Service Discovery Based on Social Profiles of Objects in a Social IoT Network

Araujo, Iury; Pedrosa, Mikaelly F.; Castro, Jessica; Anjos, Eudisley Gomes dos; Matos, Fernando

doi:10.1007/978-3-030-24308-1_33

Cited by 2 publications

(3 citation statements)

References 14 publications

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“…Response time is mentioned to execution and wait for time of a service when a service requests until receiving a response. It is calculated based on Equation (18).…”

Section: Service Discovery Response Timementioning

confidence: 99%

“…They add a natural language process approach to crowdsourcing textual requests and accordingly find the list of IoT devices suitable for the crowdsourcing process. Araujo et al 18 present a new approach for discovering services in the SIoT system based on object social profile search using the social information and attributes of objects. The approach includes three main attributes: request an object (RO), service List (SL), and requirements List (RL).…”

Section: Analysis Of Related Workmentioning

confidence: 99%

“…Figure 19 presents a success rate comparison between the proposed method, Chen, 36 and SPSS 18 approaches. Based on it, the average success rate is assessed between 4,000 to 8,000 nodes.…”

Section: Experimental Evaluationmentioning

confidence: 99%

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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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“…Response time is mentioned to execution and wait for time of a service when a service requests until receiving a response. It is calculated based on Equation (18).…”

Section: Service Discovery Response Timementioning

confidence: 99%

Section: Analysis Of Related Workmentioning

confidence: 99%