CN105763367A - Data center energy consumption management method based on virtualization - Google Patents
Data center energy consumption management method based on virtualization Download PDFInfo
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- CN105763367A CN105763367A CN201610074360.5A CN201610074360A CN105763367A CN 105763367 A CN105763367 A CN 105763367A CN 201610074360 A CN201610074360 A CN 201610074360A CN 105763367 A CN105763367 A CN 105763367A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
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Abstract
The present invention relates to the energy consumption management technology. The objective of the invention is to solve the problems that a cloud calculation base device rarely provides parts and service for supporting energy perception and cannot minimize the energy consumption while satisfying the service quality requirement. The method comprises the following steps: building the resource energy consumption module of the data center, and constructing the association between the utilization rate of a specific type resource and the energy consumption of the data center; measuring the resource utilization rate when a virtual machine operates, and performing online energy consumption contour analysis through a hardware performance counter provided by a typical virtual machine; estimating the energy consumption condition of the virtual machine, inputting the resource utilization rate, and indirectly deducting the energy consumption of the virtual machine through the calculation of the resource energy consumption model; and constructing an energy consumption mechanism and an energy consumption management algorithm to realize the resource energy consumption management of the data center. The data center energy consumption management method based on virtualization is suitable for energy consumption management of a cloud platform data center based on virtualization.
Description
Technical field
The present invention relates to power management technique, particularly to a kind of energy consumption management method based on virtualized cloud platform center.
Background technology
In recent years, the high energy consumption of data center is increasingly becoming distinct issues, especially with the arrival of cloud computing, more calculates in resource and storage resource set beyond the clouds, brings bigger challenge to the high-efficiency management of energy consumption.The high energy consumption problem of data center not only causes the waste of electric energy, the instability that system is run, and also environment is had undesirable effect simultaneously.
High energy consumption problem is mainly derived from two aspects: one be processor level energy consumption, another be the energy consumption of data center's level.Along with the continuous progress of processor manufacturing process, processor, while obtaining the high speed of service, brings high energy consumption problem.Although the optimisation technique on some hardware improves the service efficiency of energy to a certain extent, but the energy consumption of processor is used the impact of pattern, the problem that too high load and too low utilization rate all can cause high energy consumption electric energy poor efficiency by application program.Central layer time in the data, continuous along with data center's scale increases, and data center occurs in that more difficult situation: one side, due to constantly increasing of physical server quantity and constantly strengthening of disposal ability, brings more energy expenditure；The utilization rate that each server is too low on the other hand causes again huge waste of energy.
Summary of the invention
The invention aims to solve in prior art, cloud computing infrastructure is seldom provided that the parts supporting Energy-aware and service, it is impossible to the problem minimizing energy consumption expense while meeting QoS requirement.
For reaching above-mentioned purpose, the present invention provides a kind of energy consumption management method based on virtualized data center, it is characterised in that comprise the steps:
Set up the resource energy consumption model of data center, build the utilization rate of particular type resource and associating of data center systems energy consumption；
Measuring resource utilization when virtual machine runs, the hardware performance counter provided by typical virtual machine platform carries out online energy consumption edge analysis；
Assessment energy consumption of virtual machine situation, inputs resource utilization, by the calculating of described resource energy consumption model, indirectly infers the energy consumption of virtual machine；
Build managing power consumption mechanism and managing power consumption algorithm realizes the resource managing power consumption to data center.
Specifically, described resource energy consumption model is divided into static energy consumption model and dynamic energy consumption model, described static energy consumption model includes CPU energy consumption model, internal memory energy consumption model, hard disk energy consumption model and overall energy consumption model, and described dynamic energy consumption model includes Server Consolidation energy consumption model and migrates energy consumption model online.
Specifically, described energy consumption edge analysis includes the energy consumption analysis of physical node and the energy consumption analysis of virtual machine.
