TCOA: Triple-Check Offloading Algorithm for Roadside Units and Vehicular Microclouds in 5G Networks and Beyond

Next-generation intelligent transportation systems aim to achieve many cooperative perception and cooperative driving functions that require considerable computational resources. Offloading such tasks via mobile edge computing is considered part of the solution; this approach is currently being stud...

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Bibliographic Details
Published inIEEE access Vol. 11; p. 1
Main Authors Qiu, Bo-Jun, Hsieh, Cheng-Ying, Chen, Jyh-Cheng, Dressler, Falko
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
5G mobile communication
5G networks
Algorithms
Computation offloading
Computer architecture
Costs
Dynamic scaling
Edge computing
Instance leaving
Intelligent transportation systems
Mathematical models
Measurement
Mobile computing
Performance measurement
Queueing
Roadsides
RSU offloading
Servers
Task analysis
Time factors
Transportation networks
Vehicular microcloud
Wireless networks
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Summary:Next-generation intelligent transportation systems aim to achieve many cooperative perception and cooperative driving functions that require considerable computational resources. Offloading such tasks via mobile edge computing is considered part of the solution; this approach is currently being studied within the scope of 5G networks and beyond. In the automotive context, such edge systems could be roadside units (RSUs), which can easily be overloaded at peak times. Vehicular microcloud approaches have been proposed to overcome such problems by sharing the computational resources of nearby cars. In this study, we propose an offloading system architecture to enable such offloading in a vehicular microcloud interconnected by a 5G core network. We model the system as a queueing model to derive closed-form solutions for selected performance metrics. Based on our insights, we propose the triple-check offloading algorithm (TCOA) to obtain both the best offloading ratio of the vehicular microcloud to the entire offloading system and the optimal maximum number of the remaining vehicle instances in the vehicular microcloud. Our simulation results show that the proposed TCOA achieves better system performance than four other offloading schemes in terms of cost, response time, service rate, and cost response-time production service rate division (CRPSD).
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3303400