CN105302650B - A kind of more resource fairness distribution methods of dynamic towards under cloud computing environment - Google Patents
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Abstract
The invention discloses a kind of more resource fairness distribution methods of dynamic towards under cloud computing environment, the method of the present invention is based on user resources demand and users to share stock number, ensure the fairness of resource allocation by building linear programming model, and apply quick polynomial time complexity algorithm, i.e., dichotomy finds the corresponding v of a user ττ, solve optimal distributing schemeTo improve the algorithm operational efficiency problem for solving optimal distributing scheme；The present invention can accurately and truly reflect the actual conditions of resource allocation in cloud computing shared platform, solve the fairness and efficiency of the more resource allocations of multi-user under dynamic case, improve the long problem of existing resource allocation algorithm run time.
Description
Technical field
The present invention relates to field of cloud computer technology, are provided more particularly, to a kind of dynamic in cloud computing shared platform more
Source fair allocat method.
Background technology
Cloud computing shared platform is by integrating a variety of computing resources, unified management and scheduling of the realization to resource,
Various services are provided for applications.The resource dispatching strategy of cloud shared platform is according to the task resource need of each virtual machine node
It asks, reasonable distribution is carried out to resource so that virtual machine node can have enough resources to complete calculating task and ensure user
Between resource fairness distribution.Therefore how justice is carried out to resource in the case where meeting user task resource requirement effectively to distribute,
To ensure the fairness of resource allocation and improve allocation efficiency of resource to be that cloud computing shared platform needs the key solved
Problem.
Currently, on the fairness problem for solving resource allocation, main research work concentrates on following two aspects：
The fairness problem of single resource and more resource allocations.In terms of single resource allocation justice, it is concentrated mainly on to single resource
(such as CPU, link bandwidth) seeks in maximization allocation strategy (Max-min) research of minimum resource requirements, ensures most use
The resource requirement at family is met, and realizes fairness distribution.In terms of more resource allocation justices, Ghodsi et al. is earliest systematically
Study more resource fairness assignment problems in cloud computing system, it is proposed that more resource DRF (the Dominant Resource of multi-user
Fairness) algorithm solves in a variety of different resources and deposits how to ensure fairness in distribution sex chromosome mosaicism, shows many
Satisfactory fair property, and various more resource fairness distribution mechanisms (GHODSI A, ZAHARIA are derived on this basis
M,HINDMAN B,et al.Dominant resource fairness:Fair allocation of multiple
resource types[A].Proceedings of the 8th USENIX Conference on Networked
Systems Design and Implementation[C].Berkeley,CA,2011.24.).Dolev et al. proposes one
Fair allocat (Bottle-based Fairness, BBF) algorithm (DOLEV D, FEITELSON D of the kind based on bottleneck
G,HALPERN J Y,et al.No justified complaints:On fair sharing of multiple
resources[A].Proceedings of the 3rd Innovations in Theoretical Computer
Science Conference[C].Cambridge,MA,2012.68-75.)；Bhattacharya et al. redefine DRF with
This supports multi-level resource allocation (BHATTACHARYA A A, CULLER D, FRIEDMAN E, et
al.Hierarchical scheduling for diverse datacenter workloads[A].Proceedings of
the 4th Annual Symposium on Cloud Computing(SOCC’13)[C].Erlangen,Germany,
2013.)；Wang et al. proposes improvement DRF strategies, can be suitable for isomery cloud computing environment (WANG W, LI B, LIANG
B.Dominant resource fairness in cloud computing systems with heterogeneous
servers[C].Proceedings of IEEE INFOCOM[C].Toronto,Canada,2014.583-591.)；
Psomans et al. research in multiple calculate nodes to more resource fairness distribution methods of discrete tasks (PSOMAS C A,
SCHWARTZ J.Beyond beyond dominant resource fairness:Indivisible resource
allocation in clusters[R].Tech Report Berkeley,2013.)；Parks et al. is extended with a variety of methods
DRF, including the zero demand of certain resources, not Divisible loads and weighted user tilt etc. situations (PARKES D C,
