On enhancing transmission performance for iov based on improved greedy algorithm
Longqi Wei, Junyuan Feng, Yancong Deng · Applied and Computational Engineering · 2023
Nowadays, the development of 5G and IoT technology can be observed from abundance of their applications, such as VR/AR/MR, communication, healthcare, transportation and so on. Some of these applications are in need of quality improvement like delay and resource consumption decrease since the need of users and devices about the relatively developed technique gradually increase as well. About this kind of QoS improvement in the field of VANET, this paper first has a brief review on this concept and related key word and makes use of the concept of Edge Computing, eventually provides information about the research that focuses on the optimization of Task Offloading function by proposing a new algorithm. The new algorithm consists of 3 C++ programs and determines the relatively effective task offloading strategy by taking both calculating resource consumption and communication latency into consideration. In order to prove the developed performance of the proposed algorithm, paper uses other two kinds of algorithms to have comparison, finally reaches the conclusion that proposed algorithm has the best system cost performance among the comparison objects.