Literature Database Entry

dressler2024virtualized-lecture

Falko Dressler, "6G Virtualized Edge Computing on Cars for Resilient Edge AI," Invited Lecture, Distinguished Lecture Series, SFB 1053 MAKI, Technical University of Darmstadt, Darmstadt, Germany, February 09, 2024.

Abstract

As we move from 5G to 6G, edge computing is one of the concepts that needs revisiting. Its core idea is still intriguing: Instead of sending all data and tasks from an end user's device to the cloud, edge servers deployed in close proximity to the user serve as proxy for the cloud. This is particularly interesting for upcoming machine learning (ML)-based intelligent services, which require substantial computational and networking performance for continuous model training. Yet this promising idea is hampered by the limited number of such edge servers. In a parallel universe, car makers have discussed challenges and opportunities of the connected cars vision in relation to the need for distributed data management solutions ranging from the vehicle to the mobile edge and to the data centers. As a new concept, vehicle micro clouds have been proposed that bridge the gap between fully distributed vehicular networks based on short range device to device communication and 5G+ based infrastructure for centralized solutions. Taking both concepts together, we discuss a way forward, namely the virtual edge computing (V-Edge) concept. V-Edge helps bridging the gap between cloud, edge, and fog by virtualizing all available resources including the end users' devices and making these resources widely available. Thus, V-Edge acts as an enabler for novel microservices as well as cooperative computing solutions in next-generation networks. We introduce the general V-Edge architecture, and we characterize some of the key research challenges to overcome, to enable wide-spread and intelligent edge services.

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Falko Dressler

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@misc{dressler2024virtualized-lecture,
    author = {Dressler, Falko},
    title = {{6G Virtualized Edge Computing on Cars for Resilient Edge AI}},
    howpublished = {Invited Lecture},
    publisher = {Distinguished Lecture Series, SFB 1053 MAKI, Technical University of Darmstadt},
    location = {Darmstadt, Germany},
    day = {09},
    month = {02},
    year = {2024},
   }
   
   

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Last modified: 2024-04-27