CN102571694A - Computer performance optimizing system and method of computer - Google Patents

Abstract

The invention discloses a computer performance optimizing system, which comprises a client for acquiring and reporting resource parameters of a local computer; a receiving server for receiving and clustering data; an analytic server for digging data and generating a pertinent performance optimizing strategy; a database for storing the resource parameters; and a strategy library for storing the strategy generated by the analytic server. The invention also discloses a computer performance optimizing method based on the system, which comprises the steps that: 1) the client acquires and reports the resource parameters of the local computer; 2) the receiving server receives and clusters the data; and 3) the analytic server digs the data and generates the strategy and issues the strategy to a target user. The computer performance optimizing system and the method are used to form the optimal computer performance optimizing strategy that is recommended to a user in demand under different configurations and occasions by analyzing and digging the resource parameters on massive user computers in the Internet, so that common users can master the initiative for resource configuration of the computer.

Description

A kind of computing power optimization system and method

Technical field

The present invention relates to a kind of computing power optimization system.The invention still further relates to computing power optimization method based on this system.

Background technology

Domestic consumer owing to there are not enough computer literacy, comprises operative knowledge of hardware knowledge, Windows operating system knowledge and various application software or the like when using personal computer, usually can run into the obstacle in the various uses, for example:

Situation at the machines configurations resource-constrained; Need open several progresses of work simultaneously, but system resource (cpu, internal memory, video card, network) is taken by other processes, which process the user can't identify can be closed; Which process can be hung up, thereby has influence on the operating efficiency of system;

During network game, the frequent phenomenons such as card, network delay that occur have a strong impact on user experience, and the user do not know that which process can temporarily be hung up on the computer;

Though which process the user knows and can close; But still can't grasp the initiative of resource allocation; Have a lot of unforeseen processes to be started and preempting resources by system or other external tools, therefore, the user can't guarantee that the progress of work that really needs at present can access enough resources.

More than be the common computer user in the process of using a computer, some typical problems that possibly run into.These problems solve and cause considerable trouble, very little technical problem sometimes, and the user also need look for the people to solve to the doorstep, so, has expended very big human cost and expense.And if the user has done inappropriate processing to some processes under situation out of the picture, also can cause system's operation exception; Even collapse, therefore, how to let the just-plainfolk grasp the initiative of system resource allocation; Confirm the most reasonably resources employment methods; Guaranteeing just-plainfolk's Computer Data Security and system safety, improve the computed experience of user, is a problem demanding prompt solution.

At present, following two kinds of solutions are arranged.The one, directly tactful hard coded (hardcode) in client owing to can't foresee user's PC environment, therefore, this strategy does not almost have availability.Another kind is that human-edited's strategy is issued by server afterwards, but this strategy that comes out by the imagination all can't satisfy user's demand usually, can waste edit asset on the contrary.

Summary of the invention

The technical problem that the present invention will solve provides a kind of computing power optimization system, and it can guarantee that the user grasps the initiative of system resource allocation.

For solving the problems of the technologies described above, computing power optimization system of the present invention includes:

Client is used to gather the various resource parameters on the subscriber computer, and reports reception server through the Internet;

Reception server is used to receive the data that client reports, and after data are carried out cluster, is saved in the database;

Analysis server is used for the data of database are carried out analysis mining, generates the computing power optimisation strategy under the different configuration different application scenes, is saved in the policy library, and is handed down to the user through the Internet;

Database is used to store the resource parameters data after reception server is handled;

Policy library is used for the computing power optimisation strategy that the inventory analysis server generates.

Said Analysis server further comprises:

The user clustering server is used for the hardware parameter according to each computer, and the user is sorted out;

Data mining server is used for the computer resource parameter is excavated, and generates under different configurations, the different scene best computing power optimisation strategy;

Distributor is used for the strategy that data mining server generates is handed down to the user through the Internet.

Another technical problem that the present invention will solve provides the computing power optimization method based on said system.

For solving the problems of the technologies described above, computing power optimization method of the present invention may further comprise the steps:

1) client is gathered the various resource parameters on the subscriber computer, and reports reception server through the Internet;

2) reception server carries out cluster to data, and is saved in the database;

3) Analysis server is sorted out the computer user according to the computer hardware parameter in the database;

4) Analysis server is analyzed and is excavated the data in the database, generate under different configurations and the different scenes, the computing power optimisation strategy of the best, and with step 4) in class of subscriber related after, be saved in the policy library;

5) Analysis server is given the policy distribution in the policy library and this strategy related user.

The present invention is through analyzing and excavate magnanimity computer user active resources shared configuring condition on the Internet; Form the optimum down resource distribution strategy of the different configurations of different scenes, recommend the targeted customer targetedly, so; Even if common computer user; Also can under the guiding of system recommendation strategy, exactly Computer Resources Allocation be optimized, thus the fail safe that has improved subscriber computer data and system greatly.

Description of drawings

Fig. 1 is system structural framework figure of the present invention;

Fig. 2 is a data message interaction figure of the present invention;

Fig. 3 is the method flow diagram of the embodiment of the invention.

