WO2017092255A1 - 应用的在线调优方法及系统 - Google Patents

应用的在线调优方法及系统 Download PDF

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Publication number
WO2017092255A1
WO2017092255A1 PCT/CN2016/083206 CN2016083206W WO2017092255A1 WO 2017092255 A1 WO2017092255 A1 WO 2017092255A1 CN 2016083206 W CN2016083206 W CN 2016083206W WO 2017092255 A1 WO2017092255 A1 WO 2017092255A1
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Prior art keywords
type
tuning
user terminal
determining
application
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PCT/CN2016/083206
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English (en)
French (fr)
Inventor
李洪福
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乐视控股（北京）有限公司
乐视云计算有限公司
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Priority to US15/253,013 priority Critical patent/US20170156018A1/en
Publication of WO2017092255A1 publication Critical patent/WO2017092255A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/445—Program loading or initiating
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/445—Program loading or initiating
    • G06F9/44568—Immediately runnable code
    • G06F9/44578—Preparing or optimising for loading

Definitions

  • the present invention relates to the field of Internet technologies, and in particular, to an online tuning method and system for an application.
  • the application software publisher needs to provide a new version of the application software installation package periodically or irregularly to implement the function upgrade of the old version software of the application software.
  • the upgrade process of the existing application software generally includes: the software publisher releases the installation package of the new version software through various promotion channels, the user can download the installation package of the new version software from various promotion channels, and install the installation of the new version software in the user terminal. The package is replaced with an old version of the application software in the user terminal to complete the upgrade, and the software function in the user terminal is upgraded.
  • the embodiment of the present invention provides an online tuning method and system for applying the technical problem that the application software upgrade in the prior art cannot balance the configuration parameters of all current user terminals.
  • an online tuning method for an application including:
  • each indicator set in the type reference frame corresponds to one type, and determining that the characteristic parameter set is similar to multiple of the respective indicator sets Degree, determining a type of the user terminal based on a similarity calculation result;
  • an online tuning system for an application including:
  • a request receiving module configured to receive an application tuning request sent by the user terminal
  • a request parsing module configured to parse the application tuning request, and determine a characteristic parameter set of the user terminal
  • a terminal type determining module configured to compare the characteristic parameter set with each indicator set in a type reference system, where each indicator set in the type reference system corresponds to one type, and the characteristic parameter set is determined to be Determining a plurality of similarities of each indicator set, determining a type of the user terminal based on the similarity determination result;
  • the tuning parameter sending module is configured to refer to the tuning parameter configuration list corresponding to each type in the type reference system according to the determined type of the user terminal, determine the adapted tuning parameter configuration file, and send the configuration file to the user terminal.
  • the tuning parameter configuration file is configured to refer to the tuning parameter configuration list corresponding to each type in the type reference system according to the determined type of the user terminal, determine the adapted tuning parameter configuration file, and send the configuration file to the user terminal.
  • the application online optimization method and system provided by the embodiments of the present invention can be used for a user terminal with different characteristic parameters (configuration parameters) for the application of the application, and the application for which the application is installed is more suitable for the operation of the tuning parameter list, thereby ensuring Applications running with different user terminals have more suitable operating parameters to ensure service quality and enhance user experience.
  • 1 is a flow chart of an embodiment of an online tuning method for an application of the present invention
  • FIG. 2 is a flow chart of another embodiment of an online tuning method for an application of the present invention.
  • FIG. 3 is a flow chart of still another embodiment of an online tuning method of an application of the present invention.
  • FIG. 5 is a schematic diagram of an embodiment of an online tuning system applied to the present invention.
  • FIG. 6 is a schematic diagram of an embodiment of a terminal type determining module in the present invention.
  • FIG. 7 is a schematic diagram of another embodiment of an online tuning system of an application of the present invention.
  • FIG. 8 is a schematic diagram of still another embodiment of an online tuning system for use of the present invention.
  • the invention is applicable to a wide variety of general purpose or special purpose computing system environments or configurations.
  • the invention may be described in the general context of computer-executable instructions executed by a computer, such as a program module.
  • program modules include routines, programs, objects, components, data structures, and the like that perform particular tasks or implement particular abstract data types.
  • the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are connected through a communication network.
  • program modules can be located in both local and remote computer storage media including storage devices.
  • an online tuning method for an application of an embodiment of the present invention includes:
  • the server receives an application tuning request sent by the user terminal.
  • the server parses the application tuning request, and determines a characteristic parameter set of the user terminal.
  • the server compares the characteristic parameter set with each indicator set in the type reference system, where each indicator set in the type reference frame corresponds to one type, and determines the characteristic parameter set and the respective indicator set. a plurality of similarities, determining a type of the user terminal based on the similarity determination result;
  • the server determines, according to the determined type of the user terminal, a tuning parameter configuration list corresponding to each type in the type reference system, and determines an adapted tuning parameter configuration file, and sends the tuning parameter to the user terminal. Configuration file.
  • the user terminal sends an application tuning request according to a predetermined period or when the application carried by the user terminal is started, and the server parses the user terminal that sends the application tuning request from the request after receiving the application tuning request. a specific parameter set; and then, according to the determined characteristic parameter of the user terminal, compares with each indicator set in the known type reference system (each indicator set corresponds to one type), and determines that the user terminal that sends the application tuning request belongs to The terminal type; after determining the terminal type of the user terminal that sends the tuning request, refer to the tuning parameter configuration list corresponding to each type in the known type reference system, and the application tuning parameter configuration file adapted to the terminal type. Send to the user terminal that sent the request to achieve online tuning of the application it is loading.
  • the user terminal is a smart terminal
  • the smart terminal may be a mobile phone (for example, a music phone), or may be a portable, pocket, handheld, computer built-in or vehicle-mounted mobile device, or It is a PC (personal computer), a tablet computer, etc., and can also be a smart TV (for example, LeTV super TV) capable of connecting to the Internet, a set top box, etc., so that the smart terminal can realize the collection of natural information of the object to be identified.
