CN102843419B - A kind of service resource allocation method and system - Google Patents
A kind of service resource allocation method and system Download PDFInfo
- Publication number
- CN102843419B CN102843419B CN201210226396.2A CN201210226396A CN102843419B CN 102843419 B CN102843419 B CN 102843419B CN 201210226396 A CN201210226396 A CN 201210226396A CN 102843419 B CN102843419 B CN 102843419B
- Authority
- CN
- China
- Prior art keywords
- application
- application server
- server
- cluster
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Landscapes
- Computer And Data Communications (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The invention discloses a kind of service resource allocation method, comprising: the initial demand quantity of application server in the application cluster that management server statistics is corresponding with goal systems; Described management server generates application information according to described initial demand quantity, and described application information is forwarded to cloud management platform; Described cloud management platform creates application server according to described application information, and described application server is dispensed to described application cluster.The invention also discloses a kind of service resource allocation system.Adopt the present invention, the dynamic assignment of application server can be realized, the elastic demand of goal systems can be met, the paroxysmal increase of user or minimizing be made to responding timely, effectively solve the concurrent systematic function stress problems brought peak period.
Description
Technical field
The present invention relates to the communications field, particularly relate to a kind of service resource allocation method and system.
Background technology
Traditional network system, in process of construction, generally needs the planning and designing first carrying out system, buys infrastructure and the software resources such as database, middleware such as server, storage and network, then carry out business software exploitation according to business demand.Therefore, system is once implement complete, and its extended capability is limited by the extended capability of the capacity such as calculating, storage and software.And infrastructure resources is fixing, cannot flexible allocation and recovery, can only carry out resource distribution in the design phase according to peak value, cause the wasting of resources, IT resource utilization is very low.Be subject to the restriction of above-mentioned construction mode and IT architecture, system, can only the number of visiting people of restriction system when peak is applied, and adopts the compromise mode of in batches accessing to carry out, as examination system, games system, ballot system etc.
In addition, in traditional software design pattern, the application architecture of software is normally closely-coupled to the demand of hardware, and at system design stage just according to function, the demands such as performance make the Compulsory Feature of system to hardware resource.And after developing operation, can only run on the hardware platform of certain configuration and can not arbitrarily change.Such architecture design has fettered the extensibility of system, and along with business increases, once need System Expansion or needs reply large-scale concurrent demand temporarily, system is often difficult to provide support fast.
At present, General System many employings Static expansion technology is expanded system, and this technology does not need to consider the problems such as data fault-tolerant, distributed metadata management, Resource dynamic allocation, thus relatively easy in realization.But the problem thus also with serving, as loaded down with trivial details in system extension process, availability is not high, administer and maintain difficulty etc., along with improving constantly of requiring system extension, the application support modes of this static state also can not adapt to the change demand of service dynamic, and the utilance of resource also needs further lifting.
Therefore, study a kind of dynamic expansion method, the business resiliency demand meeting different system becomes problem demanding prompt solution.
Summary of the invention
Technical problem to be solved by this invention is, a kind of service resource allocation method and system are provided, can according to factors such as the using states of the demand of keeper, pre-set user quantity, application server, be goal systems dynamic assignment application server effectively, realize the elastic telescopic of application server.
In order to solve the problems of the technologies described above, the invention provides a kind of service resource allocation method, comprising: the initial demand quantity of application server in the application cluster that management server statistics is corresponding with goal systems; Described management server generates application information according to described initial demand quantity, and described application information is forwarded to cloud management platform; Described cloud management platform creates application server according to described application information, and described application server is dispensed to described application cluster.
As the improvement of such scheme, in the application cluster that described management server statistics is corresponding with goal systems, the step of the initial demand quantity of application server comprises: described management server obtains the pre-set user quantity that keeper uploads; Described management server calculates the initial demand quantity of application server in described application cluster according to described pre-set user quantity.
As the improvement of such scheme, in the application cluster that described management server statistics is corresponding with goal systems, the step of the initial demand quantity of application server also comprises: described management server obtains the initial demand quantity of the application server that keeper uploads.
As the improvement of such scheme, described service resource allocation method also comprises: described management server Real-time Obtaining is dispensed to the state parameter of the application server in described application cluster, and described state parameter comprises current memory utilance, current C PU utilance, current response time; Described state parameter and pre-set threshold value scope are compared, and generate control information according to comparison result, described pre-set threshold value scope comprises default memory usage value range, presets cpu busy percentage value range, presets response time value range; Described control information is forwarded to cloud management platform; Described cloud management platform is according to application server quantity in described control information adjustment application cluster.
