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MEC-based architecture for interoperable and trustworthy internet of moving things

Digital Communications and Networks 2023年第1期9卷 270-279页

作者： Jesus Sanchez-Gomez Rafael Marin-Perez Ramon Sanchez-Iborra Miguel Angel Zamora Department of Information and Communications Engineering University of MurciaMurciaSpain Odin Solutions S.L. MurciaSpain University Center of Defense San Javier Air Force BaseMurciaSpain

The expansion of the internet of moving things(IoMT)leads to limitless and continuous working playgrounds exploited by highly dynamic end devices.This requires the adoption of multi-Radio Access Technologies(RATs)-based strategies to provide IoMT units with ubiquitous connectivity.To this end,the development of secure bootstrapping and authentication mechanisms is necessary to permit the secure operation of end devices.Given the transmission and power limitations of these elements,current cryptographic solutions do not address these stringent requirements.For that reason,in the study we present a Multi-Access Edge Computing(MEC)-based endto-end architecture that enables an efficient and secure authentication and key agreement between end devices and network servers over heterogeneous resource-limited networks such as the Low Power Wide Area Networks(LPWANs).Our proposal is based on the Authentication,Authorization,and Accounting(AAA)architecture and the recent internet Engineering Task Force initiatives Static Context Header Compression and Low-Overhead CoAP-EAP.The results obtained from experimental tests reveal the validity of the proposal as it enables constrained IoMT devices to gain IPv6 connectivity as well as performs end-to-end secure authentication with notable reliability and controlled latency.

关键词： internet of moving things LPWAN Authentication LO-CoAP-EAP SCHC

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Machine Learning-Based Radio Access Technology Selection in the internet of moving things

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China Communications 2021年第7期18卷 13-24页

作者： Ramon Sanchez-Iborra Luis Bernal-Escobedo Jose Santa Dept.Engineering and Applied Techniques University Centre of Defence at the Spanish Air Force Academy30729 San JavierSpain Dept.Information and Communication Engineering University of Murcia30100 MurciaSpain Dept.of Electronics Computing Technology and ProjectsTechnical University of Cartagena30202 CartagenaSpain

The internet of moving things(IoMT)takes a step further with respect to traditional static IoT deployments.In this line,the integration of new eco-friendly mobility devices such as scooters or bicycles within the Cooperative-Intelligent Transportation Systems(C-ITS)and smart city ecosystems is crucial to provide novel services.To this end,a range of communication technologies is available,such as cellular,vehicular WiFi or Low-Power Wide-Area Network(LPWAN);however,none of them can fully cover energy consumption and Quality of Service(QoS)requirements.Thus,we propose a Decision Support System(DSS),based on supervised Machine Learning(ML)classification,for selecting the most adequate transmission interface to send a certain message in a multi-Radio Access Technology(RAT)set up.Different ML algorithms have been explored taking into account computing and energy constraints of IoMT enddevices and traffic type.Besides,a real implementation of a decision tree-based DSS for micro-controller units is presented and evaluated.The attained results demonstrate the validity of the proposal,saving energy in communication tasks as well as satisfying QoS requirements of certain urgent messages.The footprint of the real implementation on an Arduino Uno is 444 bytes and it can be executed in around 50µs.

关键词： internet of moving things multi-RAT CITS classification personal mobility

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Clustering spatio-temporal bi-partite graphs for finding crowdsourcing communities in IoMT networks

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Big Earth Data 2021年第1期5卷 24-48页

作者： Kaine Black Monica Wachowicz Department of Geodesy and Geomatics Engineering University of New BrunswickFrederictonCanada School of Geospatial Science RMIT UniversityMelbourneAustralia

The internet of moving things is rapidly becoming a reality where intelligent devices and infrastructures are fostering real-time data sus-tainability in smart cities and advancing crowdsourced tasks to improve energy consumption,waste management,and traffic operations.These intelligent devices create a complex network scenario in which they often move together or in conjunction with one another to complete crowdsourced tasks.Our research premise is that mobility relationships matter when performing these tasks,and therefore,a graph model based on representing the changes in mobility relation-ships is needed to help identify the neighbour devices that are moving close to one another in our physical world but also seamlessly con-nected in their virtual world.We propose a bi-partite community mobility graph model for linking intelligent devices in both virtual and physical worlds,as well as reaching a trade-off between crowd-sourced tasks designed with explicit and implicit citizen participation.This paper aims to explore a bi-partite graph as a promising spatiotemporal representation of IoMT networks since changes in mobility relationships over time can indicate volunteer organisation at the device and community levels.The Louvain community detection method is proposed to find communities of intelligent devices to reveal a value conscious participation of citizens.The proposed bi-partite graph model is evaluated using a real-world scenario in transportation,confirming the main role of evolving communities in developing crowdsourcing IoMT networks.

关键词： Bi-partite graph modelling internet of moving things crowdsourcing

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