CN117472555A - Computing power resource allocation method, system, device, equipment and storage medium - Google Patents
Computing power resource allocation method, system, device, equipment and storage medium Download PDFInfo
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Abstract
The disclosure provides a computing power resource allocation method, a computing power resource allocation system, computing power resource allocation device, computing power resource allocation equipment and a computing power resource allocation storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring a resource request of a target user, wherein the resource request comprises user information and user resource demand information of the target user, determining resource request characteristic data of the target user according to the user information and the user resource demand information, respectively matching the resource request characteristic data of the target user with resource request characteristic data of a plurality of historical users to obtain a plurality of matching results, and performing calculation resource allocation for the target user according to a calculation resource allocation mode corresponding to the historical user corresponding to the current matching result when the matching results meeting preset conditions exist in the plurality of matching results. The present disclosure can improve the efficiency of current computing power resource allocation.
Description
Technical Field
The disclosure relates to the field of computer technology, and in particular, to a method, a system, a device, equipment and a storage medium for distributing computing power resources.
Background
With the development of society, the demands of users for computing power are higher and higher, and with the increase of computing power demands, how to accurately distribute computing power so as to reduce redundancy of a large amount of computing power resources is a current urgent problem to be solved.
Currently, a common computing power distribution method distributes computing power to users according to computing power demands input by the users. However, the method for distributing the computing power resources also has the problems of large workload and low computing power resource distribution accuracy in the process of distributing the computing power resources.
Disclosure of Invention
The disclosure provides a method, a system, a device, equipment and a storage medium for distributing computing power resources, which at least overcome the problem that the current computing power resource distribution efficiency and accuracy are low to a certain extent.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to one aspect of the present disclosure, there is provided a computing power resource allocation method, including: acquiring a resource request of a target user, wherein the resource request comprises user information of the target user and user resource demand information;
determining resource request characteristic data of a target user according to the user information and the user resource demand information;
Matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of historical users respectively to obtain a plurality of matching results;
and under the condition that the matching results meeting the preset conditions exist in the plurality of matching results, performing computing power resource allocation for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result.
In one embodiment of the present disclosure, determining resource request characteristic data of a target user according to user information and user resource demand information includes:
determining a resource request vector of a target user according to the user information and the user resource demand information;
and determining the resource request vector of the target user as the resource request characteristic data of the target user.
In one embodiment of the present disclosure, determining a resource request vector of a target user from user information and user resource demand information includes:
classifying the user information and the user resource demand information based on a preset rule to obtain key demand characteristics and non-key demand characteristics;
coding the non-critical demand features to obtain coded non-critical demand features;
and determining the resource request vector of the target user according to the key demand characteristics and the coded non-key demand characteristics.
In one embodiment of the present disclosure, the user information includes service level data, consumption characteristic data, price demand data, user location data, and network demand data, wherein the network demand data includes bandwidth demand data, latency demand data, security demand data, and reliability demand data;
the user resource demand information comprises calculation force size demand data, calculation force type demand data, calculation force source demand data and calculation force form demand data;
the key demand features include calculation force size demand data, calculation force type demand data, bandwidth demand data, and time demand data.
In one embodiment of the present disclosure, before matching the resource request feature data of the target user with the resource request feature data of the plurality of historical users, respectively, to obtain a plurality of matching results, the method further includes:
acquiring resource request feature data of a plurality of historical users and user evaluation information corresponding to each historical user;
screening out the resource request characteristic data of the historical users corresponding to the user evaluation information which does not meet the preset conditions, and obtaining the resource request characteristic data of the historical users corresponding to the user evaluation information which meets the preset conditions.
In one embodiment of the present disclosure, after performing computing power resource allocation for the target user according to the computing power resource allocation manner corresponding to the historical user corresponding to the current matching result, the method further includes:
and obtaining the user evaluation of the target user based on the distribution result of the computing power resource distribution, and storing the user evaluation.
According to another aspect of the present disclosure, there is provided a computing power resource allocation system, the system comprising: the system comprises an computing power resource matching platform, a resource management platform and a history resource management platform;
the computing power resource matching platform is used for determining resource request characteristic data of a target user according to user information and user resource demand information, respectively matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of historical users to obtain a plurality of matching results, and performing computing power resource allocation for the target user according to a computing power resource allocation mode corresponding to the historical user corresponding to the current matching result when the matching result meeting the preset condition exists in the plurality of matching results;
the resource management platform is used for sending a resource request of the target user to the computing power resource matching platform, wherein the resource request comprises user information of the target user and user resource demand information;
The historical resource management platform is used for sending the resource request characteristic data of the preset historical user to the computing power resource matching platform.