  • a smart terminal for example, a music phone
  • PC personal computer
  • a tablet computer etc.
  • a smart TV for example, LeTV super TV
  • an indicator that is associated with the similarity that is greater than a threshold upper limit among the plurality of similarities is determined.
  • the type corresponding to the set is determined as the type of the user terminal.
  • the server determines a plurality of similarities between the characteristic parameter set and the respective indicator sets, and determines that the types of the user terminals include:
  • the server generates a vector by using a characteristic parameter set of the user terminal.
  • the server determines a similarity between the characteristic parameter set and a vector generated by the characteristic parameter set corresponding to each type of user terminal.
  • the server determines that the type of the similarity exceeds the first threshold is a terminal type of the user terminal.
  • the user end that sends the application tuning request is determined by the similarity between the vector generated by the characteristic parameter set of the user terminal and the vector generated by the characteristic parameter set of the known terminal type.
  • the cosine similarity algorithm is specifically used to calculate the similarity between the user terminal that sends the application tuning request and the known terminal type, and when the similarity value exceeds the first threshold, it is determined to send the application tuning request.
  • the user terminal is the current known terminal type; wherein the first threshold can be adjusted according to the requirement of the classification accuracy, and the value is generally 0.8, that is, when the acquaintance value exceeds 0.8, the sending application tuning request is determined.
  • the user terminal is the current known terminal type.
  • the classification of the terminal type is classified according to the characteristic parameters of the user terminal of the entire network in advance, and the update speed of the user terminal is fast, a new user terminal appears at any time, and the new user is followed.
  • the appearance of the characteristic parameters of the terminal when a user terminal with a new characteristic parameter appears, it is impossible to find a matching terminal type according to the pre-stated terminal type, and then a new terminal type is separately established, and Debugging a set of tuning parameters of a group of applications for the application installed on the user terminal of the type is configured in the configuration file of the newly created user terminal type, so that the type of the user terminal can be quickly determined when the user terminal is reappeared. And assign a corresponding list of tuning parameters.
  • the tuning parameter list includes at least one of: a data processing area selection parameter (local or server-side processing), a download speed parameter, a P2P/CDN selection parameter, a size of a P2P buffer buffer, and a local cache control parameter, and the present invention
  • the embodiments include, but are not limited to, the parameters listed above; by setting the data processing area selection parameters, it is possible to select whether the content of the application runtime offset calculation is implemented locally (ie, user terminal) or on the server side.
  • the content of the partial calculation can be implemented on the user terminal by setting the parameter, so as to reduce the burden on the server, and the server can better provide better quality for other user terminals.
  • Service when the CPU parameter is relatively low, the content of the partial calculation can be implemented on the server by setting the parameter to ensure the quality of service for the user.
  • the download speed parameter may be configured to configure a large download speed for the user terminal; when the user is a P2P user or a CDN user, and the memory of the user terminal is relatively large, Select parameters, P2P buffers through P2P/CDN The size of the buffer area is for the user to select a P2P service or a CDN service, and allocate an appropriate size P2P buffer buffer to it.
  • the server determines the plurality of similarities between the characteristic parameter set and the respective indicator sets
  • the server determines the user terminal as a new type, and establishes the characteristic parameter in the type reference system. Set a corresponding new set of indicators and the new type;
  • the server creates a new tuning parameter configuration file corresponding thereto according to the new type.
  • the server adds the new tuning parameter configuration file to the tuning parameter configuration list.
  • the type reference is generated by the following steps:
  • the server collects a characteristic parameter set of the user terminal of the entire network.
  • the server establishes a characteristic parameter set of each user terminal as a multi-dimensional vector, and the number of dimensions of the vector is equal to the number of the characteristic parameters;
  • the server classifies the user terminal by performing similarity calculation between each of the multi-dimensional vectors to generate the type reference system.
  • the server collects the characteristic parameter set of the user terminal of the entire network, and establishes the characteristic parameter set of the user terminal as a multi-dimensional vector, and then classifies the user terminal by calculating a cosine similarity between the multi-dimensional vectors;
  • the method of similarity calculation realizes the quantification of similarity between two terminals, which makes the classification of user terminals more scientific and accurate.
  • the characteristic parameter includes at least one of a CPU parameter, a running memory size, a storage space size, a screen resolution, a camera pixel, an operating system type, an uplink network bandwidth, and a downlink network bandwidth, but is not limited to the foregoing.
  • the listed parameters can be adjusted by the developer according to their own needs or the importance of various parameters.
  • the user terminal can be classified as follows:
  • the first category CPU parameters -8 core - 1.8GHz frequency, running memory -2G, storage space -16G;
  • the second category CPU parameters - 4 core - 1.8GHz frequency, running memory - 2G, storage space - 16G;
  • the third category CPU parameters - dual core - 2.4GHz frequency, running memory -2G, storage space -16G;
  • the fourth category CPU parameters - dual core - 2.4GHz frequency, running memory -4G, storage space -16G;
  • Calculating the cosine similarity between the vector and the vector of the above classification, respectively, and determining that the similarity value is greater than 0.8 (or customizing the similarity value according to specific classification precision) is the terminal type corresponding to the corresponding vector.
  • the cosine similarity in this embodiment is as follows: the characteristic parameter set of the user terminal is regarded as an n-dimensional space.
  • the vector which measures the similarity between two user terminals by calculating the angle cosine between the two vectors.
  • user terminals with similar feature parameter sets are grouped into one class, so that a list of parameters suitable for the application installed by each type of user terminal can be debugged according to its category and the external network environment, and used as a parameter list.
  • Adjusting the parameter list after detecting that a new user terminal installs the application software, by comparing the characteristic parameters of the new user terminal, determining the type of the new user terminal and configuring a corresponding tuning parameter list thereof,
  • the application software of the new user terminal is tuned so that the user can obtain a better user experience in the process of using the application software; this embodiment may be completed by a single server, or may be completed by a server group.
