The poor energy proportionality of server is seen as the principal source for low energy efficiency of modern data centers. We find that different resource configurations of an application lead to similar performance,...The poor energy proportionality of server is seen as the principal source for low energy efficiency of modern data centers. We find that different resource configurations of an application lead to similar performance, but have distinct energy consumption. We call this phenomenon as ＂performance-equivalent resource configurations （PERC）＂, and its performance range is called equivalent region （ER）. Based on PERC, one basic idea for improving energy efficiency is to select the most efficient configuration from PERC for each application. However, it cannot support every application to obtain optimal solution when thousands of applications are run simultaneously on resource-bounded servers. Here we propose a heuristic scheme, CPicker, based on genetic programming to improve energy efficiency of servers. To speed up convergence, CPicker initializes a high quality population by first choosing configurations from regions that have high energy variation. Experiments show that CPicker obtains above 17% energy efficiency improvement compared with the greedy approach, and less than 4% efficiency loss compared with the oracle case.展开更多
Cairo is characterized by high temperature compared to its surrounding areas,especially during the summer time.This effect is strengthened by the widespread use of sealed surfaces and the lack of vegetation.Therefore,...Cairo is characterized by high temperature compared to its surrounding areas,especially during the summer time.This effect is strengthened by the widespread use of sealed surfaces and the lack of vegetation.Therefore,the consumption of electricity in indoor spaces for cooling purposes is a critical problem especially in the summer time.The use of air conditioners has increased during the last 10 years enormously.Because of this,electricity bills increased in a huge way,which represents a burden on the citizens.Therefore,this study aims to find unconventional solutions for the reduction of energy through mitigating urban heat island(UHI)and enhancing thermal performance in Cairo.This paper studies various area cover factions of trees in an urban environment,which can be used to mitigate UHI,improve thermal performance in outdoor spaces and reduce energy consumption in high dense built up areas in Cairo.A small area of 250 m×250 m from downtown Cairo was simulated as a case study using ENVImet V.4.3.2.The comparison between reference scenario and suggested scenarios,which are 30%trees,50%trees and 30%trees+70%grass,were conducted on a summer day in Cairo.The outputs were used to estimate the amount of energy in every scenario using DesignBuilder model.The results show that the scenario with 50%trees led to the best human thermal comfort(3 K cooler).Although for the demand of energy in the buildings,the street orientation as well as the aspect ratio(H/W)play an important role and should be considered.展开更多
基金This work is supported by the National Natural Science Foundation of China under Grant Nos. 61572470, 61532017, 61522406, 61432017, 61376043, 61504153, and 61521092, and in part by Youth Innovation Promotion Association, Chinese Academy of Sciences （CAS）, under Grant No. Y404441000.
文摘The poor energy proportionality of server is seen as the principal source for low energy efficiency of modern data centers. We find that different resource configurations of an application lead to similar performance, but have distinct energy consumption. We call this phenomenon as ＂performance-equivalent resource configurations （PERC）＂, and its performance range is called equivalent region （ER）. Based on PERC, one basic idea for improving energy efficiency is to select the most efficient configuration from PERC for each application. However, it cannot support every application to obtain optimal solution when thousands of applications are run simultaneously on resource-bounded servers. Here we propose a heuristic scheme, CPicker, based on genetic programming to improve energy efficiency of servers. To speed up convergence, CPicker initializes a high quality population by first choosing configurations from regions that have high energy variation. Experiments show that CPicker obtains above 17% energy efficiency improvement compared with the greedy approach, and less than 4% efficiency loss compared with the oracle case.
文摘Cairo is characterized by high temperature compared to its surrounding areas,especially during the summer time.This effect is strengthened by the widespread use of sealed surfaces and the lack of vegetation.Therefore,the consumption of electricity in indoor spaces for cooling purposes is a critical problem especially in the summer time.The use of air conditioners has increased during the last 10 years enormously.Because of this,electricity bills increased in a huge way,which represents a burden on the citizens.Therefore,this study aims to find unconventional solutions for the reduction of energy through mitigating urban heat island(UHI)and enhancing thermal performance in Cairo.This paper studies various area cover factions of trees in an urban environment,which can be used to mitigate UHI,improve thermal performance in outdoor spaces and reduce energy consumption in high dense built up areas in Cairo.A small area of 250 m×250 m from downtown Cairo was simulated as a case study using ENVImet V.4.3.2.The comparison between reference scenario and suggested scenarios,which are 30%trees,50%trees and 30%trees+70%grass,were conducted on a summer day in Cairo.The outputs were used to estimate the amount of energy in every scenario using DesignBuilder model.The results show that the scenario with 50%trees led to the best human thermal comfort(3 K cooler).Although for the demand of energy in the buildings,the street orientation as well as the aspect ratio(H/W)play an important role and should be considered.
