KDN also has a set of challenges, such as reliance on large quantities of high-quality data, difficulty in integration with legacy networks, the high cost of upgrading to KDN, etc. In this survey, we first present an overview of the KDN architecture and then discuss each plane of the KDN in detail, such as sub-planes and interfaces, functions of each plane, existing standards and protocols, different models of the planes, etc., with respect to examples from the existing literature. Existing works are qualitatively reviewed and assessed by grouping them into categories and assessing the individual performance of the literature where possible. We further compare and contrast traditional networks and SDN against KDN. Finally, we discuss the benefits, challenges, design guidelines, and ongoing research of KDNs. Design guidelines and recommendations are provided so that identified challenges can be mitigated. Therefore, this survey is a comprehensive review of architecture, operation, applications, and existing works of knowledge-defined networks.

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Section: Ongoing Researchmentioning

confidence: 99%

A Comprehensive Survey on Knowledge-Defined Networking

Wijesekara

Gunawardena

2023

Telecom

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“…Through the WoT Arrowhead Enabler (WAE), each WT is mapped and registered as an Arrowhead service, hence becoming discoverable and usable by Mashup applications. Another example of integration between discovery services and the W3C WoT ecosystem is given by Novo and Francesco [109], where authors design an architecture for enabling the discovery using both a (WoT) Thing directory and the Resource Directory according to the IETF Core Resource specifications. More in detail, they extend the Resource Directory with additional semantic information to enable an interconnection with the Thing directory, granting full compatibility with the W3C WoT standards.…”

Section: ) Directory-based Discoverymentioning

confidence: 99%

“…This is the case of [74], where authors propose a format to represent Mashup application called System Description (SD), an enhancement of the W3C WoT TD, and provide also a tool to generate executable code that implements the business logic expressed by the SD. Similarly, Novo and Francesco [109] create a visual tool user through which developers can manually translate the TDs for those IoT devices that are not able to parse the TDs. About TD sharing, WoTify [81] is a tool for sharing and re-using TDs and Thing Application made available by the users: the ambitious goal is to create a community that actively contributes to the diffusion of the W3C WoT by easing the mapping of new and existing IoT devices.…”

Section: ) Design-time Toolsmentioning

confidence: 99%

A Survey on the Web of Things

et al. 2022

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The Web of Things (WoT) paradigm was proposed first in the late 2000s, with the idea of leveraging Web standards to interconnect all types of embedded devices. More than ten years later, the fragmentation of the IoT landscape has dramatically increased as a consequence of the exponential growth of connected devices, making interoperability one of the key issues for most IoT deployments. Contextually, many studies have demonstrated the applicability of Web technologies on IoT scenarios, while the joint efforts from the academia and the industry have led to the proposals of standard specifications for developing WoT systems. Through a systematic review of the literature, we provide a detailed illustration of the WoT paradigm for both researchers and newcomers, by reconstructing the temporal evolution of key concepts and the historical trends, providing an in-depth taxonomy of software architectures and enabling technologies of WoT deployments and, finally, discussing the maturity of WoT vertical markets. Moreover, we identify some future research directions that may open the way to further innovation on WoT systems.

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“…Although this approach was validated through its adoption by different solutions, there is not a tool or framework that validates such interoperability. This definition has been further extended in [43] (Section 2.3) for IoT data semantics.…”

Section: Related Workmentioning

confidence: 99%