  • the classification of the user terminal can also be realized by the Pearson coefficient or the adjustment of the cosine similarity.
  • Pearson coefficient Also known as correlation similarity, the Peason correlation coefficient is used to measure the similarity of two user terminals. In the calculation, the vector of the characteristic parameter sets of the two user terminals is first determined, and then the correlation coefficients of the two vectors are calculated.
  • Adjusting the cosine similarity After subtracting the average of the characteristic parameter set of the user terminal from the vector in the cosine similarity to obtain the vector, the angle cosine of the two vectors is calculated to correct the different feature parameter sets of different user terminals.
  • a related function module can be implemented by a hardware processor.
  • some embodiments of the present invention provide an online tuning system for an application, including:
  • a request receiving module configured to receive an application tuning request sent by the user terminal
  • a request parsing module configured to parse an application tuning request received by the request receiving module, and determine a characteristic parameter set of the user terminal
  • a terminal type determining module configured to compare a characteristic parameter set determined by the request parsing module with each index set in a type reference system, where each index set in the type reference system corresponds to one type, and the characteristic is determined Determining a plurality of similarities of the parameter sets and the respective indicator sets, and determining a type of the user terminal based on the similarity determination result;
  • a tuning parameter sending module configured to determine, according to the type of the user terminal determined by the terminal type determining module, a tuning parameter configuration list corresponding to each type in the type reference system, to determine an adapted tuning parameter configuration file, The user terminal sends a corresponding tuning parameter configuration file.
  • the user terminal sends an application tuning request according to a predetermined period or when the application carried by the user terminal is started.
  • the request parsing module parses and sends the application from the request. Tuning a specific parameter set of the requested user terminal; the terminal type determining module further compares the determined characteristic parameter set of the user terminal with each indicator set in the known type reference system, and determines that the user terminal that sends the application tuning request belongs to After determining the terminal type of the user terminal that sends the application tuning request, refer to the tuning parameter configuration list corresponding to each type in the known type reference system, and the tuning parameter sending module adapts the terminal type.
  • the application tuning parameter configuration file is sent to the user terminal that sends the request to implement online tuning of the application it is carrying.
  • the online tuning system applied in this embodiment is a server or a server cluster, wherein Each module may be a separate server or a server cluster.
  • the interaction between the modules is represented by the interaction between the servers or server clusters corresponding to the modules, and the multiple servers or server clusters together constitute the present invention. Applied online tuning system.
  • the online tuning system 700 of the application of this embodiment includes:
  • the request receiving server or the server cluster 710 is configured to receive an application tuning request sent by the user terminal;
  • Requesting a resolution server or server cluster 720 configured to parse the application tuning request received by the request receiving server or the server cluster 710, and determining a characteristic parameter set of the user terminal;
  • the terminal type determining server or the server cluster 730 is configured to compare the characteristic parameter set determined by the request parsing server or the server cluster 720 with each indicator set in the type reference system, where each indicator set in the type reference system corresponds to Determining, in one type, a plurality of similarities between the characteristic parameter set and the respective indicator sets, and determining a type of the user terminal based on the similarity determination result;
  • the tuning parameter sending server or the server cluster 740 is configured to determine the type of the user terminal determined by the server or the server cluster 730 according to the terminal type, and refer to the tuning parameter configuration list corresponding to each type in the type reference system to determine the adaptation.
  • the tuning parameter configuration file sends a corresponding tuning parameter configuration file to the user terminal.
  • the user terminal is communicatively connected to the online tuning system 700 through the network to receive an application tuning request sent by the user terminal.
  • the plurality of modules described above may collectively form a server or cluster of servers.
  • the request receiving module and the request parsing module together form a first server or a first server cluster
  • the terminal type determining module and the tuning parameter sending module constitute a second server or a second server cluster.
  • the interaction between the above modules represents the interaction between the first server and the second server.
  • the interaction between the first server cluster and the second server cluster, the first server to the second server or the first server cluster to the second server cluster together constitute an online tuning system of the application of the present invention.
  • the terminal type determining module includes a first terminal type determining unit configured to determine a type corresponding to the indicator set associated with the similarity that is greater than the upper threshold upper limit among the plurality of similarities as The type of user terminal.
  • the first terminal type determining unit may be a server or a server cluster.
  • a terminal type determining module is configured to determine a type of a terminal associated with a feature parameter set whose multiple similarities are less than a lower threshold than the respective indicator sets. For the new type;
  • the online tuning system further includes: a type reference system update module and a tuning parameter configuration list update module;
  • the type reference system update module is configured to: when the terminal type determining module determines a new type, establish the new type in the type reference system and correspond to a feature parameter set associated with the new type New set of indicators;
  • the tuning parameter configuration list updating module is configured to: after the terminal type determining module determines a new type, create a corresponding new tuning parameter configuration file based on the new type, and the new tuning The parameter configuration file is added to the tuning parameter configuration list.
  • the type reference system update module and the tuning parameter configuration list update module may be a server or a server cluster, respectively, or may be a type reference system update module and a tuning parameter configuration list update module to form a server or a server cluster. .
  • the online tuning system 800 of the application of this embodiment includes:
  • the requesting resolution server or server cluster 820 is configured to parse the application tuning request received by the request receiving server or the server cluster 810, and determine a characteristic parameter set of the user terminal;
  • the terminal type determining server or the server cluster 830 is configured to compare the characteristic parameter set determined by the request resolution server or the server cluster 820 with each indicator set in the type reference system, where each indicator set in the type reference system corresponds to Determining, in one type, a plurality of similarities between the characteristic parameter set and the respective indicator sets, and determining a type of the user terminal based on the similarity determination result;
  • the type reference system update server or server cluster 831 is configured to establish the new type and the new one in the type reference system when the terminal type determination server or server cluster 830 determines a new type a new set of metrics corresponding to the set of characteristic parameters associated with the type;
  • the tuning parameter configuration list update server or server cluster 832 is configured to create a corresponding new tuning parameter configuration file based on the new type after the terminal type determining server or the server cluster 830 determines a new type. Add the new tuning parameter configuration file to the tuning parameter configuration list.