As the improvement of such scheme, the described step according to comparison result generation control information comprises: when described state parameter is all less than pre-set threshold value scope, generate the control information of release application server; When arbitrary described state parameter is greater than pre-set threshold value scope, generate the control information creating application server.
As the improvement of such scheme, described service resource allocation method also comprises: the recovery information that described cloud management platform Real-time Obtaining keeper issues, and according to the application server in described recovery information release application cluster.
Correspondingly, present invention also offers service resource allocation system, comprising: for providing the application server of service for goal systems; Corresponding with described goal systems, the application cluster be made up of one or more described application server; Management server, for application server quantity in the application cluster that real-time statistics is corresponding with goal systems, is sent to cloud management platform by the application information of generation and control information; Cloud management platform, for managing described application server, according to described application information, control information and recovery information distribution application server, realizes establishment and the release of application server in application cluster.
As the improvement of such scheme, described management server comprises: statistic unit, for adding up the initial demand quantity of application server in the application cluster corresponding with goal systems; Application unit, generates application information for the initial demand quantity of adding up according to described statistic unit; First retransmission unit, the application information for described application unit being generated is forwarded to described cloud management platform; Acquiring unit, is dispensed to the state parameter of the application server in described application cluster for Real-time Obtaining, described state parameter comprises current memory utilance, current C PU utilance, current response time; Comparing unit, for described state parameter and pre-set threshold value scope are compared, and generating control information according to comparison result, described pre-set threshold value scope comprises default memory usage value range, presets cpu busy percentage value range, presets response time value range; Second retransmission unit, the control information for being generated by described comparing unit is forwarded to cloud management platform.
As the improvement of such scheme, described statistic unit comprises: the first statistic unit, for obtaining the pre-set user quantity that keeper uploads, and calculates the initial demand quantity of application server in described application cluster according to described pre-set user quantity; Second statistic unit, for obtaining the initial demand quantity of the application server that keeper uploads.
As the improvement of such scheme, described first statistic unit comprises: obtain subelement, for obtaining the pre-set user quantity that keeper uploads; Computation subunit, the pre-set user quantity for obtaining according to described acquisition subelement calculates the initial demand quantity of application server in described application cluster.
Implement beneficial effect of the present invention to be:
Keeper according to the demand of goal systems, can upload pre-set user quantity, and management server can calculate the initial demand quantity of the application server of goal systems according to pre-set user quantity.In addition, management server can obtain the initial demand quantity of the application server that keeper uploads.Management server generates application information according to the initial demand quantity of application server, and application information is sent to cloud management platform, cloud management platform creates in the application cluster also corresponding to distributing application servers to goal systems, for goal systems provides service according to application information.
In addition, management server Real-time Obtaining is dispensed to the state parameter of the application server in described application cluster, and state parameter and pre-set threshold value scope are compared, and generate control information according to comparison result, wherein, when described state parameter is all less than pre-set threshold value scope, namely application server utilance is lower, generates the control information of release application server; When arbitrary described state parameter is greater than pre-set threshold value scope, namely application server utilance is higher, generates the control information creating application server.Control information is forwarded to cloud management platform by management server, cloud management platform creates according to control information or application server in release application cluster, realize the dynamic assignment of application server, the elastic demand of goal systems can be met, the paroxysmal increase of user or minimizing are made and responds timely, effectively solve the concurrent systematic function stress problems brought peak period.
Accompanying drawing explanation
Fig. 1 is the first embodiment schematic flow sheet of a kind of service resource allocation method of the present invention;
Fig. 2 is the second embodiment schematic flow sheet of a kind of service resource allocation method of the present invention;
Fig. 3 is the 3rd embodiment schematic flow sheet of a kind of service resource allocation method of the present invention;
Fig. 4 is the 4th embodiment schematic flow sheet of a kind of service resource allocation method of the present invention;
Fig. 5 is the example structure schematic diagram of a kind of service resource allocation system of the present invention;
Fig. 6 is the structural representation of management server in the embodiment of a kind of service resource allocation system of the present invention;
Fig. 7 is another structural representation of management server in the embodiment of a kind of service resource allocation system of the present invention.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail.
Fig. 1 is the first embodiment schematic flow sheet of a kind of service resource allocation method of the present invention, comprising:
S100, the initial demand quantity of application server in the application cluster that management server statistics is corresponding with goal systems.
