Empirical Composite Workload Analysis for RSU-Assisted Computation Offloading in Connected Vehicle Services

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Abstract

The RSU(Road-Side Unit)-assisted computation offloading allows vehicles to use the RSU's compute resources to provide connected services which cannot be done due to on-board resource limitations. We propose the empirical analysis framework that can systematically characterize such RSU's compute workloads. We first formalize the relationship of the three aspects: the local load (generated from vehicles), the composite load (imposed on RSUs) and the traffic flow (mobility patterns of vehicles). Then, our framework takes the models of the local load and the traffic flow as input, and produces the RSUs' composite loads as an output. We provide the quantitative analysis to show how the RSU's composite loads change in varying traffic flows in some areas of New York City with different offload patterns.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE International Symposium on Workload Characterization, IISWC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages221-222
Number of pages2
ISBN (Electronic)9798350303179
DOIs
StatePublished - 2023
Event26th IEEE International Symposium on Workload Characterization, IISWC 2023 - Gent, Belgium
Duration: 1 Oct 20233 Oct 2023

Publication series

NameProceedings - 2023 IEEE International Symposium on Workload Characterization, IISWC 2023

Conference

Conference26th IEEE International Symposium on Workload Characterization, IISWC 2023
Country/TerritoryBelgium
CityGent
Period1/10/233/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Automotive system
  • Computation offloading
  • Connected vehicle

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