  • the tuning parameter sending server or the server cluster 840 is configured to determine the type of the user terminal determined by the server or the server cluster 830 according to the terminal type, and refer to the tuning parameter configuration list corresponding to each type in the type reference system to determine the adaptation.
  • the tuning parameter configuration file sends a corresponding tuning parameter configuration file to the user terminal.
  • the user terminal is communicably connected to the online tuning system 800 through the network to receive an application tuning request sent by the user terminal.
  • the classification of the terminal type is classified according to the characteristic parameters of the user terminal of the entire network in advance, and the update speed of the user terminal is fast, a new user terminal appears at any time, and the new user is followed.
  • the appearance of the characteristic parameters of the terminal when there are new characteristic parameters
  • a new terminal type is separately established, and a group of applications installed for the user terminal of the type is separately debugged.
  • the tuned parameter list of the application is configured in the configuration file of the newly created user terminal type.
  • the tuning parameter list includes at least one of: a data processing area selection parameter (local or server-side processing), a download speed parameter, a P2P/CDN selection parameter, a size of a P2P buffer buffer, and a local cache control parameter, and the present invention
  • the embodiments include, but are not limited to, the parameters listed above; by setting the data processing area selection parameters, it is possible to select whether the content of the application runtime offset calculation is implemented locally (ie, user terminal) or on the server side.
  • the online tuning system further includes a type reference system generation module, and the type reference system generation module includes:
  • a parameter set statistics unit configured to collect a characteristic parameter set of the user terminal of the entire network
  • a multi-dimensional vector establishing unit configured to establish, by the parameter set statistical unit, a characteristic parameter set of each of the user terminals as a multi-dimensional vector, where the number of dimensions of the vector is equal to the number of the characteristic parameters;
  • a reference system generating unit configured to classify the user terminal by performing similarity calculation between each of the multi-dimensional vectors established by the multi-dimensional vector establishing unit, to generate the type reference system.
  • the type reference generation module may be a server or a server cluster, respectively, wherein the parameter set statistical unit, the multi-dimensional vector establishing unit, and the reference system generating unit are respectively a server or a server cluster, and at this time, between the units
  • the interaction is represented by the interaction between the servers or server clusters corresponding to the units.
  • the parameter set statistical unit and the multi-dimensional vector establishing unit together form a first server or a first server cluster
  • the reference system generating unit constitutes a second server or a Two server clusters.