Specifically, described managing power consumption mechanism includes virtualization layer managing power consumption mechanism and cloud platform layer managing power consumption mechanism, described virtualization layer managing power consumption mechanism includes virtual machine manager layer managing power consumption and the managing power consumption of virtual machine internal layer, and described cloud platform layer managing power consumption mechanism includes managing power consumption and the managing power consumption middleware managing power consumption of virtual managing power consumption layer.
Specifically, described managing power consumption algorithm includes static deployment set of algorithms Dynamical Deployment algorithm, described static Deployment Algorithm includes the Deployment Algorithm collection based on dependency and clusters Deployment Algorithm based on peak value, and described Dynamical Deployment algorithm includes the minimum Deployment Algorithm of energy, based on history perception Deployment Algorithm collection migration overhead perception Deployment Algorithm.
Further, described managing power consumption algorithm also includes effective bunch of topological algorithms and peak use rate Deployment Algorithm.
Further, described managing power consumption algorithm also includes that single threshold migrates Deployment Algorithm, minimizes migration Deployment Algorithm, most high growth potentiality Deployment Algorithm collection randomly chooses Deployment Algorithm.
The invention has the beneficial effects as follows: adopt technology and the achievement of the present invention, it is possible to build the cloud computing solution of a kind of green, while energy efficient, namely reduce management operation overhead.The final goal of green cloud computing is efficiently to process and minimize energy expenditure while use cloud infrastructure.This invention can be widely applied to the fields such as IDC data center, cloud computing center, big market demand center, has a extensive future.
Accompanying drawing explanation
Fig. 1 is the structural representation of the resource energy consumption model of embodiment；
Fig. 2 is the structural representation of the managing power consumption mechanism of embodiment；
Fig. 3 is the managing power consumption algorithm structure schematic diagram of embodiment.
Detailed description of the invention
Below in conjunction with drawings and Examples, technical scheme is described in further detail.
The present invention is directed to prior art medium cloud computing basic facility and be seldom provided that the parts supporting Energy-aware and service, the problem minimizing energy consumption expense while cannot meeting QoS requirement, a kind of energy consumption management method based on virtualized data center is provided, comprises the steps:
Set up the resource energy consumption model of data center, build the utilization rate of particular type resource and associating of data center systems energy consumption；
Measuring resource utilization when virtual machine runs, the hardware performance counter provided by typical virtual machine platform carries out online energy consumption edge analysis；
Assessment energy consumption of virtual machine situation, inputs resource utilization, by the calculating of described resource energy consumption model, indirectly infers the energy consumption of virtual machine；
Build managing power consumption mechanism and managing power consumption algorithm realizes the resource managing power consumption to data center.
Embodiment
Hereinafter the technology of the present invention is conceived and technical scheme is described in further detail.
Intel Virtualization Technology brings, to the managing power consumption of cloud computation data center, the thinking that a lot of solution is new.Generally, an efficient managing power consumption solution needs to consider the factor of following 3 aspects:
1, abundant energy consumption monitoring and measuring method, provide monitoring initial data timely and accurately；
2, the modeling of accurate energy consumption and analysis, it was predicted that the Expenditure Levels of energy, indicates trend and cause effect relation；
3, power-saving mechanism and optimized algorithm, is used for reducing energy consumption, meets the requirements such as performance, service quality (QoS) or service-level agreement (SLA) simultaneously.
This invention address that the technical scheme that the problems referred to above are intended adopting includes following components:
1, based on the energy consumption monitoring of virtualized data center and measurement: the expense of energy consumption measurement and accuracy are the bases formulating efficient energy consumption management strategy；
2, energy consumption of virtual machine method for profile analysis: at present, the online energy consumption monitoring of great majority is all based on physical node.It provides only the energy expenditure of whole system, without the energy consumption providing single virtual machine.The precision of energy consumption modeling, directly reflects the accuracy of energy consumption of virtual machine data, and the effect of energy saving optimizing is extremely important；
3, based on the energy consumption analysis of virtualized data center and modeling: provide the energy consumption assessment model based on asystem function unit and the energy consumption forecast model based on hardware performance counter；
4, realization mechanism is managed based on virtualized consumption of data center: managing power consumption mechanism is divided into the administrative mechanism of virtualization layer and the administrative mechanism of cloud platform layer；
5, based on virtualized consumption of data center management algorithm: managing power consumption algorithm is divided into energy-efficient deployment algorithm, energy-conservation integration algorithm, energy-conservation migration algorithm etc. by application scenarios.
