@inproceedings{cba0837a4ec246938b5aef1360b0691e,
title = "Edge Intelligence in Mobile Nodes: Opportunistic Pipeline via 5G D2D for On-site Sensing",
abstract = "Foreseeing several potential use cases, this paper proposes a node-level edge intelligence (EI) based mobile pipeline computing concept in a Device-to-Device (D2D) communication setup and studies the related issues, where D2D is likely based on millimeter-wave (mmWave) in the 5G mobile communication. Different from traditional distributed computing systems, the proposed opportunistic system employs a chain of wirelessly pipelined resource-limited node-level edge devices (NEDs) on the move to handle real-time computation-intensive multi-stage processing for which current cloud computing technology may not be suitable. The feasibility of such a mobile pipeline can be anticipated as high-speed and low-latency wireless technologies get mature. We present a system model by defining the architecture and basic functions and introducing a possible optimal pipeline finding procedure. As part of the feasibility assessment, the impact of mmWave blockage on the pipeline stability is analyzed and examined for both single-pipeline and concurrent-multiple-pipeline scenarios. Our design and analysis results provide specific insight to guide system design and lay a foundation for further work along this line.",
author = "Guo, {Terry N.} and Hawzhin Mohammed and Hasan, {Syed R.}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022 ; Conference date: 26-09-2022 Through 29-09-2022",
year = "2022",
doi = "10.1109/VTC2022-Fall57202.2022.10012933",
language = "English (US)",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 IEEE 96th Vehicular Technology Conference, VTC 2022-Fall 2022 - Proceedings",
address = "United States",
}