  • the interaction between the above units represents an interaction between the first server and the second server or an interaction between the first server cluster and the second server cluster.
  • the characteristic parameter includes at least one of a CPU parameter, a running memory size, a storage space size, an operating system type, an uplink network bandwidth, and a downlink network bandwidth.
  • the present invention further provides an online tuning server, where the online tuning server includes:
  • a memory for storing computer operating instructions
  • a processor configured to execute the computer operating instructions of the memory storage to perform:
  • each indicator set in the type reference frame corresponds to one type, and determining that the characteristic parameter set is similar to multiple of the respective indicator sets Degree, determining a type of the user terminal based on the similarity determination result;
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) including computer usable program code.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing, thereby
  • the instructions executed on or on other programmable devices provide steps for implementing the functions specified in one or more blocks of the flowchart or in a flow or block of the flowchart.

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Abstract

本发明提供了一种应用的在线调优方法，包括：接收用户终端发送的应用调优请求；解析应用调优请求，确定用户终端的特性参数集；将所述特性参数集与类型参考系中的各个指标集进行对比，其中类型参考系中每个指标集对应于一个类型，确定特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定用户终端的类型；根据所确定的用户终端的类型，参照与类型参考系中各个类型所对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送调优参数配置文件；相应的本发明还提供一种应用的在线调优系统；本发明实施例提供的应用的在线调优方法及系统，能够解决现有技术中应用软件升级不可能兼顾当下所有用户终端的配置参数的技术问题。

Description

应用的在线调优方法及系统 技术领域
本发明涉及互联网技术领域，特别涉及一种应用的在线调优方法及系统。
背景技术
随着互联网的发展，视频领域的P2P业务也在迅猛的增长，为了给用户提供更好的应用体验，需要不断的更新升级应用软件。
现有技术中，应用软件发布者需要定期或者不定期地提供新版本的应用软件的安装包，以实现应用软件旧版本软件的功能升级。现有的应用软件的升级过程一般包括：软件发布者通过各个推广渠道发布新版本软件的安装包，用户可从各个推广渠道下载新版本软件的安装包，在用户终端安装该新版本软件的安装包，以替换用户终端中的旧版本的应用软件，完成升级，实现用户终端中的软件功能的升级。
然而，上述现有方案中，每次进行应用软件升级，都只是为了功能的扩展或者bug的修复，由于每一次应用软件升级不可能兼顾当下所有的用户终端的配置参数，所以升级后的应用软件只是更加适合于当下最流行的几款用户终端的运行，而一些配置参数比较新的用户终端，或者一些老旧的用户在安装该应用软件后则不能获得更好的用户体验。
发明内容
本发明的实施例提供一种应用的在线调优方法及系统，用于解决现有技术中应用软件升级不可能兼顾当下所有的用户终端的配置参数的技术问题。
根据本发明的一个方面，提供了一种应用的在线调优方法，包括：
接收用户终端发送的应用调优请求；
解析所述应用调优请求，确定所述用户终端的特性参数集；
将所述特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度计算结果，确定所述用户终端的类型；
根据所确定的用户终端的类型，参照与所述类型参考系中各个类型所对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送所述调优参数配置文件。
另一方面，本发明的实施例还提供一种应用的在线调优系统，包括：
请求接收模块，用于接收用户终端发送的应用调优请求；
请求解析模块，用于解析所述应用调优请求，确定所述用户终端的特性参数集；
终端类型判定模块，用于将所述特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定所述用户终端的类型；
调优参数发送模块，用于根据所确定的用户终端的类型，参照与所述类型参考系中各个类型所对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送所述调优参数配置文件。
本发明实施例提供的应用在线调优方法及系统，能够针对具有不同特性参数(配置参数)的面对用户终端，为其安装的应用用于更加适合其运行的调优参数列表，从而保证了运行与不同用户终端的应用具有更加合适的运行参数，以保证服务质量，提升用户体验。
附图说明
为了更清楚地说明本发明实施例的技术方案，下面将对实施例描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本发明的应用的在线调优方法的一实施例的流程图；
图2为本发明的应用的在线调优方法的另一实施例的流程图；
图3为本发明的应用的在线调优方法的又一实施例的流程图；
图4为本发明的应用的在线调优方法的再一实施例的流程图；
图5为本发明的应用的在线调优系统的一实施例的示意图；
图6为本发明中的终端类型判定模块的一实施例的示意图；
图7为本发明的应用的在线调优系统的另一实施例的原理图；
图8为本发明的应用的在线调优系统的又一实施例的原理图。
具体实施例
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。
本发明可用于众多通用或专用的计算系统环境或配置中。例如：个人计算机、服务器计算机、手持设备或便携式设备、平板型设备、多处理器系统、基于微处理器的系统、置顶盒、可编程的消费电子设备、网络PC、小型计算 机、大型计算机、包括以上任何系统或设备的分布式计算环境等等。
