CN117726147B - Adaptation-based server management method, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides a server management method based on adaptation degree, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a plurality of user influence parameters and corresponding user influence parameter standard values of each event execution server in a server management time period; determining the adaptation degree of each event execution server in the server management time period; if the adaptation degree is greater than or equal to a preset adaptation degree threshold, determining the corresponding event execution server as a second event execution server; otherwise, the corresponding event execution server is determined to be the first event execution server. According to the method and the system, the event execution server identifications corresponding to each second event execution server are arranged and displayed according to the descending order of the adaptation degree, and the first data information is sent to the first event execution server so as to warn the first event execution server to improve the service quality, and the quality management of each event execution server by the taxi taking platform is facilitated.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a server management method based on adaptation, an electronic device, and a storage medium.
Background
The data sources of various service providers are aggregated on the taxi taking platform, the service providers provide taxi taking services according to reservation sheets and real-time sheets, but different service providers have different quantity of the fleet of different cities, the service quality of each service provider is also different, the display sequence among the various service providers on the existing taxi taking platform is only ordered according to the price, and the taxi taking platform cannot directly acquire the service quality of each service provider, so that the management of different service providers is not facilitated.
Disclosure of Invention
Aiming at the technical problems, the invention adopts the following technical scheme:
The server management method based on the adaptation degree is applied to a server management system, wherein the server management system is in communication connection with a plurality of event execution servers, and each event execution server is correspondingly provided with a unique event execution server identifier;
The server management method based on the adaptation degree comprises the following steps:
Step S100, responding to the received server management request, and acquiring a server management time period included in the server management request; the server management time period is a time period for performing statistical management on each event execution server;
Step S200, acquiring a plurality of operation behaviors executed by each event execution server in a server management time period;
Step S300, if any operation behavior executed by the event execution server in the server management time period exists in a preset first operation behavior list, determining the event execution server as a first event execution server, and executing step S900; otherwise, executing step S400;
Step S400, acquiring a plurality of user influence parameters of each event execution server in a server management time period;
step S500, determining a user influence parameter standard value of each user according to the historical evaluation times of the user corresponding to each user influence parameter;
Step S600, determining the adaptation degree of each event execution server in the server management time period according to the user influence parameters of each event execution server and the user influence parameter standard values corresponding to the user influence parameters;
Step S700, if the adaptation degree of the event execution server in the server management time period is greater than or equal to a preset adaptation degree threshold, determining the event execution server as a second event execution server; otherwise, determining the event execution server as a first event execution server;
Step S800, according to the descending order of the adaptation degree, the event execution server identifiers corresponding to each second event execution server are arranged and displayed;
step S900, the first data information is sent to the first event execution server.
In an exemplary embodiment of the present application, step S400 includes:
Step S410, obtaining a plurality of user description semantic data received by each event execution server in a server management period, to obtain a user description semantic data list set D=(D1,D2,...,Di,...,Dn);Di=(Di1,Di2,...,Die,...,Dif(i));, where i=1, 2. n is the number of event execution servers; d i describes a semantic data list for the user received by the ith event execution server in the server management time period; e=1, 2, f (i); f (i) describing the amount of semantic data for the user received by the ith event execution server during the server management period; d ie describes semantic data for the e-th user received by the i-th event execution server in the server management time period;
Step S420, traversing D i, and acquiring the number R ie of the preset first description marks included in D ie and the number T ie of the preset second description marks included in D ie; the first description identifier represents a positive correlation description evaluation performed on the event execution server by the user; the second description identifier represents negative correlation description evaluation performed on the event execution server by the user;
Step S430, determining a user influence parameter F ie=Rie/R0-Die/D0 corresponding to the D ie; wherein, R 0 is the number of the first description marks in the preset first description mark list; d 0 is the number of second description tags in the preset second description tag list.