PROCACCIA A D,SHAH N.Beyond dominant resource fairness:extensions,
limitations,and indivisibilities[J].ACM Transactions on Economics and
Computation,2015,3(1):3.)；However these researchs are all based on the static state point of all user resources demands in system
Match, the dynamic for being added and exiting at random with user in real system has the difference of essence, and in resource allocation process not
Have in view of history distributes information.For this problem, researcher proposes resource fairness allocation strategy under a kind of dynamic case
DDRF, situation (KASH I, PROCACCIA A D, the SHAH N.No for allowing user that system is added at any time but not leaves
agent left behind:Dynamic fair division of multiple resources[J].Journal of
Artificial Intelligence Research,2014.579-603.).But researcher is that cloud is added based on user to be total to
Brought into when enjoying platform identical quantity resource it is assumed that consider otherness and resource point of the actual user to resource-sharing amount
Distribution condition with the user more than shared resource amount in scheduling process, so as to cause relatively low resource utilization and justice
Property.By the general introduction to the above resource fairness allocation strategy as can be seen that current resource allocation methods do not account for dynamic
User resources demand and influence of the shared stock number otherness to the fairness and efficiency of resource allocation under situation, it is therefore necessary to
Under cloud computing environment, being made further research to the more resource fairness distribution methods of dynamic makes it more meet real resource allocation schedule
Demand.
Invention content
To solve the above-mentioned problems, the present invention is based on the differences of user resources demand and shared resource amount under dynamic case
Property, provide a kind of more resource fairness distribution methods of dynamic towards under cloud computing environment, it is intended to solve in cloud computing shared platform
The fairness and efficiency of more resource allocations.
The present invention is built towards the more resource fairness distribution methods of dynamic under cloud computing environment by following step：
Dispose cloud computing experiment porch；More resource allocation attributes are described and are defined；It studies more under cloud computing environment
The more resource Dynamic Fairness Distribution Optimization Models of user；A kind of fast resource allocation algorithm is realized in design；Carry out emulation platform structure；
Test experiments are carried out to performance.
In cloud computing shared platform, user task request is by being responded with the virtual machine that different resource configures.
It is assumed that including m kind hardware resources, such as CPU, memory, disk, network bandwidth in resource pool.R={ 1,2 ... m } is enabled to indicate resource
Type set, U={ 1,2 ... n } indicate user set.The resource requirement vector of user i is Di=(Di1,…,Dim), wherein
DijIndicate that the task of user i accounts for the demand of resource j the ratio of the total amount of resource j in entire resource pool, and Dij＞ 0.To Di
Make normalized, obtains di=(di1,…,dij,…,dim), whereinUser i appoints
The resource having the call of being engaged in is superior resources j, i.e. dij=1.Enable wiIndicate shared moneys of the user i to each resource in resource pool
Source is measured, andWhen there is k user in system, k ∈ { 1 ..., n },Indicate superior resources part that user i is distributed
Specified number, you can the number of tasks of execution.It is defined according to superior resources, the superior resources share of user i is：
When there is k user in system, the more resource fairness allocation plans of a dynamic are Ak,
WhereinFor the resource allocation vector of user i.Indicate the money that user i is distributed on resource j
Source quantity meets condition to each resource j ∈ R：
Further, user resources demand and the more resource fairness Distribution Optimization Models of shared resource amount structure dynamic are based on：Knot
Close dynamic resource fair allocat during dynamic Pareto optimality, excitation sharing, dynamically without envy property, anti-tactic behaviour
Make, distribute irreversible attributive character, design a linear optimization model, see formula (1), by maximizing MkValue, acquires maximum
Change superior resources distribution share numberAnd ensure the fairness of resource allocation as far as possible.
