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Services for Cloud-to-Thing Computing Continnum

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 March 2020) | Viewed by 10720

Special Issue Editors


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Guest Editor
Departament de Ciències de Computació, Universitat Politècnica de Catalunya (BarcelonaTech), 08034 Barcelona, Spain
Interests: Internet of Things; edge computing; distributed computing; optimisation algorithms; collective intelligence; security and privacy
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Computer Science, Hubei University of Technology,Wuhan, China
Interests: Big data; Internet of Things; information security; cloud computation; public key cryptography
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Computer Science, China University Of Geosciences, Wuhan, China
Interests: cryptography; social network; Internet of Things, cloud computation; blockchain

Special Issue Information

Dear Colleagues,

This Special Issue is aimed to publishing both review and original research articles related to Services for Cloud-to-thing Computing Continuum. In the era of IoT and big data, many resource-constrained devices such as sensors, embedding equipments on vehicular networks, mobile phones will be used to collect data for analysis by using 4G/5G networks. The adventure of cloud computing allows these devices to outsource their data on the Cloud, thus greatly reducing the burden of local storage and computation. The paradigm of Cloud-to-things computing is essentially becoming popular for many modern information systems. Papers on key IoT-enabling technologies related to sensors, vehicular networks, actuators and machine intelligence, development and deployment of IoT tools and platforms to ensure scalability, security, reliability, and efficiency are particular welcome. Potential interesting topics also include vehicular networks and systems, services for real-time and adaptive systems, privacy of exchanged information among vehicles, anonymization of information, Cloud-to-things paradigm, device software development such as minimal operating systems, secure communication of IoT with other software layers from edge computing to the Cloud, best practices for Cloud-to-things development, test beds, and quality assurance.

Prof. Dr. Fatos Xhafa
Prof. Dr. Xu An Wang
Prof. Dr. Mingwu Zhang
Prof. Dr. Wei Ren
Guest Editors

Manuscript Submission Information

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Keywords

  • Services
  • Cloud-to-things paradigm
  • Secure communication
  • Adaptive systems
  • Privacy and anonymization of information
  • Cloud-to-things development
  • Test beds
  • Quality assurance

Published Papers (2 papers)

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Research

30 pages, 11700 KiB  
Article
End-to-End QoS “Smart Queue” Management Algorithms and Traffic Prioritization Mechanisms for Narrow-Band Internet of Things Services in 4G/5G Networks
by Mykola Beshley, Natalia Kryvinska, Marian Seliuchenko, Halyna Beshley, Elhadi M. Shakshuki and Ansar-Ul-Haque Yasar
Sensors 2020, 20(8), 2324; https://doi.org/10.3390/s20082324 - 19 Apr 2020
Cited by 41 | Viewed by 6478
Abstract
This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT [...] Read more.
This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT controller. A method for allocating uplink and downlink resources of the LTE/NB-IoT hybrid technology is applied to ensure the Quality of Service (QoS) from end-to-end. This method considers scheduling traffic/resources on the NB-IoT controller, which allows eNodeB planning to remain unchanged. This paper also proposes a prioritization approach within the IoT traffic to provide End-to-End (E2E) QoS in the integrated LTE/NB-IoT network. Further, we develop “smart queue” management algorithms for the IoT traffic prioritization. To demonstrate the feasibility of our approach, we performed a number of experiments using simulations. We concluded that our proposed approach ensures high end-to-end QoS of the real-time traffic by reducing the average end-to-end transmission delay. Full article
(This article belongs to the Special Issue Services for Cloud-to-Thing Computing Continnum)
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24 pages, 5669 KiB  
Article
Obtaining World Coordinate Information of UAV in GNSS Denied Environments
by Chengbin Chen, YaoYuan Tian, Liang Lin, SiFan Chen, HanWen Li, YuXin Wang and KaiXiong Su
Sensors 2020, 20(8), 2241; https://doi.org/10.3390/s20082241 - 15 Apr 2020
Cited by 29 | Viewed by 3746
Abstract
GNSS information is vulnerable to external interference and causes failure when unmanned aerial vehicles (UAVs) are in a fully autonomous flight in complex environments such as high-rise parks and dense forests. This paper presents a pan-tilt-based visual servoing (PBVS) method for obtaining world [...] Read more.
GNSS information is vulnerable to external interference and causes failure when unmanned aerial vehicles (UAVs) are in a fully autonomous flight in complex environments such as high-rise parks and dense forests. This paper presents a pan-tilt-based visual servoing (PBVS) method for obtaining world coordinate information. The system is equipped with an inertial measurement unit (IMU), an air pressure sensor, a magnetometer, and a pan-tilt-zoom (PTZ) camera. In this paper, we explain the physical model and the application method of the PBVS system, which can be briefly summarized as follows. We track the operation target with a UAV carrying a camera and output the information about the UAV’s position and the angle between the PTZ and the anchor point. In this way, we can obtain the current absolute position information of the UAV with its absolute altitude collected by the height sensing unit and absolute geographic coordinate information and altitude information of the tracked target. We set up an actual UAV experimental environment. To meet the calculation requirements, some sensor data will be sent to the cloud through the network. Through the field tests, it can be concluded that the systematic deviation of the overall solution is less than the error of GNSS sensor equipment, and it can provide navigation coordinate information for the UAV in complex environments. Compared with traditional visual navigation systems, our scheme has the advantage of obtaining absolute, continuous, accurate, and efficient navigation information at a short distance (within 15 m from the target). This system can be used in scenarios that require autonomous cruise, such as self-powered inspections of UAVs, patrols in parks, etc. Full article
(This article belongs to the Special Issue Services for Cloud-to-Thing Computing Continnum)
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