In an exemplary embodiment of the present application, step S500 includes:
Step S510, performing deduplication on the user identifier corresponding to the D i1,Di2,...,Die,...,Dif(i) to obtain a plurality of target user identifiers corresponding to the ith event execution server;
Step S520, obtaining the historical evaluation times of the users corresponding to each target user identifier corresponding to the ith event execution server, and obtaining a historical evaluation times set L i=(Li1,Li2,...,Lid,...,Liq(i)); wherein d=1, 2,. -%, q (i); q (i) is the number of target user identifiers corresponding to the ith event execution server; l id is the historical evaluation times of the user corresponding to the d target user identification corresponding to the i-th event execution server;
Step S530, if L id＜L0, determining a user influence parameter standard value of a user corresponding to L id as L 01; otherwise, determining a user influence parameter standard value of the user corresponding to the L id as L 02; wherein L 0 is a preset historical evaluation frequency threshold; l 02＜L01 is more than 0 and less than 1.
In an exemplary embodiment of the present application, step S600 includes:
Step S601, determining the adaptation degree Z i=∑f(i) e=1(Fie×Mie of the ith event execution server in the server management time period; wherein M ie is a user influence parameter standard value of the user corresponding to F ie.
In an exemplary embodiment of the present application, step S600 includes:
step S610, acquiring event influence parameters of each event execution server in a server management time period;
Step S620, determining event influence parameter standard values according to the server management place identifiers included in the server management requests;
Step S630, determining the adaptation degree of each event execution server in the server management time period according to the event influence parameter, the event influence parameter standard value, the user influence parameter and the user influence parameter standard value of each event execution server.
In an exemplary embodiment of the present application, step S610 includes:
Step S611, obtaining the number of event execution requests received by each event execution server in the server management period, to obtain an event execution request receiving number set a= (a 1,A2,...,Ai,...,An); wherein i=1, 2, n; n is the number of event execution servers; a i is the number of event execution requests received by the ith event execution server in the server management time period;
Step S612, obtaining the number of events corresponding to the event execution requests completed by each event execution server in the server management time period, to obtain an event execution request completion number set b= (B 1,B2,...,Bi,...,Bn); b i is the number of events corresponding to the event execution request completed by the ith event execution server in the server management time period;
step S613, determining an event influencing parameter C i=Bi/Ai of the ith event execution server in the server management time period.
In an exemplary embodiment of the present application, step S620 includes:
Step S621, a plurality of target event execution place identifiers corresponding to each event execution server are obtained, and a target event execution place identifier list set E=(E1,E2,...,Ei,...,En);Ei=(Ei1,Ei2,...,Eih,...,Eij(i)); is obtained, wherein E i is a target event execution place identifier list corresponding to the ith event execution server; h=1, 2,., j (i); j (i) is the number of target event execution place identifiers corresponding to the ith event execution server; e ih is the h target event execution location identifier corresponding to the i-th event execution server;
Step S622, if the server management location identifier included in the server management request is located in E i, determining an event impact parameter standard value K i=k1 of the ith event execution server; otherwise, determining an event influence parameter standard value K i=k2 of the ith event execution server; wherein k 1/2≤k2≤k1; and k 1 is more than or equal to 1.
In an exemplary embodiment of the present application, step S630 includes:
Step S631, determining the adaptation degree Z i=Ci×Ki+∑f(i) e=1(Fie×Mie of the ith event execution server in the server management time period); wherein M ie is a user influence parameter standard value of the user corresponding to F ie.
According to one aspect of the present application, there is provided a non-transitory computer readable storage medium having stored therein at least one instruction or at least one program loaded and executed by a processor to implement the foregoing adaptation-based server management method.
According to one aspect of the present application, there is provided an electronic device comprising a processor and the aforementioned non-transitory computer-readable storage medium.