Based on the linear programming model, a kind of faster polynomial time complexity algorithm is introduced, is solved most to improve
The algorithm operational efficiency problem of excellent allocation plan；The algorithm finds the corresponding v of a user τ using dichotomy thoughtτ(vτIt is corresponding
OneValue) so that ifIt sets up, thenOtherwiseAccording to preceding two in linear programming model (1)
A constraints is releasedSo that it is determined thatAnd it finally obtains
The present invention is directed to the more resource fairness assignment problems of multi-user under cloud computing environment, when entering system to user's dynamic,
The distributional equity and efficiency that the otherness of user resources demand and user institute shared resource amount is brought are made synthesis and are examined
Consider, a kind of more resource fairness distribution methods of dynamic towards under cloud computing environment are provided.This method provides excellent under dynamic case
Gesture resource and the definition of superior resources share, and a linear optimization model for meeting fair allocat attribute is built, meeting user
The maximum fairness distribution of superior resources is realized in resource requirement as far as possible simultaneously.Design a kind of more resource fairness allocation algorithms of dynamic
So that Riming time of algorithm complexity is reduced to Ο (n2Logn) (n is total number of users in system).Method energy provided by the invention
It enough solves the problems, such as the fair allocat of the more resources of multi-user under actual conditions, and improves allocation efficiency of resource.
The present invention has following technological merit：
One：Due to the diversity of shared resource type and user resources demand in cloud computing shared system and shared money
The otherness of source amount and user are dynamically added or log off so that the distribution of multi-kind resource is difficult to accomplish complete justice
Property, be based on this, in the case that a variety of different resources and depositing propose it is a kind of for dynamic case under superior resources fair allocat side
More resource problems are transformed into the assignment problem of single resource by method；
Secondly：Based on user resources demand and shared resource amount, the more resource fairness Distribution Optimization Models of a dynamic are established,
The model meet the dynamic Pareto optimality of fair allocat, excitation it is shared, dynamically without envy property, prevent tactic from operating, and
Irreversible attribute is distributed in dynamic allocation procedure, meeting under true cloud computing environment users to share resource and capable of obtaining justice has
Imitate the actual conditions of distribution；
Thirdly：The present invention provides one kind the quick more resource fairness allocation algorithms of dynamic, algorithm foundation linear programming model,
Optimal resource allocation scheme is solved using dichotomy thought, reduces Riming time of algorithm so that Algorithms T-cbmplexity is reduced to(n is total number of users in system).
Description of the drawings
Fig. 1 is the structure flow diagram of the invention towards the more resource fairness distribution methods of dynamic under cloud computing environment；
Fig. 2 is the flow diagram of the quick more resource fairness allocation algorithms of dynamic provided by the invention；
Fig. 3 is that the superior resources quota that the embodiment of the present invention obtains is based on wiVariation diagram, w in figureiBe user i to money
The shared resource amount of each resource in the pond of source,Indicate the superior resources quota that user i is distributed；
Fig. 4 is 100 user's superior resources quotas in the embodiment of the present inventionWith the comparative graph of optimal value, in figure
I is user,Indicate the superior resources quota that user i is distributed.
Specific implementation mode
In order to make the purpose of the present invention, technical solution and advantage be more clearly understood, below in conjunction with the accompanying drawings with embodiment
Invention is further described in detail, but the scope of the present invention is not limited to the content.
Originally whole concept towards the more resource fairness distribution methods of dynamic under cloud computing environment is：For under dynamic case
User task resource requirement and users to share stock number build the more resource fairness of the dynamic for meeting fair allocat attribute point
With Optimized model, the task of can perform number is maximized, and a polynomial time complexity is provided to solve optimal distributing scheme
Spend algorithm；Meeting task resource demand simultaneously, superior resources distribution share maximized under the distribution that guarantees fairness as far as possible,
And the more resource allocation algorithms of dynamic provided can improve allocation efficiency of resource so that Riming time of algorithm can be in Ο
(n2Logn it is realized in).
