An IoT Service Aggregation Method Based on Dynamic Planning for QoE Restraints

Jia, Bing; Hao, Lifei; Zhang, Chuxuan; Zhao, Huili; Muhammad, Khan

doi:10.1007/s11036-018-1135-7

Cited by 21 publications

(12 citation statements)

References 7 publications

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“…Data aggregation is an important research problem in wireless sensor networks [6]. For the study of data aggregation, either the algorithm based on energy balance consideration or the algorithm in the case of multiple base stations or the algorithm in the case of single base station or the realtime algorithm in the routing layer, literature [7] proves that the data aggregation problem of reducing delay is NP difficult.…”

Section: Related Workmentioning

confidence: 99%

Singing and Nervous System Regulation Based on Wireless Sensor Network Perception

Feng

2021

Journal of Sensors

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In order to build an intelligent platform that can be applied to singing and nervous system adjustment, this paper optimizes the positioning and information processing algorithms for wireless sensor network perception. Moreover, this article combines binocular vision to realize the singer’s real-time positioning, combines the singer’s emotion recognition with the intelligent sensor system, and combines the emotion recognition with the adjustment of the nervous system, so that the singer can better control the intelligent platform. In addition, in order to solve the problem of multisensor information fusion, this paper improves the sensor fusion algorithm to make it suitable for the information fusion of vision sensors and information sensors. Finally, this paper designs the functional structure of the system, transmits data through wireless sensor networks, simulates human emotion models, and studies the process of singing and the adjustment of the nervous system. It can be seen from the experimental research results that the method proposed in this paper has a certain effect.

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Section: Related Workmentioning

confidence: 99%

Singing and Nervous System Regulation Based on Wireless Sensor Network Perception

Feng

2021

Journal of Sensors

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“…The framework is based on domain ontologies (assuming that experts have defined them clearly) to provide a solid foundation (semantically) to the terms used in the framework for defining and achieving the goal. Furthermore, the framework proposed by Jia et al [ 41 ] aggregate IoT services dynamically, based on real-time sensing of information. In order to achieve the goal, the author created service combination categories according to user needs and QoS parameters (functional and non-functional requirements).…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Semantic Knowledge Integration and Sharing Approach for Distributed Smart Environments

Zeshan

Awada

Abdel‐Aty

et al. 2020

Sensors

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Distributed systems provide smart functionality to everyday objects with the help of wireless sensors using the internet. Since the last decade, the industry is struggling to develop efficient and intelligent protocols to integrate a huge number of smart objects in distributed computing environments. However, the main challenge for smart and distributed system designers lies in the integration of a large number of heterogeneous components for faster, cheaper, and more efficient functionalities. To deal with this issue, practitioners are using edge computing along with server and desktop technology for the development of smart applications by using Service-Oriented Architecture (SOA) where every smart object offers its functionality as a service, enabling other objects to interact with them dynamically. In order to make such a system, researchers have considered context-awareness and Quality of Service (QoS) attributes of device services. However, context modeling is a complicated task since it could include everything around the applications. Moreover, it is also important to consider non-functional interactions that may have an impact on the behavior of the complete system. In this regard, various research dimensions are explored. However, rich context-aware modeling, QoS, user priorities, grouping, and value type direction along with uncertainty are not considered properly while modeling of incomplete or partial domain knowledge during ontology engineering, resulting in low accuracy of results. In this paper, we present a semantic and logic-based formal framework (hybrid) to find the best service among many candidate services by considering the limitations of existing frameworks. Experimental results of the proposed framework show the improvement of the discovered results.

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“…In order to make people easier and faster to utilize the service resources, it becomes more and more important to gather the services on the IoT. Most of the current methods can only create automatic or semi-automatic service composition schemes, and lack support and consideration of real-time data and instant-situation information, so they cannot achieve dynamic adaptive aggregation of services [3].…”

Section: Editorialmentioning

confidence: 99%