@inproceedings{duc_vtc2021,
title = {A Run-time Dynamic Computation Offloading Strategy in Vehicular Edge Computing},
author = {Hong Duc Nguyen and Shunsuke Aoki and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://events.vtsociety.org/vtc2021-fall/
https://ieeexplore.ieee.org/document/9625245},
doi = {10.1109/VTC2021-Fall52928.2021.9625245},
year = {2021},
date = {2021-09-27},
urldate = {2021-09-27},
booktitle = {2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)},
publisher = {IEEE},
address = {Online},
abstract = {In vehicular edge computing (VEC), offloading the tasks to the nearby resource-rich edge servers helps each vehicle enhance computational capabilities and improve in-vehicle applications' performance. However, the concentration of travel at specific spaces and times poses significant challenges on the load-balancing and scheduling of computation tasks at the edge servers. This paper studies a low-complexity dynamic online offloading strategy that efficiently reduces task delay and computing resource consumption in the multi-user, multiserver vehicular edge computing scenarios. Our design addresses issues of computation task placement and execution order of the tasks on each server. We use a realistic approach that vehicles generate tasks over time, and the set of the tasks is unknown in advance so that the offloading decisions are made in runtime. Extensive simulations are conducted on a real mobility trace of Luxembourg city, and the results show that the proposed algorithm effectively improves the offloading utility of the system.},
keywords = {Connected vehicles, Edge computing, Off-loading, Vehicular networks},
pubstate = {published},
tppubtype = {inproceedings}
}