CN102759984A - Power supply and performance management system for virtualization server cluster - Google Patents

Power supply and performance management system for virtualization server cluster Download PDF

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CN102759984A
CN102759984A CN2012101952084A CN201210195208A CN102759984A CN 102759984 A CN102759984 A CN 102759984A CN 2012101952084 A CN2012101952084 A CN 2012101952084A CN 201210195208 A CN201210195208 A CN 201210195208A CN 102759984 A CN102759984 A CN 102759984A
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virtual machine
resource
energy consumption
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武裕斌
高永强
戚正伟
管海兵
宦飞
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Shanghai Jiaotong University
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The invention provides a power supply and performance management system for a virtualization server cluster. The power supply and performance management system comprises an acquiring module, a performance optimizing module and an energy consumption optimizing module, wherein the acquiring module is used for acquiring operation data of the virtualization server cluster; the performance optimizing module is used for carrying out energy efficiency modeling on performance and resource utilizing conditions of a virtual machine according to an original energy source and resource utilization relationship and outputting resource configuration parameter of the virtual machine; and the energy consumption optimizing module is used for receiving the resource configuration parameters of the virtual machine, which are from the performance optimizing module, establishing an energy consumption model according to the resource configuration parameters of the virtual machine and carrying out scheduling and resource re-allocation on the virtual machine according to limiting conditions of a resource threshold and the scheduling limiting condition of the virtual machine. According to the power supply and performance management system disclosed by the invention, due to the combination of a control theory with a linear programming technology, the considerable energy-saving effect can be achieved while application performances are ensured. Particularly, the effect of saving energy by 43 percent can be achieved by integrating a performance controller with an energy optimizer.

Description

The power supply of virtualized server cluster and performance management system
Technical field
The present invention relates to green computing field, especially a kind of based on the data center's performance of Intel Virtualization Technology and the layer management system of energy consumption, particularly, relate to the power supply and the performance management system of virtualized server cluster.
Background technology
Energy consumption problem highlights day by day in recent years, and the restricting relation of data center's overall performance and administration of energy conservation also receives the more concern of multiple enterprises and research institution.At present mainly utilize the technology of following several respects that the data center is dispatched and managed: control technology is used for the optimal control of physical resource operating position and effectively distribution are realized the optimization of entire system performance; Power management technique makes up rational managing power consumption system according to the utilization factor of resource, accurately estimates the electricity consumption situation of server cluster.Utilize these technology, can effectively manage the data center from aspects such as resource utilization, system running state, entire system energy consumptions.In addition, when keeping using isolation, Intel Virtualization Technology has been widely applied to data center, is used for providing more easily using and make resource multiplex facility more.The challenge of a key that is accompanied by Intel Virtualization Technology and comes is to the real-time monitoring of the shared resource of distributing to virtual machine and the management of virtual machine being satisfied the quality of service goals ability with minimum cost.
Open source softwares more of the prior art can provide management function for the virtualized server cluster; OpenNEbula for example, be a be the virtual management tool that the industrial standard of increasing income is provided of data center to different virtual platform (Xen, VMware, KVM).But this management tool only provides some basic resource management functions, the scheduling of virtual machine is not provided the control method of highly effective, and system resource rationally utilized DeGrain; In addition, its managing power consumption to virtual cluster does not provide corresponding measure, and the administration of energy conservation of data central whole is also had much room for improvement.
It is exactly the service level agreement violation through minimize power consumption and application that data center manages one of most important target, the income of coming the maximize data center.But at present under the condition of sharing infrastructure, because the dynamic of system is difficult to all reach both ways simultaneously optimization aim.One side is wherein only paid attention in the work in early stage basically, or is the off-line model that only is applicable to the application-specific load.
Summary of the invention
The present invention is directed to the deficiency that prior art exists; The stratification management system of one cover Virtual Server Cluster performance and energy consumption is proposed; Utilize the management system of linear programming technical design resource and energy consumption; Solve the problem that data center's performance and energy consumption are not taken into account, when minimizing the virtual data center energy consumption, guaranteed the performance requirement of application level service.
