發(fā)布時間：2018-07-15 11:00

【摘要】：隨著移動互聯(lián)網(wǎng)、物聯(lián)網(wǎng)、云計算的高速發(fā)展,數(shù)據(jù)中心作為信息的重要載體,迎來了一波建設(shè)的浪潮。大規(guī)模、高密度的IT設(shè)備部署,大量的分布式系統(tǒng)的應(yīng)用,供電和制冷的需求不斷增加,所有這些使得機(jī)房的運(yùn)行維護(hù)和管理復(fù)雜、能量消耗巨大。但在機(jī)房能耗分析和控制方面,通信業(yè)普遍存在采集范圍程度不夠、信息孤島化及粗放式管理等問題。能耗分析系統(tǒng)可以針對收集的基站、機(jī)房能耗數(shù)據(jù)進(jìn)行統(tǒng)一存儲分析,為管理者提供決策支持,但是該系統(tǒng)目前僅能對數(shù)據(jù)進(jìn)行簡單的統(tǒng)計分析,遠(yuǎn)沒有開發(fā)出能耗數(shù)據(jù)真正的價值。在這樣的背景下,本課題從分類算法在能耗分析系統(tǒng)中應(yīng)用場景的探索為切入點(diǎn),使用分類算法挖掘能耗數(shù)據(jù)中潛在的價值。課題研究了分類算法在節(jié)能措施業(yè)務(wù)場景、異常能耗數(shù)據(jù)告警場景以及能耗模型場景中的應(yīng)用,豐富并完善了原有的業(yè)務(wù)場景。重點(diǎn)研究了分類算法在節(jié)能措施業(yè)務(wù)場景中的應(yīng)用,設(shè)計并實(shí)現(xiàn)了節(jié)能措施仿真平臺。該平臺由三個子系統(tǒng)組成:并行計算子系統(tǒng),節(jié)能措施實(shí)施子系統(tǒng)和能耗數(shù)據(jù)仿真子系統(tǒng)。并行計算子系統(tǒng)提供計算支持,能耗數(shù)據(jù)仿真子系統(tǒng)提供能耗數(shù)據(jù)支持,節(jié)能措施實(shí)施子系統(tǒng)向用戶推薦節(jié)能措施,并提供節(jié)能措施效果對比功能。當(dāng)機(jī)房出現(xiàn)異常能耗告警時,基于分類算法實(shí)現(xiàn)的節(jié)能措施仿真平臺可以向管理員推薦合適的節(jié)能措施。另一方面,管理員在真正在機(jī)房安裝、配置、實(shí)施某節(jié)能措施前,可以通過節(jié)能措施仿真平臺接近零成本模擬實(shí)施該節(jié)能措施,驗(yàn)證該節(jié)能措施的效果,大幅降低驗(yàn)證節(jié)能措施效果的成本。
[Abstract]:With the rapid development of mobile Internet, Internet of things, cloud computing, data center as an important carrier of information, ushered in a wave of construction wave. Large-scale, high-density IT equipment deployment, a large number of distributed system applications, the increasing demand for power supply and refrigeration, all these make the operation, maintenance and management of the computer room complex, energy consumption is huge. However, in the analysis and control of computer room energy consumption, there are some problems in the communication industry, such as insufficient acquisition scope, isolated information and extensive management, etc. The energy consumption analysis system can be used to store and analyze the energy consumption data of the base station and computer room in a unified way, which can provide decision support for the manager. But at present, the system can only carry out simple statistical analysis of the data. Far from developing the true value of energy consumption data. In this context, this paper uses the classification algorithm to mine the potential value of energy consumption data from the exploration of the application of classification algorithm in the energy consumption analysis system. This paper studies the application of classification algorithm in the business scene of energy saving measures, the alarm scenario of abnormal energy consumption data and the scenario of energy consumption model, which enriches and perfects the original business scenario. The application of classification algorithm in the business scene of energy saving measures is studied, and the simulation platform of energy saving measures is designed and implemented. The platform consists of three subsystems: parallel computing subsystem, energy saving implementation subsystem and energy consumption data simulation subsystem. Parallel computing subsystem provides computing support, energy consumption data simulation subsystem provides energy consumption data support, energy saving measures implementation subsystem recommends energy saving measures to users, and provides the function of comparing the effect of energy saving measures. When the abnormal energy consumption alarm appears in the computer room, the simulation platform based on the classification algorithm can recommend the appropriate energy-saving measures to the administrator. On the other hand, before the administrator really installs, configures, and implements some energy-saving measures in the computer room, he can simulate the energy-saving measures through the simulation platform of energy-saving measures at close to zero cost, and verify the effect of the energy-saving measures. Significantly reduce the cost of verifying the effectiveness of energy conservation measures.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP311.52

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