Communication-Computing Convergence Technique for Connected Machines 


Vol. 47,  No. 4, pp. 611-614, Apr.  2022
10.7840/kics.2022.47.4.611


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  Abstract

Evolving immersive services such as digital twin and metaverse require a vast amount of computing power and extreme energy consumption. In order to support such immersive services with a mobile device which in general has much less computing power than a desktop PC and server, offloading of the computation is essential. In this paper, we propose a computation offloading algorithm considering practical overhead and power consumption of the wireless network standards. From numerical evaluation, we show that the proposed decision making algorithm can decrease the latency and improve the energy consumption efficiency.

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  Cite this article

[IEEE Style]

B. Lee and J. Noh, "Communication-Computing Convergence Technique for Connected Machines," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 4, pp. 611-614, 2022. DOI: 10.7840/kics.2022.47.4.611.

[ACM Style]

Byungju Lee and Jung-Hoon Noh. 2022. Communication-Computing Convergence Technique for Connected Machines. The Journal of Korean Institute of Communications and Information Sciences, 47, 4, (2022), 611-614. DOI: 10.7840/kics.2022.47.4.611.

[KICS Style]

Byungju Lee and Jung-Hoon Noh, "Communication-Computing Convergence Technique for Connected Machines," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 4, pp. 611-614, 4. 2022. (https://doi.org/10.7840/kics.2022.47.4.611)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880