An energy-aware resource allocation method for avionics systems based on improved ant colony optimization algorithm. (January 2023)

• Record Type: Journal Article
• Authors: Du, Xiaoyan; Du, Chenglie; Chen, Jinchao; Liu, Yifan
• Is Part Of: Computers & electrical engineering. Volume 105(2023)
• Publication Date: 2023-01
• Subjects: Resource allocation -- Energy-aware -- Improved ant colony optimization -- Avionics systems; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.108515
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: 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%. Graphical abstract: Highlights: Resource allocation becomes more challenging when coupled with energy-related issues. The resource allocation model reflects the relationship between tasks and resources. A dynamic allocation method is used to close the redundant resources. An improved ant colony optimization algorithm is used to reduce energy consumption.