The present invention realizes through following technical scheme:
The present invention provides a kind of power supply and performance management system of virtualized server cluster, comprises like lower module:
Acquisition module, it is used to gather the service data of virtualized server cluster;
The performance optimization module, it is used to utilize said service data, according to the original energy consumption and the relation of resource utilization, the performance and the utilization of resources situation of virtual machine is carried out the efficiency modeling, the resource distribution parameter of output virtual machine;
The energy optimization module; It is used to receive the resource distribution parameter from the said virtual machine of said performance optimization module; And set up energy consumption model according to the resource distribution parameter of said virtual machine; According to the restrictive condition and the scheduling virtual machine restrictive condition of resource threshold, virtual machine is dispatched the reallocation with resource.
The utilization factor of described service data: CPU, memory usage, the size of effective CPU and memory source, power consumption.
The concrete operations mode of described data acquisition: the basic function that utilizes the Intel Virtualization Technology monitor supervision platform to provide; CPU, the internal memory of gathering virtualized server utilize situation, and import the performance optimal module into as input, give the resource of virtual machine through performance optimized Algorithm Control Allocation; With the output of performance optimization module input as the energy optimization module; Through the energy optimization algorithm, further virtual machine is dispatched the reallocation with resource, to reduce the energy consumption of group system.
Described performance optimization resource controlling schemes: according to the original historical data of utilizing situation and performance of resource, make up the resource model prediction device, adopt second order autoregressive moving average control mode, current resource requirement and performance are reasonably estimated; Through adding optimization control scheme, confirm concrete resource allocation scheduling scheme and optimize properties data; Interface through calling Xen is dispatched, and the situation of utilizing of related resource is passed to the energy optimization module further to confirm the allocative decision of virtual machine.
Described prediction device system schema:
Second order autoregressive moving average control mode:
Q t(k)=a 1，t(k)Q t(k-1)+a 2,t(k)Q t(k-2)
+b 0，t(k)Ua t(k)+b 1,t(k)Ua t(k-1)+e t(k)
Wherein: t representes node; Q t(k) be in the k actual value of performance constantly; Q t(k-n) be at the measured value of k-n moment performance, confirm by system history data; Ua t(k) be k utilization of resources data constantly; Ua t(k-1) be k-1 utilization of resources data constantly; e t(k) be the error of prediction device, by the error decision of measured value and discreet value; a 1, t(k), a 2, t(k), b 0, t(k) and b 1, t(k) be systematic parameter.
Described performance optimization control mode:
The utility function that adopts:
Δ t = ( Q t ( k ) - Q t ref ) 2 + q ( U r t ( k ) - U a t ( k - 1 ) ) 2
= Δ pc + q Δ cc
Wherein: Q t(k) be in the k actual value of performance constantly;
Figure BDA00001760464500033
It is the performance objective value that the user sets; Ur t(k) be the value of the virtual machine demand resource of process controller optimization; Q is the stable factor of controller, between [0,1], changes.
Real resource distribute data Ua according to each virtual machine of gathering t(k) and Ua tAnd performance data Q (k-1), t(k), Q t(k-1), adopt minimum recurrence square law (RLS) estimation intermediate parameters a 1, t(k), a 2, t(k), b 0, t(k) and b 1, t(k) value is established the model between performance and the resources allocation.
Utilize performance desired value Q Ref, calculate the utility function Δ tUr when obtaining minimum value t(k), also promptly utilize before constantly the value of Resources allocation estimate with the performance objective value and need distribute to virtual machine optimum resource Ur t(k).
Described energy optimization scheme:, it is modified into the energy consumption model of whole virtual cluster, through adding two groups of numeric parameter { x with reference to the energy consumption of separate unit physical server linear model with cpu busy percentage Ij, y i, Real-Time Scheduling is distributed in virtual machine on the physical server to reach minimizing of the whole energy consumption of server cluster.
Original energy consumption reference model:
Figure BDA00001760464500034
Wherein, P representes the energy consumption of physical server, and unit is Watt; I representes the label of physical server; U CPUThe utilization factor of expression physical server CPU is represented with percentage point; A representes the proportionate relationship of energy consumption with cpu busy percentage; B representes the no-load power consumption of physical server.Under the normal condition, there is certain power consumption in physical server when idle (zero load, CPU is utilized as 0 situation), represent with b; This reference model hypothesis physical server is when no-load running, and we just turn off it, so power consumption values is made as 0 in other cases.
