一种基于改进遗传算法的动静态负载均衡算法

doi:10.16180/j.cnki.issn1007-7820.2023.09.012

Abstract

Abstract:

In view of the problems that current load balancing algorithm affects system efficiency under low load and poor distribution efficiency under high load, based on Nginx server, a dynamic and static load balancing algorithm based on improved genetic algorithm is proposed in this study. The algorithm chooses to use server performance parameters based on CPU performance, memory performance, disk I/O and network bandwidth as server node performance evaluation indexes and static weighted polling algorithm weights under low load, and designs a dynamic load balancing algorithm under high load based on the change of node performance utilization rate as a percentage of the cluster average load utilization rate by introducing operation conversion thresholds and dynamic. By introducing the improved genetic algorithm of operation transition threshold and dynamic triangular function operation probability as the threshold calculation method, the transformation of static algorithm dominant area into dynamic algorithm dominant area is calculated. This study designs comparison experiments to verify that the proposed algorithm has better load balancing effect when compared with weighted polling algorithm, probabilistic meritocracy algorithm and dnfs_conn algorithm in the experimental environment, and has about 15% improvement in the values of average response time and actual concurrent connections when compared with dnfs_conn algorithm.

Key words: Nginx, load balancing, performance evaluation, server clustering, genetic algorithms, dynamic algorithm, static algorithms, weighted polling

CLC Number:

TP368.5

HU Yifei,BAO Ziqun,BAO Xiaoan. A Dynamic-Static Load Balancing Algorithm Based on Improved Genetic Algorithm[J].Electronic Science and Technology, 2023, 36(9): 79-85.

Figures/Tables 4

References 18

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CPU/GHz	内存/GB	I/O/MB·s^-1	带宽/Mbit·s^-1	节点数
3.6	8	410	50	3
2.8	8	300	20	3
2.8	4	350	10	3

A Dynamic-Static Load Balancing Algorithm Based on Improved Genetic Algorithm

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