According to yet another aspect of the present disclosure, there is provided a computing power resource allocation apparatus, the apparatus comprising:
the first acquisition module is used for acquiring a resource request of a target user, wherein the resource request comprises user information of the target user and user resource demand information;
the determining module is used for determining the resource request characteristic data of the target user according to the user information and the user resource demand information;
the matching module is used for respectively matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of historical users to obtain a plurality of matching results;
and the distribution module is used for distributing the computing power resources for the target user according to the computing power resource distribution mode corresponding to the historical user corresponding to the current matching result when the matching result meeting the preset condition exists in the plurality of matching results.
In one embodiment of the present disclosure, the determining module includes:
a first determining unit, configured to determine a resource request vector of a target user according to the user information and the user resource requirement information;
And the second determining unit is used for determining the resource request vector of the target user as the resource request characteristic data of the target user.
In one embodiment of the present disclosure, the first determining unit includes:
the classification subunit is used for classifying the user information and the user resource demand information based on a preset rule to obtain key demand characteristics and non-key demand characteristics;
the coding subunit is used for coding the non-key demand characteristics to obtain coded non-key demand characteristics;
and the determining subunit is used for determining the resource request vector of the target user according to the key demand characteristics and the encoded non-key demand characteristics.
In one embodiment of the present disclosure, the user information includes service level data, consumption characteristic data, price demand data, user location data, and network demand data, wherein the network demand data includes bandwidth demand data, latency demand data, security demand data, and reliability demand data;
the user resource demand information comprises calculation force size demand data, calculation force type demand data, calculation force source demand data and calculation force form demand data;
the key demand features include calculation force size demand data, calculation force type demand data, bandwidth demand data, and time demand data.
In one embodiment of the present disclosure, the computing power resource allocation apparatus further includes:
the second acquisition module is used for acquiring the resource request characteristic data of the plurality of historical users and the user evaluation information corresponding to each historical user before matching the resource request characteristic data of the target user with the resource request characteristic data of the plurality of historical users respectively to obtain a plurality of matching results;
and the screening module is used for screening the resource request characteristic data of the historical users corresponding to the user evaluation information which does not meet the preset conditions, and obtaining the resource request characteristic data of the historical users corresponding to the user evaluation information which meets the preset conditions.
In one embodiment of the present disclosure, the computing power resource allocation apparatus further includes:
and the third acquisition module is used for acquiring the user evaluation of the target user based on the distribution result of the computing power resource distribution after the computing power resource distribution is carried out on the target user according to the computing power resource distribution mode corresponding to the historical user corresponding to the current matching result, and storing the user evaluation.
According to still another aspect of the present disclosure, there is provided an electronic apparatus including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-described computing power resource allocation method via execution of the executable instructions.
According to yet another aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described computing power resource allocation method.
According to the computing power resource allocation method provided by the embodiment of the disclosure, the resource request feature data of the target user is determined according to the user information and the user resource demand information in the resource request by acquiring the resource request of the target user, then the resource request feature data of the target user is respectively matched with the resource request feature data of a plurality of historical users according to the resource request feature data of the target user, a plurality of matching results are obtained, and computing power resource allocation is carried out for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result when the matching result meeting the preset condition exists in the plurality of matching results. Because the computing power resource is allocated to the user according to the user information of the target user and the user resource demand information, the computing power resource is allocated on the basis of multiple dimensions, so that the computing power resource allocation is more accurate, and the efficiency and the accuracy of the computing power resource allocation are improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.
FIG. 1 is a schematic diagram of a computing resource allocation system architecture in an embodiment of the present disclosure;
FIG. 2 illustrates a flow chart of a method for computing resource allocation in an embodiment of the present disclosure;
FIG. 3 illustrates another computing resource allocation method flow diagram in an embodiment of the present disclosure;
FIG. 4 illustrates a flowchart of yet another method for computing resource allocation in an embodiment of the present disclosure;
FIG. 5 illustrates a flowchart of yet another method for computing resource allocation in an embodiment of the present disclosure;
FIG. 6 illustrates a schematic diagram of a computing resource allocation device in an embodiment of the present disclosure; and
fig. 7 shows a block diagram of an electronic device in an embodiment of the disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
In order to solve the above problems, the present disclosure provides a computing power resource allocation method, system, device, equipment and storage medium.
Next, a description will be first given of the computing power resource allocation system provided by the present disclosure.