It should be noted that, application cluster is made up of one or more application server, goal systems and application cluster one_to_one corresponding, and the goal systems of the application server in application cluster corresponding to application cluster provides service.Before goal systems starts, keeper first can estimate the scale of goal systems, and uploads relevant information, the initial demand quantity of the relevant information statistics application server that management server can be uploaded according to keeper.
S101, described management server generates application information according to described initial demand quantity, and described application information is forwarded to cloud management platform.
It should be noted that, application information comprises the initial demand quantity of application server, application cluster belonging to application server, application cluster said target system.
S102, described cloud management platform creates application server according to described application information, and described application server is dispensed to described application cluster.
The application information that cloud management platform forwards according to management server, application server is created in the mode of system image, and described application server is dispensed in the application cluster corresponding with goal systems, make described application server provide service for goal systems.
Fig. 2 is the second embodiment schematic flow sheet of a kind of service resource allocation method of the present invention, comprising:
S200, described management server obtains the pre-set user quantity that keeper uploads.
Before goal systems starts, keeper can first estimate the number of users logging in goal systems, and uploads pre-set user quantity to management server.
S201, described management server calculates the initial demand quantity of application server in described application cluster according to described pre-set user quantity.
It should be noted that, management server according to the computing formula preset, can calculate the initial demand quantity of application server in described application cluster by pre-set user quantity.Wherein, the computing formula preset, can be used for representing the variable relation between pre-set user quantity and initial demand quantity, keeper is according to practical operation experience adjustments computing formula.
S202, described management server generates application information according to described initial demand quantity, and described application information is forwarded to cloud management platform.
S203, described cloud management platform creates application server according to described application information, and described application server is dispensed to described application cluster.
The application information that cloud management platform forwards according to management server, application server is created in the mode of system image, and described application server is dispensed in the application cluster corresponding with goal systems, make described application server provide service for goal systems.
Such as, in examination system, keeper first estimates that the number of users participating in examination is 200.Before examination starts, the first upload user quantity of keeper is 200, and now, management server is according to the computing formula preset, and the initial demand quantity calculating application server in the application cluster corresponding with examination system is two.Management server generates application information according to initial demand quantity, and described application information is forwarded to cloud management platform.Correspondingly, cloud management platform, according to application information, creates two application servers in the mode of system image, and is dispensed in the application cluster corresponding with examination system by described application server, makes described application server provide service for examination system.
Fig. 3 is the 3rd embodiment schematic flow sheet of a kind of service resource allocation method of the present invention, comprising:
S300, described management server obtains the pre-set user quantity that keeper uploads.
Before goal systems starts, keeper can first estimate the number of users logging in goal systems, and uploads pre-set user quantity to management server.
S301, described management server calculates the initial demand quantity of application server in described application cluster according to described pre-set user quantity.
It should be noted that, management server according to the computing formula preset, can calculate the initial demand quantity of application server in described application cluster by pre-set user quantity.
S302, described management server obtains the initial demand quantity of the application server that keeper uploads.
It should be noted that, keeper rule of thumb directly can estimate the initial demand quantity of application server, and is uploaded to management server.Meanwhile, the initial demand quantity that keeper can also calculate according to management server, in conjunction with the initial demand quantity of empirical estimating application server, and is uploaded to management server.
Step S300 and step S302 does not have inevitable sequencing.The pre-set user quantity that initial demand quantity both can have been uploaded according to keeper by management server is directly calculated, also rule of thumb directly can be estimated by keeper, can also by keeper according to the result of calculation of management server and combine have experience estimation.
S303, described management server generates application information according to described initial demand quantity, and described application information is forwarded to cloud management platform.
S304, described cloud management platform creates application server according to described application information, and described application server is dispensed to described application cluster.
Such as, in examination system, keeper first estimates that the number of users participating in examination is 200.Before examination starts, the first upload user quantity of keeper is 200, and management server is according to the computing formula preset, and the initial demand quantity calculating application server in the application cluster corresponding with examination system is two.Now, keeper can in conjunction with having experience, and when preventing peak value, application server pressure is excessive, the initial demand quantity of application server is increased to three, and initial demand is quantitatively reached management server.Management server generates application information according to initial demand quantity, and described application information is forwarded to cloud management platform.Correspondingly, cloud management platform, according to application information, creates three application servers in the mode of system image, and is dispensed in the application cluster corresponding with examination system by described application server, makes described application server provide service for examination system.
Fig. 4 is the 4th embodiment schematic flow sheet of a kind of service resource allocation method of the present invention, comprising:
S400, described management server obtains the pre-set user quantity that keeper uploads.