The technology of above-mentioned 5 aspects and content relation are close, are mutually linked, together constitute based on virtualized consumption of data center rwan management solution RWAN.Their relation is: energy consumption measurement obtains the initial data of resource service condition, passes to energy consumption model；Energy consumption model is according to the energy consumption service condition calculating virtual machine；Based on these data, it is possible to achieve complicated managing power consumption mechanism and management algorithm.
Below in conjunction with Fig. 1, Fig. 2 and Fig. 3, make technical scheme to dissect further.
In the present invention, the basic ideas that energy consumption of virtual machine is measured:
1, initially set up an energy consumption model, the utilization rate (such as CPU) of particular type resource and total system energy consumption are set up contact.For the sake of simplicity, it is left out being in the energy consumption of other resource type of relatively low utilization rate level；
2, use lightweight monitoring tools to measure the utilization rate of different resource when each virtual machine runs, such as can carry out online edge analysis by the hardware performance counter that typical virtual machine platform provides；
3, assessment energy consumption of virtual machine situation, inputs resource utilization, by the calculating of resource energy consumption model, indirectly infers the energy consumption of virtual machine.
In the present invention, energy consumption model is divided into two big classes: the energy consumption assessment model based on asystem function unit and the energy consumption forecast model based on hardware performance counter.Fig. 1 gives the energy consumption modeling method for virtualization cloud computing platform, is divided into static energy consumption modeling and dynamic energy consumption to model two classes.Static energy consumption modeling Simulation is the energy consumption of single virtual machine system feature；Dynamic energy consumption modeling is the energy consumption modeling to virtualization dynamic application scene, migrates energy consumption modeling including the modeling of Server Consolidation energy consumption with online.
In the present invention, power-saving technology is divided into static power-saving technology and dynamic energy-saving technology.Static power-saving technology method is just Energy Consumption Factors to be taken into account when initial system and part design, and this method includes circuit layer power-saving technology etc..Dynamic energy-saving technical method is the change according to load, administration of energy conservation is carried out adaptively from the angle of resource management, this method needs to optimize server layer and the energy expenditure of cluster layer by the management software of intelligence, it is more efficient way that static and dynamic energy-saving technology are bound together, and is also virtualize the energy-conservation realization mechanism that cloud computing platform is feasible.
Difference according to management level, the managing power consumption mechanism of virtualization cloud computing platform is divided into two classes: the managing power consumption mechanism of virtualization layer and the managing power consumption mechanism of cloud platform layer, Fig. 2 describes and classifies based on virtualized consumption of data center administrative mechanism.
Managing power consumption algorithm classification
The wide range that managing power consumption algorithm relates to, including random algorithm to the algorithm etc. based on study.
1, divide by main Passive Mode
Dividing by main Passive Mode, managing power consumption algorithm can be divided into actively power-economizing method and passive power-economizing method.Actively energy-conservation is by methods such as historical data study, following energy consumption being predicted, and carries out the Resource Management Algorithm of power-aware previously according to information of forecasting.Passive Energy Saving Algorithm is by means such as monitor in real time, according to the resource service condition before study, carries out corresponding resource adjustment, reaches energy-conservation purpose.
2, algorithmically precision is divided
Algorithmically precision is divided, and managing power consumption algorithm has based on cybernatic exact algorithm with based on didactic algorithm.
