TY - JOUR
T1 - An energy-aware resource allocation method for avionics systems based on improved ant colony optimization algorithm
AU - Du, Xiaoyan
AU - Du, Chenglie
AU - Chen, Jinchao
AU - Liu, Yifan
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/1
Y1 - 2023/1
N2 - With the growing number of resources and the expansion of the scale of avionics systems, the problem of energy consumption has become increasingly prominent. Even though high energy consumption increases energy costs and greenhouse gas emissions, it has a significant effect on the reliability and availability of a system. To efficiently reduce energy consumption and improve the performance of avionics systems, an energy-aware resource allocation method based on an improved ant colony optimization algorithm is proposed. First, a mathematical model of resource allocation is established, which reflects the relationship between task requirements and resource energy consumption. Then, an improved ant colony optimization algorithm is proposed to allocate heterogeneous resources, which contributes to minimizing the makespan and achieving low energy consumption. Finally, experimental results show that our proposed algorithm outperforms other existing algorithms. In particular, it reduces makespan by at least 5.48% and reduces energy consumption by at least 5.89%.
AB - With the growing number of resources and the expansion of the scale of avionics systems, the problem of energy consumption has become increasingly prominent. Even though high energy consumption increases energy costs and greenhouse gas emissions, it has a significant effect on the reliability and availability of a system. To efficiently reduce energy consumption and improve the performance of avionics systems, an energy-aware resource allocation method based on an improved ant colony optimization algorithm is proposed. First, a mathematical model of resource allocation is established, which reflects the relationship between task requirements and resource energy consumption. Then, an improved ant colony optimization algorithm is proposed to allocate heterogeneous resources, which contributes to minimizing the makespan and achieving low energy consumption. Finally, experimental results show that our proposed algorithm outperforms other existing algorithms. In particular, it reduces makespan by at least 5.48% and reduces energy consumption by at least 5.89%.
KW - Avionics systems
KW - Energy-aware
KW - Improved ant colony optimization
KW - Resource allocation
UR - http://www.scopus.com/inward/record.url?scp=85143882104&partnerID=8YFLogxK
U2 - 10.1016/j.compeleceng.2022.108515
DO - 10.1016/j.compeleceng.2022.108515
M3 - 文章
AN - SCOPUS:85143882104
SN - 0045-7906
VL - 105
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
M1 - 108515
ER -