Embodiment

Understand for technology contents of the present invention, characteristics and effect being had more specifically, combine illustrated execution mode at present, details are as follows:

See also shown in Fig. 1 and 3, the computing power optimization system of the embodiment of the invention includes:

Client is used to gather the various resource parameters of subscriber computer, and reports the Data Receiving server through the Internet.

Reception server is used to receive the resource parameters data that client reports, and after data are carried out cluster, is saved in the database.

Analysis server is used for the data of database are analyzed and excavated, and generates the computing power optimisation strategy under different configurations, the different application scene, is saved in the policy library, and is handed down to the user who needs.This Analysis server further includes user clustering server, data mining server and Distributor, and wherein, the user clustering server is used for the hardware parameter similarity according to each computer of database, and the user is sorted out; Data mining server is used for the resource parameters data of database are excavated, and generates under the different configuration different application scenes best computing power optimisation strategy; Distributor is used for the strategy of policy library is handed down to corresponding user through the Internet.

Database is used to store the subscriber computer resource parameters data after reception server is handled.

Policy library is used for the computing power optimisation strategy that the inventory analysis server is generated.

Below the implementation method of said system is done further explanation, see also shown in Fig. 2 and 3, include following steps:

At first; Client is under the situation that the user allows; Through WMI interfaces such as (Windows ManagementInstrumentation, Windows management frameworks), gather the various resource parameters on the subscriber computer; Comprise all information of software of installing on parameter and this subscriber computer of various hardware such as the mainboard that disposes on this subscriber computer, internal memory, video card, hard disk.After the resource parameters data encryption that collects,, report reception server through the Internet.

After reception server receives the resource parameters that client reports; To data decipher, processing such as decompress(ion), decoding and cleaning; Use similarity algorithm then, calculate the similarity of resource distribution between the various computing machine, and according to the similarity value that calculates; Data are carried out cluster, be saved in the database.

Then; Analysis server to the data in the database sort out, preliminary treatment such as denoising and cleaning; And, calculate every pairing user's of computer unique identification sign indicating number (being a string identification code of a computer of unique identification), according to the unique identification sign indicating number by the hardware parameter of user clustering server according to each computer; The user is sorted out, and similar user is included into same customer group with the Hardware configuration situation.

Simultaneously; Data mining server is according to the resource parameters of each computer; Calculate user's scene index of every computer; Use data mining algorithm then, the resource parameters under each user is carried out the cluster comparison, generate computing power optimisation strategy (a whole set of collocation strategy that comprises hardware and software installation scale) to the best of a certain type of resource distribution situation and scene based on Euclidean distance algorithm and Pearson came similarity algorithm.The strategy that generates and user's unique identification sign indicating number carry out related after, be saved in the policy library.

At last, by Distributor the strategy in the policy library is handed down to and this strategy related user through the Internet.After the user receives the strategy of system recommendation; Just can be under the guiding of this strategy; Resources employment methods to own computer is optimized, and Limited resources is used to support several progresses of work of current needs to greatest extent, and with other process temporary suspension or dormancy.Like this, even if common computer user also can grasp the initiative that computer resource disposes under any configuration and scene, improve own computed performance to greatest extent.

Claims (5)

1. a computing power optimization system is characterized in that, includes:

Client is used to gather the various resource parameters on the subscriber computer, and reports reception server through the Internet;

Reception server is used to receive the data that client reports, and after data are carried out cluster, is saved in the database;

Analysis server is used for the data of database are carried out analysis mining, generates the computing power optimisation strategy under the different configuration different application scenes, is saved in the policy library, and is handed down to the user through the Internet;

Database is used to store the resource parameters data after reception server is handled;

Policy library is used for the computing power optimisation strategy that the inventory analysis server generates.

2. to play 1 described computing power optimization system like right, it is characterized in that said Analysis server further comprises:

The user clustering server is used for the hardware parameter according to each computer, and the user is sorted out;

Data mining server is used for the computer resource parameter is excavated, and generates under different configurations, the different scene best computing power optimisation strategy;

Distributor is used for the strategy that data mining server generates is handed down to the user through the Internet.

3. according to claim 1 or claim 2 computing power optimization system is characterized in that: said resource parameters comprises the parameter of configured hardware and software on the subscriber computer.

4. according to claim 1 or claim 2 computing power optimization system, it is characterized in that: said computing power optimisation strategy adopts Euclidean distance algorithm and the generation of Pearson came similarity algorithm.

5. a computing power optimization method of realizing based on the system of claim 1 is characterized in that, may further comprise the steps:

1) client is gathered the various resource parameters on the subscriber computer, and reports reception server through the Internet;

2) reception server carries out cluster to data, and is saved in the database;

3) Analysis server is sorted out the computer user according to the computer hardware parameter in the database;

4) Analysis server is analyzed and is excavated the data in the database, generate under different configurations and the different scenes, the computing power optimisation strategy of the best, and with step 4) in class of subscriber related after, be saved in the policy library;

5) Analysis server is given the policy distribution in the policy library and this strategy related user.

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