Certain defect is there is, as when program adjusts time, it is necessary to again based on the study of simulation, this is unpractical for Practical Calculation based on cybernatic exact algorithm model；It addition, this model there is also certain complexity, it is mainly reflected on the execution time.
It is not required to dispose in program the study of row simulation of advancing based on didactic managing power consumption algorithm, higher performance can be obtained in real large-scale cloud computing system.At present, the most self adaptation managing power consumption algorithms based on virtualized data center all adopt based on didactic managing power consumption algorithm.
3, algorithmically granularity is divided
Granularity algorithmically is divided, and managing power consumption algorithm can be divided into Coarse grain algorithm, fine granularity algorithm and fineness degree hybrid algorithm.
Fine-grained managing power consumption algorithm is the managing power consumption algorithm at unit or hierarchy of components.The groundwork unit of the managing power consumption algorithm of coarseness is larger, and ordinary circumstance is exactly as a basic management or monitoring unit using virtual machine.
The method of fine-grained method and coarseness is joined together use, it is simply that the algorithm of thickness granularity mixing.Mixing by a local and global policies, in local aspect, system utilizes the managing power consumption strategy of client operating system；Global administration's device then obtains the information that the Current resource from local management device distributes, and applies this strategy and decide whether to adopt new deploying virtual machine scheme.
4, divide by resource category
Dividing by the kind of resource, managing power consumption algorithm is divided into calculating resource power-economizing method, storage resource power-economizing method and Internet resources power-economizing method.
5, divide by application scenarios
Intel Virtualization Technology is applied in cloud computation data center as the base layer support technology of a kind of key, the virtualization applications scene of cloud computation data center is carried out energy consumption research extremely important.Dividing according to application scenarios, managing power consumption algorithm is divided into 3 big classes: energy-efficient deployment algorithm, energy-conservation integration algorithm and energy-conservation migration algorithm.Energy-efficient deployment algorithm is divided into again static Deployment Algorithm and Dynamical Deployment algorithm.Static Deployment Algorithm includes the Deployment Algorithm based on dependency and the Deployment Algorithm based on peak value cluster；Dynamical Deployment algorithm includes the Deployment Algorithm of energy consumption minimized Deployment Algorithm, history perception Deployment Algorithm and migration overhead perception；Energy-conservation integration algorithm is divided into ECTC (effective bunch of topology) Deployment Algorithm and MaxUtil (peak use rate) Deployment Algorithm；Energy-conservation migration algorithm is subdivided into: single threshold migration algorithm, minimize migration algorithm, most high growth potentiality algorithm and stochastic selection algorithm.
The present invention is based on above-mentioned technology and solution, and the mode of application software carries the energy consumption management method based on virtualized data center.This software includes server software and client mobile terminal software two parts.Server software realizes and resident service device internal memory based on virtualized consumption of data center management method based on four big core technique constructions such as energy consumption measurement, energy consumption modeling, managing power consumption, managing power consumption algorithms, and client software realizes remotely monitoring, server software configuration, software upgrading etc..By autonomic nucleus core module functions such as software iterative manner constantly perfect, optimization energy consumption measurement, energy consumption modeling, managing power consumption, managing power consumption algorithms.
Claims (7)
1. the energy consumption management method based on virtualized data center, it is characterised in that comprise the steps:
Set up the resource energy consumption model of data center, build the utilization rate of particular type resource and associating of data center systems energy consumption；
Measuring resource utilization when virtual machine runs, the hardware performance counter provided by typical virtual machine platform carries out online energy consumption edge analysis；
Assessment energy consumption of virtual machine situation, inputs resource utilization, by the calculating of described resource energy consumption model, indirectly infers the energy consumption of virtual machine；
Build managing power consumption mechanism and managing power consumption algorithm realizes the resource managing power consumption to data center.