Before goal systems starts, keeper can first estimate the number of users logging in goal systems, and uploads pre-set user quantity to management server.
S401, described management server calculates the initial demand quantity of application server in described application cluster according to described pre-set user quantity.
It should be noted that, management server according to the computing formula preset, can calculate the initial demand quantity of application server in described application cluster by pre-set user quantity.
S402, described management server obtains the initial demand quantity of the application server that keeper uploads.
It should be noted that the initial demand quantity that keeper can also calculate according to management server in conjunction with the initial demand quantity of empirical estimating application server, and is uploaded to management server.
S403, described management server generates application information according to described initial demand quantity, and described application information is forwarded to cloud management platform.
S404, described cloud management platform creates application server according to described application information, and described application server is dispensed to described application cluster.
The application information that cloud management platform forwards according to management server, application server is created in the mode of system image, and described application server is dispensed in the application cluster corresponding with goal systems, make described application server provide service for goal systems.
S405, described management server Real-time Obtaining is dispensed to the state parameter of the application server in described application cluster.
Described state parameter comprises current memory utilance, current C PU utilance, current response time.
When goal systems starts, application server provides service for corresponding goal systems, and management server Real-time Obtaining is dispensed to and the state parameter of goal systems to the application server in corresponding application cluster.
S406, compares described state parameter and pre-set threshold value scope, and generates control information according to comparison result.
Described pre-set threshold value scope comprises default memory usage value range, presets cpu busy percentage value range, presets response time value range.
State parameter and pre-set threshold value scope are compared by management server.
When described state parameter is all less than pre-set threshold value scope, generate the control information of release application server.Namely reach that current memory utilance is less than default memory usage value range, current C PU utilance is less than default cpu busy percentage value range, current response time when being less than default response time value range simultaneously, represent that the utilance of application server is too low, cause the waste of resource, now answer release portion application server with saving resource.
When arbitrary described state parameter is greater than pre-set threshold value scope, generate the control information creating application server.Namely occur that current memory utilance is greater than default memory usage value range, current C PU utilance is greater than default cpu busy percentage value range, the current response time is when being greater than any situation in default response time value range, represent that the utilance of application server is too high, cause the pressure of system, now should increase certain applications server to alleviate the load of existing application server.
Correspondingly, when not belonging to above-mentioned two states, representing and being fully utilized at the application server run, and not to goal systems build-up of pressure, without the need to creating or discharging any application server.
S407, is forwarded to cloud management platform by described control information.
S408, described cloud management platform is according to application server quantity in described control information adjustment application cluster.
The control information that cloud management platform forwards according to management server, creates application server in the mode of system image, or release application server, with application server quantity in dynamic conditioning application cluster.
S409, the recovery information that described cloud management platform Real-time Obtaining keeper issues, and according to the application server in described recovery information release application cluster.
It should be noted that, when after goal systems power cut-off, keeper can according to actual conditions directly issue release application server recovery information to cloud management platform to discharge all application servers.
Such as, in examination system, if keeper first estimates that the number of users participating in examination is 200.
Before examination starts, the first upload user quantity of keeper is 200, and management server is according to the computing formula preset, and the initial demand quantity calculating application server in the application cluster corresponding with examination system is two.Now, keeper can in conjunction with experience, and when preventing peak value, application server pressure is excessive, the initial demand quantity of application server is increased to three, and initial demand is quantitatively reached management server.Management server generates application information according to initial demand quantity, and described application information is forwarded to cloud management platform.Correspondingly, cloud management platform, according to application information, creates three application servers in the mode of system image, and is dispensed in the application cluster corresponding with examination system by described application server.
When starting when taking an examination, application server provides service, the state parameter of management server Real-time Obtaining application server for examination system.In examination process, being on the increase of calling party thereupon, makes the state parameter of application server constantly rise, and when any state parameter is greater than pre-set threshold value scope, management server generates the control information creating application server.Control information is forwarded to cloud management platform by management server, cloud management platform is according to control information, application server is created in the mode of system image, and the application server newly created is dispensed in the application cluster corresponding with examination system, make described application server provide service for examination system.After access peak value terminates, the continuous minimizing of calling party, makes the state parameter of application server constantly decline, and when state parameter is all less than pre-set threshold value scope, management server generates the control information of release application server.Control information is forwarded to cloud management platform by management server, and cloud management platform is according to control information, and release portion application server, to realize the dynamic assignment of application server.After examination terminates, still have certain applications server to maintain the basic running of examination system, now keeper issue discharge all application servers recovery information to cloud management platform, discharge all application servers, realize the recycled in its entirety of examination system.