Improved linear programming model: Σ i = 1 m P i = Σ i = 1 m [ a × Σ j n ( x Ij · R Pj ) + b × y i ]
Wherein, m representes physical server quantity; N representes to distribute to the quantity of i virtual machine; J representes the label of virtual machine; R pThe cpu busy percentage of expression virtual machine is represented with number percent; x IjRepresent whether j virtual machine is positioned on the i platform physical server, 1 expression is that 0 expression is not; y iRepresent whether i platform physical server is in running status, 1 expression is that 0 expression is not.
In order to reach the energy consumption minimized operating position of cluster, utilize the integral linear programming technology to provide corresponding restricted version:
The minimum value restrictive condition of
Figure BDA00001760464500042
:
Σ i = 1 m x ij = 1 , ∀ j ∈ J
Σ j = 1 n R p j · x ij ≤ C p i · y i , ∀ i ∈ I
Σ j = 1 n R m j · x ij ≤ C m i y i , ∀ i ∈ I
y i , x Ij ∈ { 0,1 } , ∀ j ∈ J And ∀ i ∈ I
Wherein, C pThe limits value that expression physical machine CPU utilizes; C mThe limits value that expression physical machine internal memory utilizes; R mThe utilization factor of expression virutal machine memory; All the other symbols are with reference to above-mentioned energy consumption model.
Utilize instrument to solve x Ij, y iDraw the virtual machine allocation plan of reasonably optimizing, call the xen interface and carry out scheduling virtual machine efficiently, further reach the effect of energy saving optimizing.
Characteristic of the present invention and innovation are for combining control theory and linear programming technological: at node (server) grade; Performance controller is employed in line model prediction device, multiple-input, multiple-output optimal controller and moderator, keeps the performance of expecting through reconfiguring of dynamic cpu resource; In data center's level, use the linear programming technology to come the design energy optimizer, between the node of data center, dynamically adjust and redistribute virtual machine and come optimizing energy cost.
Experimental result shows that the framework that invention proposes can bring considerable energy-saving effect on the basis that guarantees application performance.Especially, performance controller and energy-optimised device are integrated can produce energy-conservation 43% effect.
Description of drawings
By reading the detailed description of non-limiting example being done with reference to the following drawings, it is more obvious that other features, objects and advantages of the present invention will become:
Fig. 1 is power supply of the present invention and energy consumption holistic management frame diagram.
Embodiment
The energy consumption problem that the present invention is directed to virtual data center has proposed a kind of performance and managing power consumption framework of virtualized server cluster, and concrete realization comprises performance optimization module and energy optimization module two parts.
In one embodiment, cooperate through following step between said acquisition module, performance optimization module and the energy optimization module:
Step 1; Use virtual management instrument Xen management and move a virtualized server cluster; Resource data and performance data that the interface that utilization provides is gathered virtual machine through said acquisition module, and related data passed to resource model prediction device and the energy consumption model in the said energy optimization module in the said performance optimization module.
Step 2, resource model prediction device analyze and make up the online Prediction model of performance and utilization of resources situation to current data and historical data; The performance optimization module is carried out the efficiency modeling to performance and utilization of resources situation, utilizes prediction model parameter and performance resource historical data to obtain next resource allocation conditions of virtual machine constantly, keeps the stability of performance simultaneously.
Step 3; The energy optimization module utilizes utilization of resources data that energy consumption system is analyzed and set up in the distribution of data center virtual machine; Obtain the reasonable distribution scheme of the virtual machine of a least energy consumption according to the restrictive condition of resource threshold and scheduling virtual machine restrictive condition; This allocative decision is distributed virtual machine by the scheduler of Xen and is optimized scheduling, reaches energy consumption minimized target.
Through above-mentioned steps, adopt 20 Dell VOSTRO servers, processor is Intel Core TM2, the 3G internal memory, the 250GB hard disk, every physical machine is used Xen (2.6.16.60-021) tools build server cluster, and virtual machine is installed OpenSuSE10.2 and is run application.Use the said system of this patent, can be in the metastable while of guaranteed performance, the energy consumption that reduces data center reaches 43%.
More than specific embodiment of the present invention is described.It will be appreciated that the present invention is not limited to above-mentioned specific implementations, those skilled in the art can make various distortion or modification within the scope of the claims, and this does not influence flesh and blood of the present invention.

