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Title	Guest Editorial Special Issue On Collaborative Intelligence For Green Internet Of Things In The 6G Era
ID_Doc	28575
Authors	Wu C.; Yau K.-L.A.; Zhang Z.; Turgut D.; Mao S.
Year	2023
Published	IEEE Transactions on Green Communications and Networking, 7, 2
DOI	http://dx.doi.org/10.1109/TGCN.2023.3274248
Abstract	In the 6G era, with the hyper-connectivity among humans and everything, we are anticipating Internet of Things (IoT) applications in various fields, including smart city, smart factory, smart home, smart grid, e-health, and smart transportation, accompanied by new services with rich experiences, such as truly immersive VR/AR/MR (XR), high-fidelity mobile hologram, and digital twins. However, in order to facilitate these emerging IoT applications, we have to investigate the collaboration among different network entities to achieve joint optimization under heterogeneous communication, caching, and computing resources. Recently, artificial intelligence (AI) based approaches have been attracting great interest in empowering computer systems. Since the centralized learning approaches face many challenges in terms of scalability, some collaborative learning approaches, such as federated learning and multi-agent systems, have been investigated recently to reduce networking overhead and improve learning efficiency. Based on refined AI technologies, collaborative intelligence can achieve better decisions by aggregating knowledge and enabling efficient coordination among multiple agents with a light communication overhead. It is envisioned that the collaborative intelligence is the enabler for collaborative IoT systems. © 2017 IEEE.
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