@Article{jiot.2020.011792,
AUTHOR = {Yuxin Xu, Zilong Jin, Xiaorui Zhang, Lejun Zhang},
TITLE = {An Optimization Scheme for Task Offloading and Resource Allocation in  Vehicle Edge Networks},
JOURNAL = {Journal on Internet of Things},
VOLUME = {2},
YEAR = {2020},
NUMBER = {4},
PAGES = {163--173},
URL = {http://www.techscience.com/jiot/v2n4/40249},
ISSN = {2579-0080},
ABSTRACT = {The vehicle edge network (VEN) has become a new research hotspot 
in the Internet of Things (IOT). However, many new delays are generated during 
the vehicle offloading the task to the edge server, which will greatly reduce the 
quality of service (QOS) provided by the vehicle edge network. To solve this 
problem, this paper proposes an evolutionary algorithm-based (EA) task 
offloading and resource allocation scheme. First, the delay of offloading task to 
the edge server is generally defined, then the mathematical model of problem is 
given. Finally, the objective function is optimized by evolutionary algorithm, 
and the optimal solution is obtained by iteration and averaging. To verify the 
performance of this method, contrast experiments are conducted. The 
experimental results show that our purposed method reduces delay and improves 
QOS, which is superior to other schemes.},
DOI = {10.32604/jiot.2020.011792}
}