The invention has at least the following beneficial effects:
The method comprises the steps of determining whether an event execution server is determined to be a first event execution server or not by acquiring a plurality of operation behaviors of each event execution server in a server management time period, acquiring a plurality of user influence parameters of each event execution server in the server management time period if the event execution server is not determined to be the first event execution server, determining a user influence parameter standard value of each user according to historical evaluation times of users corresponding to each user influence parameter, determining the adaptation degree of each event execution server in the server management time period according to the user influence parameters of each event execution server and the user influence parameter standard value corresponding to the user influence parameter, and determining the event execution server as a second event execution server if the adaptation degree of the event execution server in the server management time period is greater than or equal to a preset adaptation degree threshold value; otherwise, determining the event execution server as a first event execution server, wherein the first event execution server represents an event execution server with poor service quality, the second event execution server represents an event execution server with good service quality, the event execution server identifications corresponding to each second event execution server are arranged and displayed according to the descending order of the adaptation degree, and first data information is sent to the first event execution server so as to warn the first event execution server to improve the service quality, and the taxi taking platform is convenient for quality management of each event execution server.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a server management method based on adaptation degree according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
A server management method based on adaptation degree is applied to a server management system, wherein the server management system is in communication connection with a plurality of event execution servers, and each event execution server is correspondingly provided with a unique event execution server identifier.
The server management system is a server for determining the adaptation degree of a plurality of event execution servers, and in particular, the server management system may be a taxi taking platform.
The event execution server is a server needing to determine the adaptation degree, specifically, the event execution server may be an aggregated service provider on the taxi taking platform, and the adaptation degree may be a service quality parameter of each service provider on the taxi taking platform.
As shown in fig. 1, the server management method based on the adaptation degree according to the present application includes the following steps:
Step S100, responding to the received server management request, and acquiring a server management time period included in the server management request; the server management time period is a time period for performing statistical management on each event execution server;
Step S200, acquiring a plurality of operation behaviors executed by each event execution server in a server management time period;
Step S300, if any operation behavior executed by the event execution server in the server management time period exists in a preset first operation behavior list, determining the event execution server as a first event execution server, and executing step S900; otherwise, executing step S400;
Step S400, acquiring a plurality of user influence parameters of each event execution server in a server management time period;
the user influence parameters are determined according to description semantic data of the user on the event execution server in the server management time period, and the description semantic data corresponding to the user influence parameters can be evaluation of the user on the service provider.
Further, step S400 includes:
Step S410, obtaining a plurality of user description semantic data received by each event execution server in a server management period, to obtain a user description semantic data list set D=(D1,D2,...,Di,...,Dn);Di=(Di1,Di2,...,Die,...,Dif(i));, where i=1, 2. n is the number of event execution servers; d i describes a semantic data list for the user received by the ith event execution server in the server management time period; e=1, 2, f (i); f (i) describing the amount of semantic data for the user received by the ith event execution server during the server management period; d ie describes semantic data for the e-th user received by the i-th event execution server in the server management time period;
Step S420, traversing D i, and acquiring the number R ie of the preset first description marks included in D ie and the number T ie of the preset second description marks included in D ie; the first description identifier represents a positive correlation description evaluation performed on the event execution server by the user; the second description identifier represents negative correlation description evaluation performed on the event execution server by the user;
the first descriptive identifier may be represented as a user's good rating identifier for the facilitator, and the second descriptive identifier may be represented as a user's bad rating identifier for the facilitator.
Since the quality of service of each service provider is to be determined, the neutral evaluation of the user is not high in referential, so that only the good evaluation and poor evaluation of the user are considered when the user influence parameter is determined in the application, and the neutral evaluation is not considered.
Step S430, determining a user influence parameter F ie=Rie/R0-Die/D0 corresponding to the D ie; wherein, R 0 is the number of the first description marks in the preset first description mark list; d 0 is the number of second description tags in the preset second description tag list.
Step S500, determining a user influence parameter standard value of each user according to the historical evaluation times of the user corresponding to each user influence parameter;
in order to further improve the accuracy of the obtained adaptation degree, the reference value of the evaluation of the user to the service provider is higher, so that the user influence parameter standard value of each user is determined according to the evaluation times of each user in the historical period, and the user influence parameter standard value can be expressed as the weight of the user influence parameter and represents the influence coefficient of the evaluation made by the user to the adaptation degree of the service provider evaluated by the user.
Further, step S500 includes:
Step S510, performing deduplication on the user identifier corresponding to the D i1,Di2,...,Die,...,Dif(i) to obtain a plurality of target user identifiers corresponding to the ith event execution server;
the target user identifier is an identifier corresponding to a user evaluating the event execution server in the server management time period.
