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 language | English |
|---|---|
| Title of host publication | Proceedings - 2023 IEEE International Symposium on Workload Characterization, IISWC 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 221-222 |
| Number of pages | 2 |
| ISBN (Electronic) | 9798350303179 |
| DOIs | |
| State | Published - 2023 |
| Event | 26th IEEE International Symposium on Workload Characterization, IISWC 2023 - Gent, Belgium Duration: 1 Oct 2023 → 3 Oct 2023 |
Publication series
| Name | Proceedings - 2023 IEEE International Symposium on Workload Characterization, IISWC 2023 |
|---|
Conference
| Conference | 26th IEEE International Symposium on Workload Characterization, IISWC 2023 |
|---|---|
| Country/Territory | Belgium |
| City | Gent |
| Period | 1/10/23 → 3/10/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Automotive system
- Computation offloading
- Connected vehicle