As shown in Figure 5, service resource allocation system 5 comprises:
For providing the application server 1 of service for goal systems, the quantity of described application server 1 can be one or more.
Corresponding with described goal systems, the application cluster 2 be made up of one or more described application server 1.
It should be noted that, application cluster 2 is made up of one or more application server 1, goal systems and application cluster 2 one_to_one corresponding, and the goal systems of the application server 1 in application cluster 2 corresponding to application cluster 2 provides service.
Management server 3, for application server 1 quantity in the application cluster 2 that real-time statistics is corresponding with goal systems, is sent to cloud management platform 4 by the application information of generation and control information.
Cloud management platform 4, for managing described application server 1, according to described application information, control information and recovery information distribution application server 1, realizes establishment and the release of application server 1 in application cluster 2.
Before goal systems starts, in the application cluster 2 that management server 3 statistics is corresponding with goal systems, the initial demand quantity of application server 1, generates application information according to initial demand quantity, and described application information is forwarded to cloud management platform 4.Correspondingly, cloud management platform 4, according to application information, creates application server 1 in the mode of system image, and described application server 1 to be dispensed in the application cluster corresponding with goal systems 2.
During goal systems work, application server 1 provides service for goal systems, and the state parameter of management server 3 Real-time Obtaining application server 1, compares state parameter and pre-set threshold value scope, generation control information, and is forwarded to management platform 4.The control information that cloud management platform 4 forwards according to management server 3, creates application server 1 in the mode of system image, or release application server 1, with application server 1 quantity in dynamic conditioning application cluster 2.
During goal systems power cut-off, keeper can according to actual conditions directly issue release application server 1 recovery information to cloud management platform 4 to discharge all application servers 1.
As shown in Figure 6, management server 3 comprises:
Statistic unit 31, for adding up the initial demand quantity of application server 1 in the application cluster 2 corresponding with goal systems.
Application unit 32, generates application information for the initial demand quantity of adding up according to described statistic unit 31.
First retransmission unit 33, the application information for described application unit 32 being generated is forwarded to described cloud management platform 4.
Before goal systems starts, the initial demand quantity of application server 1 in the application cluster 2 that statistic unit 31 statistics is corresponding with goal systems, application unit 32 generates application information according to initial demand quantity, and described application information is forwarded to cloud management platform 4 by the first retransmission unit 33.Correspondingly, cloud management platform 4, according to application information, creates application server 1 in the mode of system image, and described application server 1 to be dispensed in the application cluster corresponding with goal systems 2.
As shown in Figure 6, management server 3 also comprises:
Acquiring unit 34, is dispensed to the state parameter of the application server 1 in described application cluster 2 for Real-time Obtaining.Described state parameter comprises current memory utilance, current C PU utilance, current response time.
Comparing unit 35, for described state parameter and pre-set threshold value scope being compared, and generates control information according to comparison result.Described pre-set threshold value scope comprises default memory usage value range, presets cpu busy percentage value range, presets response time value range.
When described state parameter is all less than pre-set threshold value scope, generate the control information of release application server 1.Namely reach that current memory utilance is less than default memory usage value range, current C PU utilance is less than default cpu busy percentage value range, current response time when being less than default response time value range simultaneously, represent that the utilance of application server 1 is too low, cause the waste of resource, now answer release portion application server 1 with saving resource.
When arbitrary described state parameter is greater than pre-set threshold value scope, generate the control information creating application server 1.Namely occur that current memory utilance is greater than default memory usage value range, current C PU utilance is greater than default cpu busy percentage value range, the current response time is when being greater than any situation in default response time value range, represent that the utilance of application server 1 is too high, cause the pressure of system, now should increase certain applications server 1 to alleviate the load of existing application server.
Correspondingly, when not belonging to above-mentioned two states, representing and being fully utilized at the application server 1 run, and not to goal systems build-up of pressure, without the need to creating or discharging any application server 1.
Second retransmission unit 36, is forwarded to cloud management platform 4 for the control information generated by described comparing unit 35.
When goal systems works, application server 1 provides service, the state parameter of acquiring unit 34 Real-time Obtaining application server 1 for goal systems.In the running of goal systems, along with being on the increase of calling party, the state parameter of application server 1 is made constantly to increase, state parameter and pre-set threshold value scope are carried out real-time comparison by comparing unit 35, generate control information, and by the second retransmission unit 36, the control information that described comparing unit 35 generates is forwarded to cloud management platform 4.Cloud management platform 4 is according to control information, and dynamic creation or release application server 1, alleviate system pressure, reduce the wasting of resources.