Step S520, obtaining the historical evaluation times of the users corresponding to each target user identifier corresponding to the ith event execution server, and obtaining a historical evaluation times set L i=(Li1,Li2,...,Lid,...,Liq(i)); wherein d=1, 2,. -%, q (i); q (i) is the number of target user identifiers corresponding to the ith event execution server; l id is the historical evaluation times of the user corresponding to the d target user identification corresponding to the i-th event execution server;
Step S530, if L id＜L0, determining a user influence parameter standard value of a user corresponding to L id as L 01; otherwise, determining a user influence parameter standard value of the user corresponding to the L id as L 02; wherein L 0 is a preset historical evaluation frequency threshold; l 02＜L01 is more than 0 and less than 1.
If the historical evaluation number of times of the user is smaller than the preset evaluation number threshold value, the user is indicated to normally not actively make the evaluation, but the evaluation is performed on the event execution server at this time, which means that the service quality of the user subjected to the event execution server is better or worse, therefore, the evaluation weight (namely, the user influence parameter standard value) of the user is set to be larger than the value of the evaluation weight of the user with the historical evaluation number of times being larger than or equal to the preset evaluation number threshold value, and the evaluation reference value of the user is indicated to be higher.
Step S600, determining the adaptation degree of each event execution server in the server management time period according to the user influence parameters of each event execution server and the user influence parameter standard values corresponding to the user influence parameters;
Step S700, if the adaptation degree of the event execution server in the server management time period is greater than or equal to a preset adaptation degree threshold, determining the event execution server as a second event execution server; otherwise, determining the event execution server as a first event execution server;
The second event execution server is represented as an event execution server with the adaptation degree (service quality) meeting the preset condition, namely, a service provider with better service quality is a service provider needing to be displayed.
Step S800, according to the descending order of the adaptation degree, the event execution server identifiers corresponding to each second event execution server are arranged and displayed;
And arranging and displaying event execution server identifiers corresponding to the second event execution servers according to the adaptation degree so as to inform a user of the service quality of each service provider in the server management time period, so that the user can conveniently select the service provider and play an excitation and supervision role on the service provider.
Step S900, the first data information is sent to the first event execution server.
The first event execution server is an event execution server with the adaptation degree smaller than a preset adaptation degree threshold, namely, a service provider with poor service quality in a server management time period is not shown on a default page or a home page of application software because of low adaptation degree, and first data information is sent to the first event execution server, wherein the first data information can be prompt information so as to inform the adaptation degree of the first event execution server.
Further, the first embodiment of step S600 is:
Step S601, determining the adaptation degree Z i=∑f(i) e=1(Fie×Mie of the ith event execution server in the server management time period; wherein M ie is a user influence parameter standard value of the user corresponding to F ie.
Further, the second embodiment of step S600 is:
step S610, acquiring event influence parameters of each event execution server in a server management time period;
Wherein, step S610 includes:
Step S611, obtaining the number of event execution requests received by each event execution server in the server management period, to obtain an event execution request receiving number set a= (a 1,A2,...,Ai,...,An); wherein i=1, 2, n; n is the number of event execution servers; a i is the number of event execution requests received by the ith event execution server in the server management time period;
The event execution request is a request for indicating the corresponding event execution server to execute the event, may be an order execution request of a service provider, and the number of event execution requests received by the event execution server may be the number of orders received by the service provider.
Step S612, obtaining the number of events corresponding to the event execution requests completed by each event execution server in the server management time period, to obtain an event execution request completion number set b= (B 1,B2,...,Bi,...,Bn); b i is the number of events corresponding to the event execution request completed by the ith event execution server in the server management time period;
the number of events corresponding to the event execution request completed by the event execution server may be the number of orders completed by the facilitator.
Step S613, determining an event influencing parameter C i=Bi/Ai of the ith event execution server in the server management time period.
The event impact parameter may represent the order completion rate for each facilitator over a fitness determination period.
Because the service providers have different vehicle throwing amounts in each city, the number of throwing in big cities is possibly larger than that in small cities, or the number of throwing in tourist popular cities is possibly larger than that in other cities, the order amount (the number of event execution) of each city is also different, and corresponding standard adjustment is needed to be carried out on event influence parameters of different cities according to the user ordering amount and the vehicle throwing amount of different cities, so that the obtained adaptation degree can more accurately represent the service quality of the corresponding service providers.
