TY - JOUR
T1 - Adaptive Computation Offloading with Task Scheduling Minimizing Reallocation in VANETs
AU - Gong, Minyeong
AU - Yoo, Younghwan
AU - Ahn, Sanghyun
N1 - Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - Computation Offloading (CO) can accelerate application running through parallel processing. This paper proposes a method called vehicular adaptive offloading (VAO) in which vehicles in vehicular ad-hoc networks (VANETs) offload computationally intensive tasks to nearby vehicles by taking into account the dynamic topology change of VANETs. In CO, task scheduling has a huge impact on overall performance. After representing the precedence relationship between tasks with a directed acyclic graph (DAG), VAO in the CO requesting vehicle assigns tasks to neighbors so that it can minimize the probability of task reallocations caused by connection disruption between vehicles in VANETs. The simulation results showed that the proposed method decreases the number of reallocations by 45.4%, as compared with the well-known task scheduling algorithms HEFT and Max-Min. Accordingly, the schedule length of entire tasks belonging to one application is shortened by 14.4% on average.
AB - Computation Offloading (CO) can accelerate application running through parallel processing. This paper proposes a method called vehicular adaptive offloading (VAO) in which vehicles in vehicular ad-hoc networks (VANETs) offload computationally intensive tasks to nearby vehicles by taking into account the dynamic topology change of VANETs. In CO, task scheduling has a huge impact on overall performance. After representing the precedence relationship between tasks with a directed acyclic graph (DAG), VAO in the CO requesting vehicle assigns tasks to neighbors so that it can minimize the probability of task reallocations caused by connection disruption between vehicles in VANETs. The simulation results showed that the proposed method decreases the number of reallocations by 45.4%, as compared with the well-known task scheduling algorithms HEFT and Max-Min. Accordingly, the schedule length of entire tasks belonging to one application is shortened by 14.4% on average.
KW - computation offloading
KW - directed acyclic graph
KW - task scheduling
KW - vehicular ad hoc network
UR - http://www.scopus.com/inward/record.url?scp=85127433302&partnerID=8YFLogxK
U2 - 10.3390/electronics11071106
DO - 10.3390/electronics11071106
M3 - Article
AN - SCOPUS:85127433302
SN - 2079-9292
VL - 11
JO - Electronics (Switzerland)
JF - Electronics (Switzerland)
IS - 7
M1 - 1106
ER -