Claims (6)

1. the power supply of a virtualized server cluster and performance management system is characterized in that, comprise like lower module:
Acquisition module, it is used to gather the service data of virtualized server cluster;
The performance optimization module, it is used to utilize said service data, according to the original energy consumption and the relation of resource utilization, the performance and the utilization of resources situation of virtual machine is carried out the efficiency modeling, the resource distribution parameter of output virtual machine;
The energy optimization module; It is used to receive the resource distribution parameter from the said virtual machine of said performance optimization module; And set up energy consumption model according to the resource distribution parameter of said virtual machine; According to the restrictive condition and the scheduling virtual machine restrictive condition of resource threshold, virtual machine is dispatched the reallocation with resource.
2. the power supply of virtualized server cluster according to claim 1 and performance management system is characterized in that, the data of said operation comprise following any or appoint a plurality of data:
The utilization factor of CPU;
Memory usage;
The size of effective CPU and memory source;
Power consumption.
3. the power supply of virtualized server cluster according to claim 1 and performance management system is characterized in that, said performance optimization module, comprise particularly following any or appoint a plurality of characteristics:
According to the original historical data of utilizing situation and performance of resource, make up the resource model prediction device, adopt second order autoregressive moving average control mode, current resource requirement and performance are reasonably estimated;
Adopt the optimal control mode, confirm concrete resource allocation scheduling scheme and optimize properties data;
Interface through calling Xen is dispatched, and the situation of utilizing of related resource is passed to the energy optimization module further to confirm the allocative decision of virtual machine.
4. the power supply of virtualized server cluster according to claim 3 and performance management system is characterized in that, said second order autoregressive moving average control mode is specially:
Q t(k)=a 1，t(k)Q t(k-1)+a 2,t(k)Q t(k-2)
+b 0，t(k)Ua t(k)+b 1,t(k)Ua t(k-1)+e t(k)
Wherein: t representes node; Q t(k) be in the k actual value of performance constantly; Q t(k-n) be at the measured value of k-n moment performance, confirm by system history data; Ua t(k) be k utilization of resources data constantly; Ua t(k-1) be k-1 utilization of resources data constantly; e t(k) be the error of resource model prediction device, by the error decision of measured value and discreet value; a 1, t(k), a 2, t(k), b 0, t(k) and b 1, t(k) be systematic parameter.
5. according to the power supply and the performance management system of claim 3 or 4 described virtualized server clusters, it is characterized in that said optimal control mode is specially:
Adopt utility function:
Δ t = ( Q t ( k ) - Q t ref ) 2 + q ( U r t ( k ) - U a t ( k - 1 ) ) 2
= Δ pc + q Δ cc
Wherein: Q t(k) be in the k actual value of performance constantly;
Figure FDA00001760464400023
It is the performance objective value that the user sets; Ur t(k) be the value of the virtual machine demand resource of process controller optimization; Q is the stable factor of controller, between [0,1], changes; Ua t(k-1) be k-1 utilization of resources data constantly;
Real resource distribute data Ua according to each virtual machine of gathering t(k) and Ua tAnd performance data Q (k-1), t(k), Q t(k-1), adopt minimum recurrence square law estimation intermediate parameters a 1, t(k), a 2, t(k), b 0, t(k) and b 1, t(k) value is established the model between performance and the resources allocation;
Utilize performance desired value Q Ref, calculate the utility function Δ tUr when obtaining minimum value t(k), also promptly utilize before constantly the value of Resources allocation estimate with the performance objective value and need distribute to virtual machine optimum resource Ur t(k).
6. the power supply of virtualized server cluster according to claim 1 and performance management system; It is characterized in that; With reference to the energy consumption of separate unit physical server linear model, it is modified into the energy consumption model of whole virtual cluster, through adding two groups of numeric parameter { x with cpu busy percentage Ij, y i, Real-Time Scheduling is distributed in virtual machine on the physical server to reach minimizing of the whole energy consumption of server cluster, particularly:
Improved linear programming model: Σ i = 1 m P i = Σ i = 1 m [ a × Σ j n ( x Ij · R Pj ) + b × y i ]
Wherein, P representes the energy consumption of physical server; I representes the label of physical server; A representes the proportionate relationship of energy consumption with cpu busy percentage; B representes the no-load power consumption of physical server; M representes physical server quantity; N representes to distribute to the quantity of i virtual machine; J representes the label of virtual machine; R pThe cpu busy percentage of expression virtual machine is represented with number percent; x IjRepresent whether j virtual machine is positioned on the i platform physical server, 1 expression is that 0 expression is not; y iRepresent whether i platform physical server is in running status, 1 expression is that 0 expression is not.
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