Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs
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Abstract (arXiv)
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
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 35 of its 83 references that are in the map. First posted on arXiv 4 Oct 2021.
Builds on
35 of 83 references.
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23 more
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Citing papers per year: 2022: 2; 2023: 1.
3 papers.