Towards avatar-based discovery for IoT services using social networking and clustering mechanisms

Khadir, Karima; Guermouche, Nawal; Monteil, Thierry; Guittoum, Amal

doi:10.23919/cnsm50824.2020.9269040

Cited by 6 publications

(5 citation statements)

References 20 publications

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“…The proposed approach extends our previous work proposed in [2]. In this work, we have presented a new distributed avatar discovery approach that relies on social networking mechanisms and fuzzy c-means clustering algorithm.…”

Section: Introductionmentioning

confidence: 72%

A Genetic Algorithm-Based Approach for Fluctuating QoS Aware Selection of IoT Services

et al. 2022

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In recent years, the Internet of Things (IoT) has evolved at an exceptional speed, which enables to interconnect a very large number of heterogeneous, distributed, and mobile devices. This number will exceed 70 billion by 2025 according to Statista a . Therefore, with this huge amount of connected objects, the fulfillment of complex IoT applications, which usually requires a combination of several IoT objects, remains a real challenge. Besides, several requirements of Quality of Service (QoS) must be fulfilled, which makes the problem of selecting the appropriate IoT services NP-hard. In the literature, two main techniques for QoS-driven service selection are proposed: global selection characterized by a poor performance in dynamic and distributed huge environments and local selection which considers pre-defined local QoS constraints. Mainly, the existing works consider static QoS. However, in real life scenarios, QoS of IoT services can be fluctuating. To enhance the reliability of IoT applications, it is of paramount importance to consider the fluctuation dimension. In this context, we propose a QoS fluctuation-aware selection approach of IoT services. To do so, we propose a near-to optimal distributed approach that relies on decomposing the global QoS into distinct local constraints that serve as upper/lower bounds for selection while enhancing the reliability of the resulting composition by considering the QoS fluctuation of the candidate IoT services. The approach, we propose is based on a multi-objective evolutionary algorithm (MOEA) to solve the global QoS decomposition problem. Then a local selection using the obtained local constraints is performed in a parallel and distributed way. The performance of the proposed approach is evaluated and validated via experiment series.

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Section: Introductionmentioning

confidence: 72%

A Genetic Algorithm-Based Approach for Fluctuating QoS Aware Selection of IoT Services

et al. 2022

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“…Introducing Social aspects in IoT/WoT is also a critical factor. Khadir et al (2020) [31] propose the concept of the Social Web of Things (SoWoT), which emerges from the convergence of Social Networking and WoT/SWoT. Social IoT (SIoT) [32] and WoT represent evolutionary paradigms envisioning social consciousness within smart objects.…”

Section: Evolutionary Directions and Engineeringmentioning

confidence: 99%

IR.WoT: An Architecture and Vision for a Unified Web of Things Search Engine

Manta-Caro,

Fernández-Luna

2024

Sensors

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The revolution of the Internet of Things (IoT) and the Web of Things (WoT) has brought new opportunities and challenges for the information retrieval (IR) field. The exponential number of interconnected physical objects and real-time data acquisition requires new approaches and architectures for IR systems. Research and prototypes can be crucial in designing and developing new systems and refining architectures for IR in the WoT. This paper proposes a unified and holistic approach for IR in the WoT, called IR.WoT. The proposed system contemplates the critical indexing, scoring, and presentation stages applied to some smart cities’ use cases and scenarios. Overall, this paper describes the research, architecture, and vision for advancing the field of IR in the WoT and addresses some of the remaining challenges and opportunities in this exciting area. The article also describes the design considerations, cloud implementation, and experimentation based on a simulated collection of synthetic XML documents with technical efficiency measures. The experimentation results show promising outcomes, whereas further studies are required to improve IR.WoT effectiveness, considering the WoT dynamic characteristics and, more importantly, the heterogeneity and divergence of WoT modeling proposals in the IR domain.

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“…They decrease the delay time of discovering services between IoT devices, and their approach is cost-effective and improves resource utilization and availability. Khadir et al 21 proposed an avatar-based distributed mechanism for service discovery, defined as virtual entities of SIoT devices. Qiu et al 22,23 present a deep-learning community detection method based on graph neural networks-VGAER and GAER-with a high performance based on NMI and modularity index.…”

Section: Analysis Of Related Workmentioning

confidence: 99%

“…28 The main premise of community recognition is that similar objects have similar interests, preferences, and social behaviors, leading to forming a community among them. 21 Service discovery • Higher efficiency -Algorithm Qiu et al 22 Community detection…”

Section: Basic Definitionmentioning

confidence: 99%

Community detection and service discovery on Social Internet of Things

Rad

Rahmani

Sahafi

et al. 2023

Int J Communication

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Summary Due to the increasing growth of objects and problems such as increased traffic, overload, delay in response, and low search volume in the service discovery process in the complex Social Internet of Things (SIoT) environment, we provide an effective mechanism in the service discovery process by grouping objects based on common criteria that help us improve service search performance. In this article, we present a new method for clustering objects so that we can group objects that have common services and can work together. Hence, we create a set of different associations for the type of service and reciprocal cooperation of objects. With its help, instead of a global network search, we can perform service searches locally more efficiently and ensure the accuracy and correctness of searches and their answers. Then, we have provided a new mechanism for the service discovery process. In addition, we categorized communities based on their size to compare our proposed algorithm with other approaches using factors such as modularity in SIoT. Finally, we achieved sufficient efficiency in service discovery (86.81% and 88.28%) and demonstrated better performance of the proposed approach in identifying communities.

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Towards avatar-based discovery for IoT services using social networking and clustering mechanisms

Cited by 6 publications

References 20 publications

A Genetic Algorithm-Based Approach for Fluctuating QoS Aware Selection of IoT Services

A Genetic Algorithm-Based Approach for Fluctuating QoS Aware Selection of IoT Services

IR.WoT: An Architecture and Vision for a Unified Web of Things Search Engine

Community detection and service discovery on Social Internet of Things

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