Toward Immersive Experience: Evaluation for Interactive Network Services

IEEE Network ◽  
2022 ◽  
pp. 1-7
Author(s):  
Yun Gao ◽  
Xin Wei ◽  
Jianxin Chen ◽  
Liang Zhou
2021 ◽  
Author(s):  
Evgeniya Sergeyevna Zharina ◽  
Yulia Sergeevna Riesen

Data visualization finds its application in many disciplines as the modern equivalent of visual communication, and at the same time does not belong to any specific field, but has its own significance in the presentation of information, ready-made data through the use of visualization tools. In the process of scientific communication, the problem arises of the possibility of methods for presenting information that will be understandable to the user. Therefore, in the process of the exponential growth of the documentary flow of information, the need for compression of information, visibility increases, while maintaining the integrity of the display of the main idea and compact generalization of data. The article discusses data visualization as a way of presenting information and options for using interactive network services to visualize contextual information. Using specific examples, the application of such technologies (services) is tested and presented to present ready-made data or information, which is a more visual, accessible way for perception, understanding and memorization. The study of online services as data visualization tools can be applied and have practical value in educational processes. The aim of the study was: search and study of effective methods of data presentation and clearly demonstrate the use of this method through online services as data visualization tools. The relevance of the work consists in the use of methods for presenting information as services and tools for automating the presentation of analysis, stages or results of work.


2017 ◽  
Vol 2 (2) ◽  
pp. 470-478
Author(s):  
Emad H. Al-Hemiary
Keyword(s):  

2021 ◽  
pp. 101412
Author(s):  
Vitor A. Cunha ◽  
Daniel Corujo ◽  
Joao P. Barraca ◽  
Rui L. Aguiar

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1342
Author(s):  
Borja Nogales ◽  
Miguel Silva ◽  
Ivan Vidal ◽  
Miguel Luís ◽  
Francisco Valera ◽  
...  

5G communications have become an enabler for the creation of new and more complex networking scenarios, bringing together different vertical ecosystems. Such behavior has been fostered by the network function virtualization (NFV) concept, where the orchestration and virtualization capabilities allow the possibility of dynamically supplying network resources according to its needs. Nevertheless, the integration and performance of heterogeneous network environments, each one supported by a different provider, and with specific characteristics and requirements, in a single NFV framework is not straightforward. In this work we propose an NFV-based framework capable of supporting the flexible, cost-effective deployment of vertical services, through the integration of two distinguished mobile environments and their networks: small sized unmanned aerial vehicles (SUAVs), supporting a flying ad hoc network (FANET) and vehicles, promoting a vehicular ad hoc network (VANET). In this context, a use case involving the public safety vertical will be used as an illustrative example to showcase the potential of this framework. This work also includes the technical implementation details of the framework proposed, allowing to analyse and discuss the delays on the network services deployment process. The results show that the deployment times can be significantly reduced through a distributed VNF configuration function based on the publish–subscribe model.


2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.


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