An energy-aware resource allocation method for avionics systems based on improved ant colony optimization algorithm

Xiaoyan Du, Chenglie Du, Jinchao Chen, Yifan Liu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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%.

Original languageEnglish
Article number108515
JournalComputers and Electrical Engineering
Volume105
DOIs
StatePublished - Jan 2023

Keywords

  • Avionics systems
  • Energy-aware
  • Improved ant colony optimization
  • Resource allocation

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