Power consumption minimization by distributive particle swarm optimization for luminance control and its parallel implementations
作者：
Highlights：
• Luminance control is formalized as a constrained search problem.
• Both power consumption minimization and sufficient illuminance are considered.
• A distributive PSO-based algorithm is developed to do an effective search.
• Parallel implementations in GPU and Hadoop MapReduce are developed.
• The developed systems are demonstrated to be effective in real-time luminance control.
摘要
•Luminance control is formalized as a constrained search problem.•Both power consumption minimization and sufficient illuminance are considered.•A distributive PSO-based algorithm is developed to do an effective search.•Parallel implementations in GPU and Hadoop MapReduce are developed.•The developed systems are demonstrated to be effective in real-time luminance control.
论文关键词：Energy conservation,Particle swarm optimization,Parallel algorithm,GPU,CUDA,MapReduce,Hadoop
论文评审过程：Received 4 February 2016, Revised 31 October 2017, Accepted 1 November 2017, Available online 8 November 2017, Version of Record 5 January 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.002