Fig. 7 is another structural representation of management server 3 in the embodiment of a kind of service resource allocation system 5 of the present invention, with Fig. 6 unlike, statistic unit 31 comprises:
First statistic unit 311, for obtaining the pre-set user quantity that keeper uploads, and calculates the initial demand quantity of application server 1 in described application cluster according to described pre-set user quantity.
Second statistic unit 312, for obtaining the initial demand quantity of the application server 1 that keeper uploads.
It should be noted that, keeper can estimate the number of users of access destination system and upload, and obtains number of users and calculate the initial demand quantity of application server 1 by the first statistic unit 311.Or keeper also directly can estimate the initial demand quantity of the application server 1 needed for goal systems and upload, and the second statistic unit 312 directly can obtain the initial demand quantity of the application server 1 that keeper uploads.
More preferably, the first statistic unit 311 also comprises:
Obtain subelement 3111, for obtaining the pre-set user quantity that keeper uploads.
Computation subunit 3112, the pre-set user quantity for obtaining according to described acquisition subelement 3111 calculates the initial demand quantity of application server 1 in described application cluster 2.
Before goal systems starts, keeper can estimate the number of users of access destination system and upload, and obtains after subelement 3111 obtains the pre-set user quantity that keeper uploads, is calculated the initial demand quantity of application server 1 by computation subunit 3112.Or keeper also directly can estimate the initial demand quantity of the application server 1 needed for goal systems and upload, meanwhile, the second statistic unit 312 directly can obtain the initial demand quantity of the application server 1 that keeper uploads.Application unit 32 generates application information according to initial demand quantity, and described application information is forwarded to cloud management platform 4 by the first retransmission unit 33.Correspondingly, cloud management platform 4, according to application information, creates application server 1 in the mode of system image, and described application server 1 to be dispensed in the application cluster corresponding with goal systems 2.
As from the foregoing, keeper according to the demand of goal systems, can upload pre-set user quantity, and the first statistic unit 311 can calculate the initial demand quantity of the application server 1 of goal systems according to pre-set user quantity.In addition, the second statistic unit 312 can obtain the initial demand quantity of the application server 1 that keeper uploads.The initial demand quantity of the application server 1 that application unit 32 is added up according to the first statistic unit 311 or the second statistic unit 312 generates application information, and by the first retransmission unit 33, application information is sent to cloud management platform 4, cloud management platform 4 creates in the application cluster 2 also corresponding to distributing application servers 1 to goal systems, for goal systems provides service according to application information.In addition, acquiring unit 34 Real-time Obtaining of management server 3 is dispensed to the state parameter of the application server 1 in described application cluster 2, and by comparing unit 35, state parameter and pre-set threshold value scope are compared, and generate control information according to comparison result, wherein, when described state parameter is all less than pre-set threshold value scope, namely application server 1 utilance is lower, generates the control information of release application server 1; When arbitrary described state parameter is greater than pre-set threshold value scope, namely application server 1 utilance is higher, generates the control information creating application server 1.Control information is forwarded to cloud management platform 4 by the second retransmission unit 36, cloud management platform 4 creates according to control information or application server 1 in release application cluster, realize the dynamic assignment of application server 1, the elastic demand of goal systems can be met, the paroxysmal increase of user or minimizing are made and responds timely, effectively solve the concurrent systematic function stress problems brought peak period.In addition, keeper can according to actual conditions directly issue release application server 1 recovery information to cloud management platform 4 to discharge all application servers 1, the recovery of realize target system.
The above is the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications are also considered as protection scope of the present invention.
Claims (4)
1. a service resource allocation method, is characterized in that, comprising:
The initial demand quantity of application server in the application cluster that management server statistics is corresponding with goal systems;
Described management server generates application information according to described initial demand quantity, and described application information is forwarded to cloud management platform;
Described cloud management platform, according to described application information, creates application server in the mode of system image, and described application server is dispensed to described application cluster;
Application information comprises the initial demand quantity of application server, application cluster belonging to application server, application cluster said target system;
In the application cluster that described management server statistics is corresponding with goal systems, the step of the initial demand quantity of application server comprises: described management server obtains the pre-set user quantity that keeper uploads; Described management server calculates the initial demand quantity of application server in described application cluster according to described pre-set user quantity;
In the application cluster that described management server statistics is corresponding with goal systems, the step of the initial demand quantity of application server also comprises: described management server obtains the initial demand quantity of the application server that keeper uploads;
Described service resource allocation method also comprises: described management server Real-time Obtaining is dispensed to the state parameter of the application server in described application cluster, and described state parameter comprises current memory utilance, current C PU utilance, current response time; Described state parameter and pre-set threshold value scope are compared, and generate control information according to comparison result, described pre-set threshold value scope comprises default memory usage value range, presets cpu busy percentage value range, presets response time value range; Described control information is forwarded to cloud management platform; Described cloud management platform is according to application server quantity in described control information adjustment application cluster.
