Energy Efficiency Based on High Performance Particle Swarm Optimization: A Case

doi:10.1007/s11235-011-9641-y

CNU IR > College of Sustainable Environment and Recreation > Dept. of Applied Geoinformatics > Periodical Articles > Item 310902800/26976

Please use this identifier to cite or link to this item: https://ir.cnu.edu.tw/handle/310902800/26976

Title:	Energy Efficiency Based on High Performance Particle Swarm Optimization: A Case
Authors:	Liao, Ming-Yi Tsai, Chun-Wei Yang, Chu-Sing Chiang, Ming-Chao Lai, Chin-Feng
Contributors:	應用空間資訊系
Keywords:	Clustering algorithm Green computing Particle swarm optimization
Date:	2011-01
Issue Date:	2013-10-14 14:57:47 (UTC+8)
Publisher:	Springer
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.
Relation:	Telecommunication Systems , 52(2), pp.1293-1304
Appears in Collections:	[Dept. of Applied Geoinformatics] Periodical Articles

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