A Survey of Interoperability Challenges and Solutions for Dealing With Them in IoT Environment

Albouq, Sami S.; Sen, Adnan Ahmed Abi; Almashf, Nabil; Yamin, Mohammad; Alshanqiti, Abdullah; Bahbouh, Nour Mahmoud

doi:10.1109/access.2022.3162219

Cited by 24 publications

(8 citation statements)

References 75 publications

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“…Additionally, if the protocols of the two devices are incompatible, a protocol converter is required to permit communication [27]. Additionally, there are several specifications for network compatibility [30]. Network interoperability is sensitive to quality of service (QoS) and latency because real-time data and service sharing are crucial.…”

Section: Network Interoperabilitymentioning

confidence: 99%

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Interoperability for intelligent traffic management systems in smart cities

Alanazi,

Alenezi

2024

IJECE

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Intelligent traffic management systems (ITMS) are essential for safe and livable smart cities. However, achieving seamless interoperability between diverse devices and services is challenging due to the lack of universal open standards. This study examines different types of interoperability (syntactic, semantic, network, middleware, and security) and their relationships with ITMS in the smart city context. By discussing requirements, challenges, and potential standards, this research provides a comprehensive understanding of interoperability issues in ITMS. It highlights the importance of standardization and collaboration among stakeholders, including policymakers, urban planners, and technology providers, to achieve interoperability. Addressing these challenges can optimize ITMS performance and contribute to smarter, sustainable cities. The study categorically examines challenges and potential standards, offering a framework for future research and practice. By advancing our understanding of ITMS interoperability, this research facilitates improved traffic management and smarter city development, enhancing urban residents’ quality of life. It makes a significant contribution to the field by emphasizing the critical role of interoperability in effective traffic management systems and the advancement of smart cities. By addressing interoperability challenges, we can create safer, more efficient, and sustainable transportation networks, fostering the development of livable cities.

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Section: Network Interoperabilitymentioning

confidence: 99%

“…Middleware interoperability problems arise because each system has a separate development environment, and each system was created using its standards under various settings [27,30]. Managing integrated data, which includes gathering, storing, processing, and evaluating data, can be challenging.…”

Section: Middleware Interoperabilitymentioning

confidence: 99%

Interoperability for intelligent traffic management systems in smart cities

Alanazi,

Alenezi

2024

IJECE

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“…For this, energy-efficient network designs coupled with energy harvesting techniques are required to offer sustainable solutions for next-gen IoT [ 2 ]. The heterogeneous IoT networks need to perform seamlessly, for which dynamic network frameworks are needed to support interoperability, integration and coordination [ 3 ]. Owing to the increasing number of IoT nodes and communicating terminals, the storage and security of the huge data are a challenge.…”

Section: Introductionmentioning

confidence: 99%

Interference Aware Resource Control for 6G-Enabled Expanded IoT Networks

Taneja

Alqahtani

2023

Sensors

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Emerging consumer devices rely on the next generation IoT for connected support to undergo the much-needed digital transformation. The main challenge for next-generation IoT is to fulfil the requirements of robust connectivity, uniform coverage and scalability to reap the benefits of automation, integration and personalization. Next generation mobile networks, including beyond 5G and 6G technology, play an important role in delivering intelligent coordination and functionality among the consumer nodes. This paper presents a 6G-enabled scalable cell-free IoT network that guarantees uniform quality-of-service (QoS) to the proliferating wireless nodes or consumer devices. By enabling the optimal association of nodes with the APs, it offers efficient resource management. A scheduling algorithm is proposed for the cell-free model such that the interference caused by the neighbouring nodes and neighbouring APs is minimised. The mathematical formulations are obtained to carry out the performance analysis with different precoding schemes. Further, the allocation of pilots for obtaining the association with minimum interference is managed using different pilot lengths. It is observed that the proposed algorithm offers an improvement of 18.9% in achieved spectral efficiency using partial regularized zero-forcing (PRZF) precoding scheme at pilot length τp=10. In the end, the performance comparison with two other models incorporating random scheduling and no scheduling at all is carried out. As compared to random scheduling, the proposed scheduling shows improvement of 10.9% in obtained spectral efficiency by 95% of the user nodes.

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“…However, this increasing use of IoT devices, e.g., smart home systems, wearable health monitors, and autonomous vehicles, raises many concerns about security risks, higher network complexity, management, and service interoperability [4], [5]. Moreover, the massive growth of heterogeneous interconnected smart devices, which is estimated to reach 50 billion devices by 2030 [6], will lead to a dense network that is composed of multiple devices requesting various services, inter-connected with different communication protocols, and being vulnerable to internal threats and external attacks.…”

Section: Introductionmentioning

confidence: 99%

Context-Aware Service Discovery: Graph Techniques for IoT Network Learning and Socially Connected Objects

et al. 2022

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Adopting Internet-of-things (IoT) in large-scale environments such as smart cities raises compatibility and trustworthiness challenges, hindering conventional service discovery and network navigability processes. The IoT network is known for its highly dynamic topology and frequently changing characteristics (e.g., the devices' status, such as battery capacity and computational power); traditional methods fail to learn and understand the evolving behavior of the network to enable real-time and contextaware service discovery in such diverse and large-scale topologies of IoT networks. The Social IoT (SIoT) concept, which defines the relationships among the connected objects, can be exploited to extract established relationships between devices and enable trustworthy and context-aware services. In fact, SIoT expresses the possible connections that devices can establish in the network and reflect compatibility, trustworthiness, and so on. In this paper, we investigate the service discovery process in SIoT networks by proposing a lowcomplexity context-aware Graph Neural Network (GNN) approach to enable rapid and dynamic service discovery. Unlike the conventional graph-based techniques, the proposed approach simultaneously embeds the devices' features and their SIoT relations. Our simulations on a real-world IoT dataset show that the proposed GNN-based approach can provide more concise clusters compared to traditional techniques, namely the Louvain and Leiden algorithms. This allows a better IoT network learning and understanding and also, speeds up the service lookup search space. Finally, we discuss implementing the GNN-assisted context-service discovery processes in novel smart city IoT-enabled applications.

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A Survey of Interoperability Challenges and Solutions for Dealing With Them in IoT Environment

Cited by 24 publications

References 75 publications

Interoperability for intelligent traffic management systems in smart cities

Interoperability for intelligent traffic management systems in smart cities

Interference Aware Resource Control for 6G-Enabled Expanded IoT Networks

Context-Aware Service Discovery: Graph Techniques for IoT Network Learning and Socially Connected Objects

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