2. service resource allocation method as claimed in claim 1, is characterized in that, the described step according to comparison result generation control information comprises:
When described state parameter is all less than pre-set threshold value scope, generate the control information of release application server;
When arbitrary described state parameter is greater than pre-set threshold value scope, generate the control information creating application server.
3. service resource allocation method as claimed in claim 1 or 2, is characterized in that, also comprise:
The recovery information that described cloud management platform Real-time Obtaining keeper issues, and according to the application server in described recovery information release application cluster.
4. a service resource allocation system, is characterized in that, comprising:
For providing the application server of service for goal systems;
Corresponding with described goal systems, the application cluster be made up of one or more described application server;
Management server, for application server quantity in the application cluster that real-time statistics is corresponding with goal systems, is sent to cloud management platform by the application information of generation and control information;
Cloud management platform, for managing described application server, according to described application information, control information and the information of recovery, with the mode distributing application servers of system image, realizes establishment and the release of application server in application cluster;
Application information comprises the initial demand quantity of application server, application cluster belonging to application server, application cluster said target system;
Described management server comprises: statistic unit, for adding up the initial demand quantity of application server in the application cluster corresponding with goal systems; Application unit, generates application information for the initial demand quantity of adding up according to described statistic unit; First retransmission unit, the application information for described application unit being generated is forwarded to described cloud management platform; Acquiring unit, is dispensed to the state parameter of the application server in described application cluster for Real-time Obtaining, described state parameter comprises current memory utilance, current C PU utilance, current response time; Comparing unit, for described state parameter and pre-set threshold value scope being compared, and generates control information according to comparison result, and described pre-set threshold value comprises default memory usage value range, presets cpu busy percentage value range, presets response time value range; Second retransmission unit, the control information for being generated by described comparing unit is forwarded to cloud management platform;
Described statistic unit comprises: the first statistic unit, for obtaining the pre-set user quantity that keeper uploads, and calculates the initial demand quantity of application server in described application cluster according to described pre-set user quantity; Second statistic unit, for obtaining the initial demand quantity of the application server that keeper uploads;
Described first statistic unit comprises: obtain subelement, for obtaining the pre-set user quantity that keeper uploads; Computation subunit, the pre-set user quantity for obtaining according to described acquisition subelement calculates the initial demand quantity of application server in described application cluster.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201210226396.2A CN102843419B (en) | 2012-07-03 | 2012-07-03 | A kind of service resource allocation method and system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201210226396.2A CN102843419B (en) | 2012-07-03 | 2012-07-03 | A kind of service resource allocation method and system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN102843419A CN102843419A (en) | 2012-12-26 |
CN102843419B true CN102843419B (en) | 2015-08-12 |
Family
ID=47370472
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201210226396.2A Active CN102843419B (en) | 2012-07-03 | 2012-07-03 | A kind of service resource allocation method and system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN102843419B (en) |
Families Citing this family (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104348887B (en) * | 2013-08-09 | 2019-02-19 | 中国电信股份有限公司 | Resource allocation methods and device in cloud management platform |
CN103473140A (en) * | 2013-10-09 | 2013-12-25 | 浪潮(北京)电子信息产业有限公司 | Cluster distribution method of life science applications, and software setup method and device applied of life science applications |
CN105095042B (en) * | 2014-05-06 | 2017-09-29 | 中国电信股份有限公司 | Management information system and its method for processing business |
CN105100152A (en) * | 2014-05-14 | 2015-11-25 | 腾讯科技(深圳)有限公司 | Application server selection method and system, and application client |