As shown in Figure 1, this is built towards the more resource fairness distribution methods of dynamic under cloud computing environment by following step：
Dispose cloud computing experiment porch；More resource allocation attributes are described and are defined；Multi-user under cloud computing environment is studied to provide more
Source Dynamic Fairness Distribution Optimization Model；A kind of fast resource allocation algorithm is realized in design；Carry out emulation platform structure；To performance into
Row test experiments.
One as the present embodiment solves scheme, and more resource allocation attributes are described and are defined as：
One as the present embodiment solves scheme, builds the linear programming model of a maximization superior resources quota
Method is：
It establishes shown in a linear programming model such as formula (1), maximizes MkValue, it is final so that when there are k in system
When user, superior resources quota is maximizedAnd ensure the fairness of resource allocation as far as possible.
Wherein first constraints be as far as possible guarantee superior resources fair allocat, meanwhile, shared resource amount is more
The superior resources quota that user distributes is more.In addition, (1) is given at other two constraints in more resource allocation process
Condition, i.e., when there is k user in system, being not less than in system to the superior resources quota that arbitrary user distributes has k-
Distribution condition when 1 user；When there is k user in system, the stock number that system can distribute is up toThis is linear
Optimized model meets dynamic resource fair allocat attribute：Dynamic Pareto optimality, excitation are shared, dynamically without envy property, anti-strategy
Property operation, distribute it is irreversible.
Further, according to linear programming optimum target Mk, a kind of more resource fairness allocation algorithms of dynamic are introduced, realize money
Source is quickly distributed.
The resource allocation process of the present embodiment is further described as shown in Figure 2：
Step 1：When there is k user in system, to k-1Value carries out non-increasing sequence (i ＜ k-1), i.e. v1≥…
≥vk-1,And user i is inputted to each resource j requirement vectors di；
Step 2：Calculate demand ds of the user i in each resourceijWith it is total obtained by first superior resources quota product
Resource allocation, i.e.,
Step 3：Judge whether total resource allocation is more than users to share stock number in system, i.e., to each resource j, such as
FruitIt sets up, goes to step 6；
Step 4：IfIt is invalid, the superior resources share number interval after sequence, i.e., to arbitrary i, i
∈ U, in section [v1,∞),[v2,v1],...,(0,vk-1], utilize binary search vτThe section [LB, UB] at place；
Step 5：Judge UB-LB ＞ 1, if set up, jumps to step 4, otherwise end loop；
Step 6：M is determined according to formula (2)kValue；
Step 7：Pass throughCalculate the superior resources quota that each user i is assigned to
Step 8：It calculatesExport allocation plans of the user i on resource j
Required CPU and Memory moneys in true calculating task load in the present embodiment 100 Google clusters of random selection
Source is asked as user resources, and dynamic sequential enters system, and is randomly provided the shared resource amount w of each useri, meetThe fast allocation procedures of resource are realized using the more resource fairness allocation algorithms of dynamic, and test user under dynamic case
The resource allocation conditions for the different sharing stock number brought.
Fig. 3 is shown in the influence that users to share stock number distributes user resources under dynamic case, uniformly has chosen wherein
The superior resources quota that 20 users distribute, and to wiCarry out ascending order arrangement.From figure 3, it can be seen that users to share
Stock number wiMore, the superior resources quota that distribution obtains is more, and the more resource fairness distribution methods of dynamic ensure that money
" fairness " of source distribution.
Fig. 4 shows the superior resources quota that 100 users are allocated under the more resource fairness allocation algorithms of dynamic
Namely distribute the comparison result for the optimal value that the number of tasks executed is obtained with solution linear programming equation group formula (1)；It can from Fig. 4
Go out the more resource fairness allocation algorithm curves of dynamic always close to optimal value curve, takes into account the efficiency and justice of resource allocation
Property.
