A Resource Scheduling Algorithm with Low Latency for 5G Networks

被引：0
|
作者：
Wang C. [1 ,2 ]
Tang H. [1 ,2 ]
You W. [1 ,2 ]
Wang X. [1 ,2 ]
Yuan Q. [1 ,2 ]
机构：
[1] National Digital Switching System Engineering and Technological Research Center, Zhengzhou
[2] National Engineering Laboratory for Mobile Network Security, Beijing
来源：
Tang, Hongbo | 2018年 / Xi'an Jiaotong University卷 / 52期
关键词：
5G network; Bandwidth allocation; Genetic algorithm; Network function virtualization; Scheduling; Tabu search;
D O I：
10.7652/xjtuxb201804017
中图分类号：
学科分类号：
摘要：
A resource scheduling algorithm based on hybrid genetic algorithm and tabu search (named GATS) is proposed to solve the problem that the existing schedule methods are difficult to meet the requirement of the mobile communication with low latency. First, a dynamic bandwidth allocation policy of virtual links is established using an integer linear programming. Then, the transmission delay of data traffic in virtual links is introduced based on a traditional flexible job shop scheduling model, and the corresponding resource scheduling model for 5G is established. Owing to the complexity of the scheduling problem, the resource scheduling algorithm based on hybrid genetic algorithm and tabu search is developed for solving the problem efficiently. The algorithm introduces tabu search in optimization process of the genetic algorithm to balance capabilities of global and local searches, solves the problem of premature convergence of the genetic algorithm, and obtains better scheduling solutions. Simulation results show that the GATS algorithm outperforms the GA-BA algorithm in reducing the scheduling makespan by 17%, and caters to 5G service with stringent delay requirements, thereby increases users' experience and operators' revenues. © 2018, Editorial Office of Journal of Xi'an Jiaotong University. All right reserved.
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页码：117 / 124
页数：7
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