FIG. 1 illustrates a schematic diagram of a computing force resource allocation system provided by an embodiment of the present disclosure, as illustrated in FIG. 1, a computing force resource allocation system 10 in an embodiment of the present disclosure may include:
an computing power resource matching platform 101, a resource management platform 102, and a history resource management platform 103;
the computing power resource matching platform 101 is configured to determine resource request feature data of a target user according to user information and user resource requirement information, match the resource request feature data of the target user with resource request feature data of a plurality of historical users respectively, obtain a plurality of matching results, and perform computing power resource allocation for the target user according to a computing power resource allocation mode corresponding to the historical user corresponding to the current matching result when a matching result meeting a preset condition exists in the plurality of matching results;
The resource management platform 102 is configured to send a resource request of the target user to the computing power resource matching platform 101, where the resource request includes user information of the target user and user resource requirement information;
the historical resource management platform 103 is configured to send the preset resource request feature data of the historical user to the computing power resource matching platform 101.
It should be noted that, the computing resource matching platform 101, the resource management platform 102, and the history resource management platform 103 may all be disposed on a server, and the server may be a server that provides various services.
Optionally, the server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs (Content Delivery Network, content delivery networks), basic cloud computing services such as big data and artificial intelligence platforms, and the like. The terminal may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, etc. The terminal and the server may be directly or indirectly connected through wired or wireless communication, which is not limited herein.
It should be noted that, the resource management platform 102 may respond to a resource request of a target user sent by a user through a user terminal device.
The terminal device may be a variety of electronic devices including, but not limited to, smartphones, tablets, laptop portable computers, desktop computers, wearable devices, augmented reality devices, virtual reality devices, and the like.
The server and the terminal device carrying the resource management platform 102 may complete information transmission through a wired network and a wireless network.
Alternatively, the wireless network or wired network described above uses standard communication techniques and/or protocols. The network is typically the Internet, but may be any network including, but not limited to, a local area network (Local Area Network, LAN), metropolitan area network (Metropolitan Area Network, MAN), wide area network (Wide Area Network, WAN), mobile, wired or wireless network, private network, or any combination of virtual private networks. In some embodiments, data exchanged over a network is represented using techniques and/or formats including HyperText Mark-up Language (HTML), extensible markup Language (Extensible MarkupLanguage, XML), and the like. All or some of the links may also be encrypted using conventional encryption techniques such as secure sockets layer (Secure Socket Layer, SSL), transport layer security (Transport Layer Security, TLS), virtual private network (Virtual Private Network, VPN), internet protocol security (Internet ProtocolSecurity, IPsec), etc. In other embodiments, custom and/or dedicated data communication techniques may also be used in place of or in addition to the data communication techniques described above.
Those skilled in the art will appreciate that the above-described number of terminal devices, networks and servers is merely illustrative, and that any number of terminal devices, networks and servers may be provided as desired. The embodiments of the present disclosure are not limited in this regard.
In the computing power resource allocation system provided by the embodiment of the disclosure, a resource request of a target user is obtained through a resource management platform, then user information and user resource demand information in the resource request are sent to a computing power resource matching platform, resource request feature data of the target user is determined by the computing power resource matching platform according to the user information and the user resource demand information in the resource request, then the resource request feature data of the target user are respectively matched with resource request feature data of a plurality of historical users sent by a historical resource management platform to obtain a plurality of matching results, and computing power resource allocation is carried out for the target user according to a computing power resource allocation mode corresponding to the historical user corresponding to the current matching result under the condition that the matching results meeting preset conditions exist in the plurality of matching results. Because the computing power resource is allocated to the user according to the user information of the target user and the user resource demand information, the computing power resource is allocated on the basis of multiple dimensions, so that the computing power resource allocation is more accurate, and the efficiency and the accuracy of the computing power resource allocation are improved.
Based on the same inventive concept, an embodiment of the present disclosure discloses a method for allocating computing power resources, fig. 2 shows a flowchart of a method for allocating computing power resources in an embodiment of the present disclosure, and as shown in fig. 2, the method for allocating computing power resources in an embodiment of the present disclosure may include:
s202, acquiring a resource request of a target user, wherein the resource request comprises user information of the target user and user resource demand information.
It should be noted that, the user information includes service level data, consumption characteristic data, price demand data, user location data, and network demand data, where the network demand data includes bandwidth demand data, time delay demand data, security demand data, and reliability demand data.
The user resource demand information includes power size demand data, power type demand data, power source demand data, and power form demand data.
By way of example, the service level data may include general users, advanced users, premium users.
The consumption characteristic data may include individual user consumption, business user consumption, and government user consumption.
Price demand data may include price sensitive and price insensitive.
The user location data may include latitude and longitude data of the user location.
The bandwidth requirement data may include a bandwidth requirement of the network path.
The latency requirement data may include latency requirements of the network path.
The security requirement data may include unsecure encryption and secure encryption.
Reliability requirement data may include best effort and deterministic.
