Telecommunications Science ›› 2022, Vol. 38 ›› Issue (3): 172-182.doi: 10.11959/j.issn.1000-0801.2022060
• Research and Development • Previous Articles
Shengchao XU1, Maohua XIONG1, Tianqi ZHOU2
Revised:
2022-01-24
Online:
2022-03-20
Published:
2022-03-01
Supported by:
CLC Number:
Shengchao XU, Maohua XIONG, Tianqi ZHOU. Approach of glowworm swarm optimization based virtual machine placement[J]. Telecommunications Science, 2022, 38(3): 172-182.
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算法 | 参数 | 具体值 |
GSO-VM | p荧光素衰减系数(0<p<1) | 0.4 |
物理主机 j的局部径向范围的最大传感范围ωs | 0.6 | |
相邻区域的变化率 θ | 0.08 | |
最佳的邻居的数目kt | 5 | |
移动的步长尺寸s | 0.03 | |
荧光素初始值 | 0.05 | |
FPA[ | 种群大小 | 50, 100, 150, 200 |
标准函数gamma | 1.5 | |
随机步长 L | [0, 1] | |
转换概率 p | 0.9 | |
最大迭代次数 | 1 000 | |
GA[ | 种群大小 | 50, 100, 150, 200 |
交叉率 | 0.5 | |
变异率 | 0.01 | |
最大迭代次数 | 1 000 | |
ACO[ | 蚁群算法的蚂蚁个数 | 50, 100, 150, 200 |
挥发因子 p | 0.4 | |
信息素追踪权重α | 0.3 | |
启发式信息权重β | 1 | |
信息素更新常量 Q | 100 | |
最大迭代次数 | 1 000 |
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