Step S620, determining event influence parameter standard values according to the server management place identifiers included in the server management requests;
wherein, step S620 includes:
Step S621, a plurality of target event execution place identifiers corresponding to each event execution server are obtained, and a target event execution place identifier list set E=(E1,E2,...,Ei,...,En);Ei=(Ei1,Ei2,...,Eih,...,Eij(i)); is obtained, wherein E i is a target event execution place identifier list corresponding to the ith event execution server; h=1, 2,., j (i); j (i) is the number of target event execution place identifiers corresponding to the ith event execution server; e ih is the h target event execution location identifier corresponding to the i-th event execution server;
the target event execution location identifier is a location identifier corresponding to a geographic location with more data nodes of the event execution server.
The target event execution location identification corresponding to each event execution server is determined through the following steps:
Acquiring the number of data nodes of an ith event execution server at a geographic position corresponding to each candidate event execution place identifier, and acquiring a data node number set J i=(Ji1,Ji2,...,Jib,...,Jic of the ith event execution server; wherein b=1, 2, c; c is the number of candidate event execution place identifiers; j ib is the number of data nodes at the geographic location corresponding to the ith candidate event execution location identification by the ith event execution server;
the data node of the event execution server at the geographic position corresponding to the candidate event execution place identifier is the data node of the event execution server at the geographic position, the data node can be expressed as a delivery vehicle of a service provider at the geographic position, and the data node is used for receiving the event request and executing the corresponding event.
If J ib≥J0, determining the candidate event execution location identifier corresponding to J ib as a target event execution location identifier; wherein J 0 is a preset data node number threshold.
If the number of the data nodes of the event execution server at a certain geographic position is greater than or equal to a preset number threshold, the number of the data nodes of the event executable by the event execution server at the geographic position is larger than or equal to a preset number threshold, the data nodes are determined to be target event execution place identifiers, the geographic positions corresponding to the target event execution place identifiers are the geographic positions with more data nodes set by the event execution server, and the determination of event influence parameter standard values has reference value.
Step S622, if the server management location identifier included in the server management request is located in E i, determining an event impact parameter standard value K i=k1 of the ith event execution server; otherwise, determining an event influence parameter standard value K i=k2 of the ith event execution server; wherein k 1/2≤k2≤k1; and k 1 is more than or equal to 1.
And if the adaptation degree determines that the location identifier is the target event execution location identifier, the corresponding event influence parameter standard value is enlarged so as to improve the weight of the user evaluation of the event execution server at the geographic position corresponding to the location identifier.
Step S630, determining the adaptation degree of each event execution server in the server management time period according to the event influence parameter, the event influence parameter standard value, the user influence parameter and the user influence parameter standard value of each event execution server.
Wherein, step S630 includes:
Step S631, determining the adaptation degree Z i=Ci×Ki+∑f(i) e=1(Fie×Mie of the ith event execution server in the server management time period); wherein M ie is a user influence parameter standard value of the user corresponding to F ie.
The method comprises the steps of determining whether an event execution server is determined to be a first event execution server or not by acquiring a plurality of operation behaviors of each event execution server in a server management time period, acquiring a plurality of user influence parameters of each event execution server in the server management time period if the event execution server is not determined to be the first event execution server, determining a user influence parameter standard value of each user according to historical evaluation times of users corresponding to each user influence parameter, determining the adaptation degree of each event execution server in the server management time period according to the user influence parameters of each event execution server and the user influence parameter standard value corresponding to the user influence parameter, and determining the event execution server as a second event execution server if the adaptation degree of the event execution server in the server management time period is greater than or equal to a preset adaptation degree threshold value; otherwise, determining the event execution server as a first event execution server, wherein the first event execution server represents an event execution server with poor service quality, the second event execution server represents an event execution server with good service quality, the event execution server identifications corresponding to each second event execution server are arranged and displayed according to the descending order of the adaptation degree, and first data information is sent to the first event execution server so as to warn the first event execution server to improve the service quality, and the taxi taking platform is convenient for quality management of each event execution server.