本发明可以在由计算机执行的计算机可执行指令的一般上下文中描述，例如程序模块。一般地，程序模块包括执行特定任务或实现特定抽象数据类型的例程、程序、对象、组件、数据结构等等。也可以在分布式计算环境中实践本发明，在这些分布式计算环境中，由通过通信网络而被连接的远程处理设备来执行任务。在分布式计算环境中，程序模块可以位于包括存储设备在内的本地和远程计算机存储介质中。
最后，还需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”，不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
如图1所示，本发明的一实施例的应用的在线调优方法，包括：
S11、服务器接收用户终端发送的应用调优请求；
S12、服务器解析所述应用调优请求，确定所述用户终端的特性参数集；
S13、服务器将所述特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定所述用户终端的类型；
S14、服务器根据所确定的用户终端的类型，参照与所述类型参考系中各个类型所对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送所述调优参数配置文件。
本实施例中，用户终端按照预定的周期或者在用户终端所搭载的应用启动时，发送应用调优请求，服务器接收到应用调优请求后从请求中解析出发送该应用调优请求的用户终端的特定参数集；再根据确定的用户终端的特性参数与已知的类型参考系中的各个指标集(每个指标集对应于一个类型)进行对比，确定发送应用调优请求的用户终端所属的终端类型；在确定发送调优请求的用户终端的终端类型后，参照与已知的类型参考系中各个类型所对应的调优参数配置列表，将该终端类型适配的应用调优参数配置文件发送至发送请求的用户终端，实现其搭载的应用的在线调优。
在本实施例中，用户终端为一种智能终端，且该智能终端可以是手机(例如，乐视手机)，也可以是便携式、袖珍式、手持式、计算机内置的或者车载的移动装置，也可以是PC(personal computer，个人计算机)、平板电脑等，还可以是能够连接到互联网的智能电视(例如，乐视超级电视)、机顶盒等，因此智能终端可以实现待识别目标的自然信息的采集。
在一些本发明的一些实施例中，在确定所述特性参数集与所述各个指标集的多个相似度之后，将与所述多个相似度中大于阈值上限最高的相似度相关联的指标集所对应的类型确定为所述用户终端的类型。
如图2所示，在一些实施例中，服务器确定所述特性参数集与所述各个指标集的多个相似度，并确定用户终端的类型包括：
S21、服务器将用户终端的特性参数集生成向量；
S22、服务器确定特性参数集与各类型的用户终端对应的特性参数集生成的向量之间的相似度；
S23、服务器确定相似度超过第一阈值的类型为用户终端的终端类型。
本实施例中通过根据用户终端的特性参数集生成的向量与已知的终端类型的特性参数集生成的向量之间的相似度来判断发送应用调优请求的用户终 端的类型。本实施例中具体的采用余弦相似度算法来计算发送应用调优请求的用户终端与已知的终端类型之间的相似度的，当相似度值超过第一阈值时则判定发送应用调优请求的用户终端为当前的已知的终端类型；其中第一阈值可以根据对分类精度的需求调整其大小，一般取值为0.8，即当相识度值超过0.8时，则确定该发送应用调优请求的用户终端为当前的已知的终端类型。
由于终端类型的分类是预先根据全网的用户终端的特性参数进行分类的，并且用户终端的更新迭代的速度之快，随时都会有新的用户终端的出现，随之而来的就是新的用户终端的特性参数的出现，当出现具有新的特性参数的用户终端时，就不能够根据预先统计的终端类型中找到与之匹配的终端类型，这时就单独建立一种新的终端类型，并单独针对该类型的用户终端所安装的应用调试一组应用的调优参数列表出来配置到新建的用户终端类型的配置文件中，以备后续再次出现该种类型的用户终端时可以快速确定其类型并为其分配相应的调优参数列表。
调优参数列表至少包括：数据处理区选择参数(本地or服务器端处理)、下载速度参数、P2P/CDN选择参数、P2P的buffer缓存区的大小、本地缓存控制参数中的至少一种，本发明的实施例包括但并不限于上述所列参数；通过设置数据处理区选择参数，可以选择应用运行时偏计算的内容是在本地(即用户终端)实现还是在服务器端实现。
例如，当用户终端的CPU参数比较高时则可以通过该参数的设置把偏计算的内容放在用户终端上实现，以减轻服务器的负担，便于服务器可以更好的为其它用户终端提供更优质的服务；当CPU参数比较低时则可以通过该参数的设置把偏计算的内容放在服务器上实现，以保证对该用户的服务质量。
当特性参数中的上行下载带宽、下行下载带宽比较大时可以通过下载速度参数为该用户终端配置较大的下载速度；当用户为P2P用户或者CDN用户，并且用户终端的内存比较大时，可以通过P2P/CDN选择参数、P2P的buffer 缓存区的大小为用户选择P2P服务或者CDN服务，并为其分配适当大小的P2P的buffer缓存区。
如图3所示，在一些本发明的一些实施例中，在服务器确定所述特性参数集与所述各个指标集的多个相似度之后，
S31、当所述特性参数集与所述各个指标集的多个相似度均小于阈值下限时，服务器将所述用户终端确定为新的类型，在所述类型参考系中建立与所述特性参数集相应的新的指标集和所述新的类型；
S32、服务器基于所述新的类型，创建与之相应的新的调优参数配置文件；
S33、服务器将所述新的调优参数配置文件添加至调优参数配置列表。
本实施例中通过针对新的用户终端建立新的指标集和新的类型，并配置新的调优参数配置文件，实现了对用户终端类型的实时的监测，缩短了对服务质量的反应时间(能够及时的发现新类型的用户终端，并为其调试最优的应用运行参数，并进行推送)，保证对所有类型(已有类型或者新出类型的用户终端)服务质量，提升了用户质量。
如图4所示，在一些实施例中，类型参考系通过以下步骤生成：
S41、服务器统计全网用户终端的特性参数集；
S42、服务器把各用户终端的特性参数集建立为一个多维向量，向量的维度数等于特性参数的个数；
S43、服务器通过在各所述多维向量间进行相似度计算，对所述用户终端进行分类，生成所述类型参考系。
本实施例中，服务器通过统计全网用户终端的特性参数集，并将用户终端的特性参数集建立为多维向量，再通过计算各多维向量之间的余弦相似度的方法将用户终端进行分类；通过相似度计算的方法实现了两个终端之间的相似性的量化，使得对用户终端的分类更加科学准确。
在上述任一实施例中，特性参数至少包括CPU参数、运行内存大小、存储空间大小、屏幕分辨率、摄像头像素、操作系统类型、上行网络带宽和下行网络带宽中的一种，但不限于上述所列的几种参数，开发人员可以根据自己的需求或者各种参数的重要性自行进行调整。
例如，当只考虑CPU参数、运行内存大小、存储空间大小三个参数时，可以对用户终端进行如下分类：
第一类、CPU参数-8核-1.8GHz主频、运行内存-2G、存储空间-16G；
第二类、CPU参数-4核-1.8GHz主频、运行内存-2G、存储空间-16G；
第三类、CPU参数-双核-2.4GHz主频、运行内存-2G、存储空间-16G；
第四类、CPU参数-双核-2.4GHz主频、运行内存-4G、存储空间-16G；
……
针对上述分类分别形成以下向量：
第一向量、[8、1.8、2、16]；
第二向量、[4、1.8、2、16]；
第三向量、[2、2.4、2、16]；
第四向量、[2、2.4、4、16]；
……
当新的用户终端上传的特性参数为：CPU参数-8核-1.8GHz主频、运行内存-2G、存储空间-32G时，建立特性参数的向量：[8、1.8、2、32]