The experimental result of embodiment is shown under dynamic case, can be taken into account by the more resource fairness distribution methods of dynamic
User resources demand, more moneys can be obtained in the more user of fair allocat shared resource amount as far as possible by turn ensuring
Source.
From the foregoing, it can be seen that the embodiment of the present invention is based on cloud shared platform resource allocation system, user task money is considered
Influence of the otherness of source demand and the shared amount of user resources to the fairness and efficiency of resource allocation, is thought using optimization programming
Road solves resource fairness assignment problem under dynamic case.
Specific embodiment described herein is only an example for the spirit of the invention.All spirit in the present invention
With within principle made by all any modification, equivalent and improvement etc., should be included within the scope of the present invention.
Claims (1)
1. a kind of more resource fairness distribution methods of dynamic towards under cloud computing environment, it is characterised in that include the following steps：
(1) it is based on user resources demand and shared resource amount under dynamic case, the more resource fairness of structure dynamic distribute linear programming
Model, the linear programming model are：
K is number of users in system in the linear programming model,Indicate the superior resources quota that user i is distributed, wiIt indicates
User i is to the shared resource amount of each resource in resource pool, dijIndicate demand of the user i tasks to resource j；The linear programming
Model determine when in system there are when k user, maximization MkValue, so that it is determined that superior resources part that each user distributes
Specified number
(2) it is based on above-mentioned linear programming model, optimal distributing scheme is solved by following step
Step 1：When there is k user in system, to k-1Value carries out non-increasing sequence (i ＜ k-1), i.e. v1≥...≥
vk-1,And user i is inputted to each resource j requirement vectors di=(di1,...,
dij,...,dim), it includes m kind hardware resources that wherein m, which refers in resource pool,；
Step 2：Calculate user i demand d in each resourceijIt is distributed with total resources obtained by first superior resources quota product
Amount, i.e.,
Step 3：Judge whether total resources sendout is more than users to share stock number in system, i.e., to each resource j, ifIt sets up, goes to step 6；
Step 4：IfIt is invalid, the superior resources share number interval after sequence, i.e., to arbitrary i, i ∈ U,
In section [v1,∞),[v2,v1],...,(0,vk-1], utilize binary search vτThe section [LB, UB] at place, wherein U=1,
2 ... n } indicate user's set；
Step 5：Judge UB-LB ＞ 1, if set up, jumps to step 4, otherwise end loop；
Step 6：M is determined according to following formulakValue,
Step 7：Pass throughCalculate the superior resources quota that each user i is assigned to
Step 8：It calculatesExport allocation plans of the user i on resource j
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| CN105871618B (en) | 2016-04-13 | 2019-05-24 | 上海交通大学 | More resource regulating methods of erratic demand are coped in cloud scheduler |
| CN108268317B (en) * | 2016-12-30 | 2020-07-28 | 华为技术有限公司 | Resource allocation method and device |
| CN110888732B (en) * | 2018-09-10 | 2023-04-25 | 中国移动通信集团黑龙江有限公司 | Resource allocation method, equipment, device and computer readable storage medium |
| CN109901929B (en) * | 2019-03-04 | 2023-04-18 | 云南大学 | Cloud computing task share fair distribution method under server level constraint |
| CN111510479B (en) * | 2020-04-08 | 2021-09-24 | 天津大学 | A resource allocation method and device for a heterogeneous cache system |
| CN111611076B (en) * | 2020-05-20 | 2023-03-28 | 云南大学 | Fair distribution method for mobile edge computing shared resources under task deployment constraint |
| CN113419827A (en) * | 2021-05-11 | 2021-09-21 | 北京天云融创软件技术有限公司 | High-performance computing resource scheduling fair sharing method |
| CN118138592B (en) * | 2024-04-30 | 2024-07-30 | 吉林省枫瑞科技有限公司 | Super-calculation simulation supporting method for prestressed concrete pipe structure based on cloud computing |
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