CN104202388A (en) * | 2014-08-27 | 2014-12-10 | 福建富士通信息软件有限公司 | Automatic load balancing system based on cloud platform |
CN104333600A (en) * | 2014-11-13 | 2015-02-04 | 浪潮(北京)电子信息产业有限公司 | Cloud computing based resource managing method and system |
CN104486148B (en) * | 2014-12-04 | 2018-11-23 | 北京百度网讯科技有限公司 | A kind of server recycling and control method and device |
CN104850931A (en) * | 2015-04-09 | 2015-08-19 | 北京百度网讯科技有限公司 | Server update control method and device |
CN106533713B (en) * | 2015-09-09 | 2019-12-10 | 阿里巴巴集团控股有限公司 | Application deployment method and device |
CN105227676A (en) * | 2015-10-20 | 2016-01-06 | 珠海许继芝电网自动化有限公司 | A kind of method of distribution terminal data acquisition |
CN105245617A (en) * | 2015-10-27 | 2016-01-13 | 江苏电力信息技术有限公司 | Container-based server resource supply method |
CN106775809B (en) * | 2016-11-15 | 2020-02-07 | 北京安云世纪科技有限公司 | Method and device for cleaning memory of mobile terminal and mobile terminal |
CN106713021B (en) * | 2016-12-09 | 2020-02-11 | 北京奇虎科技有限公司 | Method and device for judging whether server in cluster needs to be recycled |
CN106961670B (en) * | 2017-05-02 | 2019-03-12 | 千寻位置网络有限公司 | Geo-fencing system and working method based on distributed structure/architecture |
CN112346850A (en) * | 2019-08-09 | 2021-02-09 | 北京国双科技有限公司 | Method and device for configuring memory |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102065122A (en) * | 2010-11-11 | 2011-05-18 | 上海海事大学 | Ship network construction method based on radio frequency identification and cloud computing |
CN102427481A (en) * | 2012-01-12 | 2012-04-25 | 易云捷讯科技(北京)有限公司 | System for managing cloud computing service and cloud computing management method |
-
2012
- 2012-07-03 CN CN201210226396.2A patent/CN102843419B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102065122A (en) * | 2010-11-11 | 2011-05-18 | 上海海事大学 | Ship network construction method based on radio frequency identification and cloud computing |
CN102427481A (en) * | 2012-01-12 | 2012-04-25 | 易云捷讯科技(北京)有限公司 | System for managing cloud computing service and cloud computing management method |
Non-Patent Citations (1)
Title |
---|
李书生,段勇,石屹嵘,叶宇航.电信BS架构系统迁移及云化研究.《电信科学》.2012,全文. * |
Also Published As
Publication number | Publication date |
---|---|
CN102843419A (en) | 2012-12-26 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN102843419B (en) | A kind of service resource allocation method and system | |
CN110138732B (en) | Access request response method, device, equipment and storage medium | |
CN103559072B (en) | Virtual machine two-way automatic telescopic service implementing method and system thereof | |
CN105893148B (en) | A kind of accidental task low energy consumption dispatching method based on RM strategy | |
CN102158513A (en) | Service cluster and energy-saving method and device thereof | |
CN111770157B (en) | Business processing method and device, electronic equipment and storage medium | |
CN105159775A (en) | Load balancer based management system and management method for cloud computing data center | |
CN103856512A (en) | Cloud computing management server, working host, idle host and resource scheduling method | |
CN102932418B (en) | Cloud application deploying method and device | |
CN104065663A (en) | Auto-expanding/shrinking cost-optimized content distribution service method based on hybrid cloud scheduling model | |
CN102148846B (en) | Method, device and system for realizing service access of access gateways | |
CN108366082A (en) | Expansion method and flash chamber | |
CN103237037A (en) | Media format conversion method and system based on cloud computing architecture | |
Singh et al. | Container-based load balancing for energy efficiency in software-defined edge computing environment | |
CN108924203B (en) | Data copy self-adaptive distribution method, distributed computing system and related equipment | |
CN110149377A (en) | A kind of video service node resource allocation methods, system, device and storage medium | |
CN102419753B (en) | Information processing equipment, information processing method and information processing system | |
CN113342827A (en) | Power grid data storage method, storage medium and system based on multi-tenant technology | |
Yao et al. | Data-driven resource allocation with traffic load prediction | |
CN117394370B (en) | Intelligent dynamic power-saving scheduling system and method for power supply network | |
CN103973784A (en) | Method for effectively utilizing resources of cloud storage server | |
CN115794305B (en) | Method and device for adjusting memory of virtual machine, storage medium and electronic device | |
CN111143055A (en) | Virtual cloud host pre-allocation method and device, readable storage medium and electronic equipment | |
CN115756135A (en) | Processor management method and computing device | |
CN110308991A (en) | A kind of data center's energy conservation optimizing method and system based on Random Task |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant |