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Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs

Authors :
Soret, Beatriz
Nguyen, Lam D.
Seeger, Jan
Bröring, Arne
Issaid, Chaouki Ben
Samarakoon, Sumudu
Gabli, Anis El
Kulkarni, Vivek
Bennis, Mehdi
Popovski, Petar
Source :
IEEE Transactions on Green Communications and Networking 2021
Publication Year :
2021

Abstract

An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications, examples of which include highly automated manufacturing cells or autonomously interacting harvesting machines. Energy efficiency is key in such edge environments, since they are often based on an infrastructure that consists of wireless and battery-run devices, e.g., e-tractors, drones, Automated Guided Vehicle (AGV)s and robots. The total energy consumption draws contributions from multipleiIoTe technologies that enable edge computing and communication, distributed learning, as well as distributed ledgers and smart contracts. This paper provides a state-of-the-art overview of these technologies and illustrates their functionality and performance, with special attention to the tradeoff among resources, latency, privacy and energy consumption. Finally, the paper provides a vision for integrating these enabling technologies in energy-efficient iIoTe and a roadmap to address the open research challenges<br />Comment: Accepted for publication in IEEE Transactions on Green Communication and Networking

Details

Database :
arXiv
Journal :
IEEE Transactions on Green Communications and Networking 2021
Publication Type :
Report
Accession number :
edsarx.2110.01686
Document Type :
Working Paper
Full Text :
https://doi.org/10.1109/TGCN.2021.3138792