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Research on Computational Load Balancing for Massively Parallel Tasks Based on Adaptive Iterative Algorithm

Wenwen Huang

Wenwen Huang

Department of Electronic Information Engineering, Jining PolytechnicJining, China
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Huang, Wenwen
, 
Xiaofang Hu

Xiaofang Hu

Department of Art and Design, Jining PolytechnicJining, China
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Hu, Xiaofang
 y 
Fengfei Yang

Fengfei Yang

Comprehensive Support Department, Jining PolytechnicJining, China
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Yang, Fengfei
  
29 sept 2025
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Publicado en línea: 29 sept 2025
Recibido: 06 feb 2025
Aceptado: 10 may 2025
DOI: https://doi.org/10.2478/amns-2025-1104
Palabras clave
© 2025 Wenwen Huang, Xiaofang Hu and Fengfei Yang, published by Sciendo.
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Adaptive crossover probability
Adaptive crossover probability

Figure 2.

Adaptive mutation probability
Adaptive mutation probability

Figure 3.

Flow chart of improved genetic algorithm
Flow chart of improved genetic algorithm

Figure 4.

The solution of the three algorithms
The solution of the three algorithms

Figure 5.

The solution time and the cpoccupancy rate of the three algorithms
The solution time and the cpoccupancy rate of the three algorithms

Figure 6.

Test results for large-scale use cases
Test results for large-scale use cases

Figure 7.

Load statistics for tasks
Load statistics for tasks

Figure 8.

The result of the convergence of load inequality
The result of the convergence of load inequality

Figure 9.

The number of times required to spread to 99% of the process
The number of times required to spread to 99% of the process

Figure 10.

Different algorithms are overhead for different systems
Different algorithms are overhead for different systems

Figure 11.

Different algorithms are accelerating in different systems
Different algorithms are accelerating in different systems

Small-scale test case 1

Test number R1 R2 R3 R4 R5 R6 R7 Ri
Resource number
1 1 1 1 0 0 0 0 6
2 0 0 1 0 0 0 0 15
3 0 1 0 1 0 0 0 5
4 0 0 0 0 1 0 0 4
5 1 0 0 0 1 0 0 22
6 0 1 1 0 0 1 0 7
7 0 0 0 0 0 0 1 43
8 0 1 0 1 0 0 0 14
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