分别计算该向量与上述分类的向量之间的余弦相似度，并确定相似度值大于0.8(或者根据具体的分类精度进行自定义该相似度值)的为相应向量所对应的终端类型。
本实施例中余弦相似性为：把用户终端的特性参数集看作是n维空间上 的向量，通过计算两个向量之间的夹角余弦来度量两个用户终端之间的相似性。
通过相似度算法将特性参数集相近的用户终端聚为一类，从而可以根据其类别以及外部的网络环境来为每一类用户终端调试出一组适合于其安装的应用的参数列表，用作调优参数列表，当检测到有新的用户终端安装该应用软件后，通过比较该新的用户终端的特性参数，判断该新的用户终端所属类型并为其配置相应的调优参数列表，实现新的用户终端的应用软件的调优，以便用户在使用该应用软件的过程中获得更好的用户体验；本实施例可以有单个服务器来完成，也可以有一个服务器群组来完成。
上述实施例中还可以通过皮尔森系数或调整余弦相似性来实现对用户终端的分类。
皮尔森系数：又称相关相似性，通过Peason(皮尔森)相关系数来度量两个用户终端的相似性。计算时，首先确定两个用户终端的特性参数集的向量，然后计算这两个向量的相关系数。
调整余弦相似性：将余弦相似性中的向量，减去用户终端的特性参数集的平均值得到向量后，再计算两向量的夹角余弦以修正不同用户终端特征参数集不同的问题。
本发明实施例中可以通过硬件处理器(hardware processor)来实现相关功能模块。
需要说明的是，对于前述的各方法实施例，为了简单描述，故将其都表述为一系列的动作合并，但是本领域技术人员应该知悉，本发明并不受所描述的动作顺序的限制，因为依据本发明，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作和模块并不一定是本发明所必须的。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
如图5所示，另一方面本发明的一些实施例还提供一种应用的在线调优系统，包括：
请求接收模块，用于接收用户终端发送的应用调优请求；
请求解析模块，用于解析所述请求接收模块接收的应用调优请求，确定所述用户终端的特性参数集；
终端类型判定模块，用于将所述请求解析模块确定的特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定所述用户终端的类型；
调优参数发送模块，用于根据终端类型判定模块所确定的用户终端的类型，参照与所述类型参考系中各个类型对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送相应的调优参数配置文件。
本实施例中，用户终端按照预定的周期或者在用户终端所搭载的应用启动时，发送应用调优请求，请求接收模块接收到应用调优请求后，请求解析模块从请求中解析出发送该应用调优请求的用户终端的特定参数集；终端类型判定模块再根据确定的用户终端的特性参数集与已知的类型参考系中的各个指标集进行对比，确定发送应用调优请求的用户终端所属的终端类型；在确定发送应用调优请求的用户终端的终端类型后，参照与已知的类型参考系中各个类型所对应的调优参数配置列表，调优参数发送模块将该终端类型适配的应用调优参数配置文件发送至发送请求的用户终端，实现其搭载的应用的在线调优。
在本实施例中应用的在线调优系统为一个服务器或者服务器集群，其中 每个模块可以是单独的服务器或者服务器集群，此时，上述模块之间的交互表现为各模块所对应的服务器或者服务器集群之间的交互，所述多个服务器或服务器集群共同构成本发明的应用的在线调优系统。
如图7所示，具体地，本实施例的应用的在线调优系统700包括：
请求接收服务器或者服务器集群710，用于接收用户终端发送的应用调优请求；
请求解析服务器或者服务器集群720，用于解析所述请求接收服务器或者服务器集群710接收的应用调优请求，确定所述用户终端的特性参数集；
终端类型判定服务器或者服务器集群730，用于将所述请求解析服务器或者服务器集群720确定的特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定所述用户终端的类型；
调优参数发送服务器或者服务器集群740，用于根据终端类型判定服务器或者服务器集群730所确定的用户终端的类型，参照与所述类型参考系中各个类型对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送相应的调优参数配置文件。
在本实施例中，用户终端通过网络与在线调优系统700通信连接，以接收用户终端发送的应用调优请求。
在一种替代实施例中，可以是上述多个模块中的几个模块共同组成一个服务器或者服务器集群。例如：请求接收模块和请求解析模块共同组成第一服务器或者第一服务器集群，终端类型判定模块和调优参数发送模块构成第二服务器或者第二服务器集群。
此时，上述模块之间的交互表现为第一服务器和第二服务器之间的交互 或者第一服务器集群和第二服务器集群之间的交互，所述第一服务器至第二服务器或第一服务器集群至第二服务器集群共同构成本发明的应用的在线调优系统。
在一些本发明的一些实施例中，终端类型判定模块包括第一终端类型确定单元，其用于将与多个相似度中大于阈值上限最高的相似度相关联的指标集所对应的类型确定为用户终端的类型。
在本实施例中，第一终端类型确定单元可以为一个服务器或者服务器集群。
如图6所示，在本发明的一些实施例中，终端类型判定模块用于将与所述各个指标集相比的多个相似度均小于阈值下限的特性参数集所关联的终端的类型确定为新的类型；
所述在线调优系统还包括：类型参考系更新模块和调优参数配置列表更新模块；
所述类型参考系更新模块用于在所述终端类型判定模块确定出新的类型时，在所述类型参考系中建立所述新的类型以及与所述新的类型相关联的特性参数集对应的新的指标集；
所述调优参数配置列表更新模块用于在所述终端类型判定模块确定出新的类型后，基于所述新的类型，创建相应的新的调优参数配置文件，将所述新的调优参数配置文件添加至调优参数配置列表。
在本实施例中，类型参考系更新模块和调优参数配置列表更新模块可以分别为服务器或者服务器集群，或者可以是类型参考系更新模块和调优参数配置列表更新模块共同构成一个服务器或者服务器集群。
如图8所示，具体地，本实施例的应用的在线调优系统800包括：
请求接收服务器或者服务器集群810，用于接收用户终端发送的应用调 优请求；
请求解析服务器或者服务器集群820，用于解析所述请求接收服务器或者服务器集群810接收的应用调优请求，确定所述用户终端的特性参数集；
终端类型判定服务器或者服务器集群830，用于将所述请求解析服务器或者服务器集群820确定的特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定所述用户终端的类型；
所述类型参考系更新服务器或者服务器集群831用于在所述终端类型判定服务器或者服务器集群830确定出新的类型时，在所述类型参考系中建立所述新的类型以及与所述新的类型相关联的特性参数集对应的新的指标集；
所述调优参数配置列表更新服务器或者服务器集群832用于在所述终端类型判定服务器或者服务器集群830确定出新的类型后，基于所述新的类型，创建相应的新的调优参数配置文件，将所述新的调优参数配置文件添加至调优参数配置列表。
调优参数发送服务器或者服务器集群840，用于根据终端类型判定服务器或者服务器集群830所确定的用户终端的类型，参照与所述类型参考系中各个类型对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送相应的调优参数配置文件。
在本实施例中，用户终端通过网络与在线调优系统800通信连接，以接收用户终端发送的应用调优请求。
