Adaptive V2X User Selection and Resource Allocation for Ultra-Dense 5G HetNet Network

Bouaziz, Amal; Saddoud, Ahlem; Fourati, Lamia Chaari; Chaouchi, Hakima

doi:10.1109/iwcmc51323.2021.9498912

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…Nowadays, with the rapid development of communication technology, the increasing number of smart devices increases the burden of network transmission and makes the data transmission delay more and more obvious [1,2]. e proposal of mobile edge computing solves the computationally intensive computing tasks to a certain extent [3][4][5]. e proposal of the Internet of Vehicles (IoV) system realizes a wireless connection between the drive test unit and pedestrians.…”

Section: Introductionmentioning

confidence: 99%

Computing Resource Allocation Strategy Based on Mobile Edge Computing in Internet of Vehicles Environment

Gao

2022

Mobile Information Systems

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The rapid growth of the Internet of Vehicles applications leads to unreasonable resource allocation, task computing delay, and large energy consumption. To solve this problem, this paper proposes a computing resource allocation strategy based on mobile edge computing in the Internet of Vehicles environment. Firstly, we analyze the process of mobile edge computing network and resource allocation. Then, it is improved by introducing the Halton sequence into the traditional genetic algorithm, and the difference between populations is reduced by canceling the randomness to generate an initial population with smaller individual differences. Furthermore, by optimizing the parameter setting method of traditional genetic algorithm, the crossover probability and mutation probability that change dynamically with fitness value are given, which improves the accuracy of the algorithm. Finally, the simulation results show that under the premise of the same number of tasks, the average delay and total cost of the proposed strategy are also the smallest. When the number of tasks is 45, the average delay of the proposed method is 0.32 s and the total cost is 0.34, which are better than the comparison method. Simulation results show that the improved algorithm has more advantages in delay and overhead.

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Section: Introductionmentioning

confidence: 99%

Computing Resource Allocation Strategy Based on Mobile Edge Computing in Internet of Vehicles Environment

Gao

2022

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

Adaptive V2X User Selection and Resource Allocation for Ultra-Dense 5G HetNet Network

Cited by 1 publication

References 9 publications

Computing Resource Allocation Strategy Based on Mobile Edge Computing in Internet of Vehicles Environment

Computing Resource Allocation Strategy Based on Mobile Edge Computing in Internet of Vehicles Environment

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