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Energy efficiency based on high performance particle swarm optimization: a case study

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Abstract

Finding solutions to green manufacturing, green production, and increasing energy efficiency is definitely our responsibility to resist changing the vulnerable environment dramatically. Over the past, several practical techniques have been proposed to reduce the greenhouse gas emissions, e.g., increasing energy efficiency, reducing power usage, using sustainable energy, and recycling. This paper first gives a brief review of green computing and then presents a case study for energy efficiency called energy efficient particle swarm optimization (EEPSO). The proposed algorithm integrates particle swarm optimization and triangle inequality for improving energy efficiency of computers, by using the clustering results to adjust the CPU frequency of network management system. Simulation results show that not only can the proposed algorithm significantly reduce the computation time, but it can also be extended to enhance the performance of network traffic control system to further reduce the power they consume.

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Authors and Affiliations

  1. Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, ROC

    Ming-Yi Liao & Chu-Sing Yang

  2. Department of Applied Geoinformatics, Chia Nan University of Pharmacy & Science, Tainan, Taiwan, ROC

    Chun-Wei Tsai

  3. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, ROC

    Ming-Chao Chiang

  4. Institute of Computer Science & Information Engineering, National Ilan University, I-Lan, Taiwan, ROC

    Chin-Feng Lai

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  1. Ming-Yi Liao
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Correspondence to Chin-Feng Lai.

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Liao, MY., Tsai, CW., Yang, CS. et al. Energy efficiency based on high performance particle swarm optimization: a case study. Telecommun Syst 52, 1293–1304 (2013). https://doi.org/10.1007/s11235-011-9641-y

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