由于终端类型的分类是预先根据全网的用户终端的特性参数进行分类的，并且用户终端的更新迭代的速度之快，随时都会有新的用户终端的出现，随之而来的就是新的用户终端的特性参数的出现，当出现具有新的特性参数 的用户终端时，就不能够根据预先统计的终端类型中找到与之匹配的终端类型，这时就单独建立一种新的终端类型，并单独针对该类型的用户终端所安装的应用调试一组应用的调优参数列表出来配置到新建的用户终端类型的配置文件中，以备后续再次出现该种类型的用户终端时可以快速确定其类型并为其分配相应的调优参数列表。
调优参数列表至少包括：数据处理区选择参数(本地or服务器端处理)、下载速度参数、P2P/CDN选择参数、P2P的buffer缓存区的大小、本地缓存控制参数中的至少一种，本发明的实施例包括但并不限于上述所列参数；通过设置数据处理区选择参数，可以选择应用运行时偏计算的内容是在本地(即用户终端)实现还是在服务器端实现。
在一些实施例中，所述在线调优系统还包括类型参考系生成模块，类型参考系生成模块包括：
参数集统计单元，用于统计全网用户终端的特性参数集；
多维向量建立单元，用于把参数集统计单元统计的各所述用户终端的特性参数集建立为一个多维向量，向量的维度数等于所述特性参数的个数；
参考系生成单元，用于通过在多维向量建立单元所建立的各所述多维向量间进行相似度计算，对所述用户终端进行分类，生成所述类型参考系。
在本实施例中，类型参考系生成模块可以分别为服务器或者服务器集群，其中参数集统计单元、多维向量建立单元和参考系生成单元分别为一个服务器或者服务器集群，这时，各单元之间的交互表现为各单元所对应的服务器或者服务器集群之间的交互。
在一种替代实施例中，可以是上述多个单元中的几个单元共同组成一个服务器或者服务器集群。例如：参数集统计单元和多维向量建立单元共同组成第一服务器或者第一服务器集群，参考系生成单元构成第二服务器或者第 二服务器集群。
此时，上述单元之间的交互表现为第一服务器和第二服务器之间的交互或者第一服务器集群和第二服务器集群之间的交互。
在上述任一实施例的应用的在线调优系统中，特性参数至少包括CPU参数、运行内存大小、存储空间大小、操作系统类型、上行网络带宽和下行网络带宽中的一种。
另一方面，本发明还提供一种在线调优服务器，该在线调优服务器包括：
存储器，用于存储计算机操作指令；
处理器，用于执行所述存储器存储的计算机操作指令，以执行：
接收用户终端发送的应用调优请求；
解析所述应用调优请求，确定所述用户终端的特性参数集；
将所述特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定所述用户终端的类型；
根据所确定的用户终端的类型，参照与所述类型参考系中各个类型所对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送所述调优参数配置文件。
以上所描述的方法实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
通过以上的实施例的描述，本领域的技术人员可以清楚地了解到各实施 例可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件。基于这样的理解，上述技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行各个实施例或者实施例的某些部分所述的方法。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机 或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
最后应说明的是：以上实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的精神和范围。

Claims (10)

  1. 一种应用的在线调优方法，包括：
    接收用户终端发送的应用调优请求；
    解析所述应用调优请求，确定所述用户终端的特性参数集；
    将所述特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度确定结果，确定所述用户终端的类型；
    根据所确定的用户终端的类型，参照与所述类型参考系中各个类型所对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送所述调优参数配置文件。
  2. 根据权利要求1所述的应用的在线调优方法，其特征在于，在确定所述特性参数集与所述各个指标集的多个相似度之后，
    当所述特性参数集与所述各个指标集的多个相似度均小于阈值下限时，将所述用户终端确定为新的类型，在所述类型参考系中建立与所述特性参数集相应的新的指标集和所述新的类型；
    基于所述新的类型，创建相应的新的调优参数配置文件；
    将所述新的调优参数配置文件添加至调优参数配置列表。
  3. 根据权利要求1或2所述的应用的在线调优方法，其特征在于，在确定所述特性参数集与所述各个指标集的多个相似度之后，
    将与所述多个相似度中大于阈值上限最高的相似度相关联的指标集所对 应的类型确定为所述用户终端的类型。
  4. 根据权利要求1-3任一项所述的应用的在线调优方法，其特征在于，所述类型参考系通过以下步骤生成：
    统计全网用户终端的特性参数集；
    把各所述用户终端的特性参数集建立为一个多维向量，向量的维度数等于所述特性参数的个数；
    通过在各所述多维向量间进行相似度计算，对所述用户终端进行分类，生成所述类型参考系。
  5. 根据权利要求1-3任一项所述的应用的在线调优方法，其特征在于，所述特性参数至少包括CPU参数、运行内存大小、存储空间大小、操作系统类型、上行网络带宽和下行网络带宽中的一种。
  6. 一种应用的在线调优系统，包括：
    请求接收模块，用于接收用户终端发送的应用调优请求；
    请求解析模块，用于解析所述应用调优请求，确定所述用户终端的特性参数集；
    终端类型判定模块，用于将所述特性参数集与类型参考系中的各个指标集进行对比，其中所述类型参考系中每个指标集对应于一个类型，确定所述特性参数集与所述各个指标集的多个相似度，基于相似度计算结果，确定所述用户终端的类型；
    调优参数发送模块，用于根据所确定的用户终端的类型，参照与所述类 型参考系中各个类型所对应的调优参数配置列表，确定适配的调优参数配置文件，向用户终端发送所述调优参数配置文件。
  7. 根据权利要求6所述的应用的在线调优系统，其特征在于，所述终端类型判定模块用于将与所述各个指标集相比的多个相似度均小于阈值下限的特性参数集所关联的终端的类型确定为新的类型；
    所述在线调优系统包括：类型参考系更新模块和调优参数配置列表更新模块，
    所述类型参考系更新模块用于在所述终端类型判定模块确定出新的类型时，在所述类型参考系中建立所述新的类型以及与所述新的类型相关联的特性参数集对应的新的指标集；
    所述调优参数配置列表更新模块用于在所述终端类型判定模块确定出新的类型后，基于所述新的类型，创建相应的新的调优参数配置文件，将所述新的调优参数配置文件添加至调优参数配置列表。
  8. 根据权利要求6或7所述的应用的在线调优系统，其特征在于，所述终端类型判定模块用于将与所述多个相似度中大于阈值上限最高的相似度相关联的指标集所对应的类型确定为所述用户终端的类型。
  9. 根据权利要求6-8任一项所述的应用的在线调优系统，其特征在于，还包括类型参考系生成模块，用于统计全网用户终端的特性参数集；用于把各所述用户终端的特性参数集建立为一个多维向量，向量的维度数等于所述特性参数的个数；用于通过在各所述多维向量间进行相似度计算，对所述用户终端进行分类，生成所述类型参考系。
  10. 根据权利要求6-8任一项所述的应用的在线调优系统，其特征在于，所述特性参数至少包括CPU参数、运行内存大小、存储空间大小、操作系统类型、上行网络带宽和下行网络带宽中的一种。
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