2. a kind of energy consumption management method based on virtualized data center as claimed in claim 1, it is characterized in that, described resource energy consumption model is divided into static energy consumption model and dynamic energy consumption model, described static energy consumption model includes CPU energy consumption model, internal memory energy consumption model, hard disk energy consumption model and overall energy consumption model, and described dynamic energy consumption model includes Server Consolidation energy consumption model and migrates energy consumption model online.
3. a kind of energy consumption management method based on virtualized data center as claimed in claim 1, it is characterised in that described energy consumption edge analysis includes the energy consumption analysis of physical node and the energy consumption analysis of virtual machine.
4. a kind of energy consumption management method based on virtualized data center as claimed in claim 1, it is characterized in that, described managing power consumption mechanism includes virtualization layer managing power consumption mechanism and cloud platform layer managing power consumption mechanism, described virtualization layer managing power consumption mechanism includes virtual machine manager layer managing power consumption and the managing power consumption of virtual machine internal layer, and described cloud platform layer managing power consumption mechanism includes managing power consumption and the managing power consumption middleware managing power consumption of virtual managing power consumption layer.
5. a kind of energy consumption management method based on virtualized data center as claimed in claim 1, it is characterized in that, described managing power consumption algorithm includes static deployment set of algorithms Dynamical Deployment algorithm, described static Deployment Algorithm includes the Deployment Algorithm collection based on dependency and clusters Deployment Algorithm based on peak value, and described Dynamical Deployment algorithm includes the minimum Deployment Algorithm of energy, based on history perception Deployment Algorithm collection migration overhead perception Deployment Algorithm.
6. a kind of energy consumption management method based on virtualized data center as claimed in claim 1, it is characterised in that described managing power consumption algorithm also includes effective bunch of topological algorithms and peak use rate Deployment Algorithm.
7. a kind of energy consumption management method based on virtualized data center as claimed in claim 1, it is characterized in that, described managing power consumption algorithm also includes that single threshold migrates Deployment Algorithm, minimizes migration Deployment Algorithm, most high growth potentiality Deployment Algorithm collection randomly chooses Deployment Algorithm.
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| CN107341043A (en) * | 2017-06-28 | 2017-11-10 | 东北大学 | A kind of emulation mode for the consumption of data center for assessing regenerative resource hybrid power supply |
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| CN107911255A (en) * | 2017-12-28 | 2018-04-13 | 李淑芹 | A kind of power grid energy consumption processing unit based on cloud computing system |
| CN110705062A (en) * | 2019-09-20 | 2020-01-17 | 苏州智博汇能电子科技股份有限公司 | Cabinet energy consumption remote statistical metering method based on 5G |
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| CN106886274A (en) * | 2017-01-22 | 2017-06-23 | 青海大学 | The management method and device of a kind of consumption of data center |
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| CN107341043A (en) * | 2017-06-28 | 2017-11-10 | 东北大学 | A kind of emulation mode for the consumption of data center for assessing regenerative resource hybrid power supply |
| CN107656851A (en) * | 2017-09-30 | 2018-02-02 | 华南理工大学 | A kind of Cloud Server energy consumption measuring method and system based on part energy consumption model |
| CN107656851B (en) * | 2017-09-30 | 2021-01-19 | 华南理工大学 | Cloud server energy consumption measuring and calculating method and system based on component energy consumption model |
| CN107911255A (en) * | 2017-12-28 | 2018-04-13 | 李淑芹 | A kind of power grid energy consumption processing unit based on cloud computing system |
| CN111435317A (en) * | 2019-01-14 | 2020-07-21 | 阿里巴巴集团控股有限公司 | Data processing method, computing device and storage medium |
| CN111435317B (en) * | 2019-01-14 | 2023-04-11 | 阿里巴巴集团控股有限公司 | Data processing method, computing device and storage medium |
| CN110705062A (en) * | 2019-09-20 | 2020-01-17 | 苏州智博汇能电子科技股份有限公司 | Cabinet energy consumption remote statistical metering method based on 5G |
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