Embodiments of the present invention also provide a computer program product comprising program code for causing an electronic device to carry out the steps of the method according to the various exemplary embodiments of the invention as described in the specification, when said program product is run on the electronic device.
Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order, or that all illustrated steps be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
Those skilled in the art will appreciate that the various aspects of the invention may be implemented as a system, method, or program product. Accordingly, aspects of the invention may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.
An electronic device according to this embodiment of the invention. The electronic device is merely an example, and should not impose any limitations on the functionality and scope of use of embodiments of the present invention.
The electronic device is in the form of a general purpose computing device. Components of an electronic device may include, but are not limited to: the at least one processor, the at least one memory, and a bus connecting the various system components, including the memory and the processor.
Wherein the memory stores program code that is executable by the processor to cause the processor to perform steps according to various exemplary embodiments of the invention described in the "exemplary methods" section of this specification.
The storage may include readable media in the form of volatile storage, such as Random Access Memory (RAM) and/or cache memory, and may further include Read Only Memory (ROM).
The storage may also include a program/utility having a set (at least one) of program modules including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
The bus may be one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.
The electronic device may also communicate with one or more external devices (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device, and/or with any device (e.g., router, modem, etc.) that enables the electronic device to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface. And, the electronic device may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through a network adapter. As shown, the network adapter communicates with other modules of the electronic device over a bus. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with an electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, a computer-readable storage medium having stored thereon a program product capable of implementing the method described above in the present specification is also provided. In some possible embodiments, the various aspects of the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the invention as described in the "exemplary methods" section of this specification, when said program product is run on the terminal device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
Furthermore, the above-described drawings are only schematic illustrations of processes included in the method according to the exemplary embodiment of the present invention, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (7)
1. The server management method based on the adaptation degree is characterized by being applied to a server management system, wherein the server management system is in communication connection with a plurality of event execution servers, and each event execution server is correspondingly provided with a unique event execution server identifier;
The method comprises the following steps:
step S100, responding to a received server management request, and acquiring a server management time period included in the server management request; the server management time period is a time period for carrying out statistics management on each event execution server;
Step 200, obtaining a plurality of operation behaviors executed by each event execution server in the server management time period;
Step S300, if any operation behavior executed by the event execution server in the server management time period exists in a preset first operation behavior list, determining the event execution server as a first event execution server, and executing step S900; otherwise, executing step S400;
Step S400, acquiring a plurality of user influence parameters of each event execution server in the server management time period; the user influence parameters are determined according to description semantic data of the user on the event execution server in a server management time period, and the description semantic data corresponding to the user influence parameters is evaluation of the user on the event execution server;
Step S500, determining a user influence parameter standard value of each user according to the historical evaluation times of the user corresponding to each user influence parameter;
Step S600, determining the adaptation degree of each event execution server in the server management time period according to the user influence parameters of each event execution server and the user influence parameter standard values corresponding to the user influence parameters; the adaptation degree is a service quality parameter of a corresponding event execution server;
step S700, if the adaptation degree of the event execution server in the server management time period is greater than or equal to a preset adaptation degree threshold, determining the event execution server as a second event execution server; otherwise, determining the event execution server as a first event execution server;
step S800, according to the descending order of the adaptation degree, arranging and displaying the event execution server identifiers corresponding to each second event execution server;
Step S900, sending first data information to the first event execution server;
wherein, the step S400 includes:
step S410, obtaining a plurality of user description semantic data received by each event execution server in the server management period, to obtain a user description semantic data list set D=(D1,D2,...,Di,...,Dn);Di=(Di1,Di2,...,Die,...,Dif(i));, where i=1, 2. n is the number of event execution servers; d i describes a semantic data list for the user received by the ith event execution server in the server management time period; e=1, 2, f (i); f (i) describing the amount of semantic data for the user received by the ith event execution server within the server management time period; d ie describes semantic data for the e-th user received by the i-th event execution server in the server management time period;
Step S420, traversing D i, and acquiring the number R ie of the preset first description marks included in D ie and the number T ie of the preset second description marks included in D ie; the first description identifier represents positive correlation description evaluation of the event execution server by a user; the second description identifier represents negative correlation description evaluation of the event execution server by the user;
Step S430, determining a user influence parameter F ie=Rie/R0-Die/D0 corresponding to the D ie; wherein, R 0 is the number of the first description marks in the preset first description mark list; d 0 is the number of second description marks in a preset second description mark list;
Wherein, the step S500 includes:
Step S510, performing deduplication on the user identifier corresponding to the D i1,Di2,...,Die,...,Dif(i) to obtain a plurality of target user identifiers corresponding to the ith event execution server;
Step S520, obtaining a historical evaluation number of times of each user corresponding to the target user identifier corresponding to the ith event execution server, thereby obtaining a historical evaluation number set L i=(Li1,Li2,...,Lid,...,Liq(i)); wherein d=1, 2,. -%, q (i); q (i) is the number of target user identifiers corresponding to the ith event execution server; l id is the historical evaluation times of the user corresponding to the d-th target user identifier corresponding to the i-th event execution server;
Step S530, if L id＜L0, determining a user influence parameter standard value of a user corresponding to L id as L 01; otherwise, determining a user influence parameter standard value of the user corresponding to the L id as L 02; wherein L 0 is a preset historical evaluation frequency threshold; l 02＜L01 is more than 0 and less than 1;
Wherein, the step S600 includes:
Step S601, determining the fitness Z i=∑f(i) e=1(Fie×Mie of the ith event execution server in the server management period; wherein M ie is a user influence parameter standard value of the user corresponding to F ie.
2. The method according to claim 1, wherein the step S600 further comprises:
step S610, acquiring event influence parameters of each event execution server in the server management time period;
Step S620, determining event influence parameter standard values according to the server management place identifiers included in the server management requests;
Step S630, determining the adaptation degree of each event execution server in the server management time period according to the event influence parameter, the event influence parameter standard value, the user influence parameter and the user influence parameter standard value of each event execution server.
3. The method according to claim 2, wherein the step S610 includes:
Step S611, obtaining the number of event execution requests received by each of the event execution servers in the server management period, to obtain an event execution request receiving number set a= (a 1,A2,...,Ai,...,An); wherein i=1, 2, n; n is the number of event execution servers; a i is the number of event execution requests received by the ith event execution server in the server management time period;
step S612, obtaining the number of events corresponding to the event execution requests completed by each event execution server in the server management time period, to obtain an event execution request completion number set b= (B 1,B2,...,Bi,...,Bn); b i is the number of events corresponding to the event execution request completed by the ith event execution server in the server management time period;
Step S613, determining an event influencing parameter C i=Bi/Ai of the ith event execution server in the server management time period.
4. A method according to claim 3, wherein said step S620 comprises:
Step S621, obtaining a plurality of target event execution location identifiers corresponding to each of the event execution servers, to obtain a target event execution location identifier list set E=(E1,E2,...,Ei,...,En);Ei=(Ei1,Ei2,...,Eih,...,Eij(i));, where E i is a target event execution location identifier list corresponding to the ith event execution server; h=1, 2,., j (i); j (i) is the number of target event execution place identifiers corresponding to the ith event execution server; e ih is the h target event execution location identifier corresponding to the i-th event execution server;
Step S622, if the server management location identifier included in the server management request is located in E i, determining an event impact parameter standard value K i=k1 of the ith event execution server; otherwise, determining an event influence parameter standard value K i=k2 of the ith event execution server; wherein k 1/2≤k2≤k1; and k 1 is more than or equal to 1.
5. The method according to claim 4, wherein the step S630 includes:
Step S631, determining the adaptation degree Z i=Ci×Ki+∑f(i) e=1(Fie×Mie of the ith event execution server in the server management time period; wherein M ie is a user influence parameter standard value of the user corresponding to F ie.
6. A non-transitory computer readable storage medium having stored therein at least one instruction or at least one program, wherein the at least one instruction or the at least one program is loaded and executed by a processor to implement the method of any one of claims 1-5.
7. An electronic device comprising a processor and the non-transitory computer-readable storage medium of claim 6.
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