The computing force size demand data may include the size of the computing force resources required.
The calculation force type demand data may include a base calculation force, an intelligent calculation force, and an supercomputing calculation force.
The computing power source demand data may include public clouds, private clouds, and hybrid clouds.
The power form demand data may include bare metal, virtual machines, and containers.
As a specific example, the computing power resource allocation apparatus may be configured to receive a resource request sent by a user through a terminal device.
The computing power resource allocation device can also determine the resource request of the user through the collection of the historical data of the user.
S204, determining the resource request characteristic data of the target user according to the user information and the user resource demand information.
The resource request feature data is data that can reflect the user information and the features of the user resource request information.
The computing power resource allocation device can distinguish the target user from other users according to the resource request characteristic data, and can acquire users with similar requirements with the target user according to the resource request characteristic data.
S206, matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of historical users respectively to obtain a plurality of matching results.
It should be noted that the resource request feature data of the historical user may be determined by the computing power resource allocation device based on the user information of the historical user and the user resource requirement information.
Matching the resource request characteristic data of the target user with the resource request characteristic data of the plurality of historical users, respectively, may include:
and obtaining the similarity between the resource request characteristic data of the target user and the resource request characteristic data of a plurality of historical users.
The formula for obtaining the similarity may include a cosine similarity formula, which is not specifically limited in this disclosure.
And S208, under the condition that the matching results meeting the preset conditions exist in the plurality of matching results, computing power resource allocation is carried out for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result.
It should be noted that the plurality of matching results may include a similarity between the resource request feature data of the target user and the resource request feature data of the history user.
The matching result meeting the preset condition may include that the obtained similarity meets a certain value range.
The computing power resource allocation mode corresponding to the historical user can comprise an allocation scheme of computing power resource allocation of the historical user. Wherein the allocation scheme may include all elements related to the allocation of computational resources, which are not described in detail herein.
According to the computing power resource allocation method provided by the embodiment of the disclosure, the resource request feature data of the target user is determined according to the user information and the user resource demand information in the resource request by acquiring the resource request of the target user, then the resource request feature data of the target user is respectively matched with the resource request feature data of a plurality of historical users according to the resource request feature data of the target user, a plurality of matching results are obtained, and computing power resource allocation is carried out for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result when the matching result meeting the preset condition exists in the plurality of matching results. Because the computing power resource is allocated to the user according to the user information of the target user and the user resource demand information, the computing power resource is allocated on the basis of multiple dimensions, so that the computing power resource allocation is more accurate, and the efficiency and the accuracy of the computing power resource allocation are improved.
Based on the same inventive concept, the embodiment of the present disclosure discloses another method for allocating computing power resources, fig. 3 shows a flowchart of another method for allocating computing power resources in the embodiment of the present disclosure, and as shown in fig. 3, the difference between the embodiment of the present disclosure and the above embodiment is that S204 may include:
s302, determining a resource request vector of the target user according to the user information and the user resource demand information.
It should be noted that, the foregoing embodiments have disclosed detailed information included in the user information and the user resource requirement information.
For example, the detailed information may be digitized, and then a corresponding resource request vector may be generated according to the digitized detailed information.
S304, determining the resource request vector of the target user as the resource request characteristic data of the target user.
In the embodiment of the disclosure, the resource request characteristic data of the target user is determined by vectorizing the user information and the user resource demand information. The resource request characteristic data based on the vector representation can be made clearer because the vector has the characteristic of being clear and easy to observe.
Based on the same inventive concept, the embodiment of the present disclosure discloses yet another method for allocating computing power resources, and fig. 4 shows a flowchart of another method for allocating computing power resources in the embodiment of the present disclosure, as shown in fig. 4, where the difference between the embodiment of the present disclosure and the above embodiment is that S302 may include:
And S402, classifying the user information and the user resource demand information based on preset rules to obtain key demand characteristics and non-key demand characteristics.
It should be noted that the key demand features include calculation force demand data, calculation force type demand data, bandwidth demand data, and time demand data.
The non-critical demand characteristic data may include user information beyond the critical demand characteristic data and user resource demand information.
S404, coding the non-critical demand features to obtain coded non-critical demand features.
It should be noted that encoding the non-critical demand features may include mapping different non-critical demand features to different data.
For example, an individual user consumption correspondence may be encoded as 1 and an enterprise user consumption correspondence may be encoded as 2. The above examples are merely illustrative of coding schemes, and the coding schemes are various and are not particularly limited herein.
And S406, determining a resource request vector of the target user according to the key demand characteristics and the coded non-key demand characteristics.
In the embodiment of the disclosure, the user information and the network demand data are divided into the key demand characteristics and the non-key demand characteristics, and on the basis, the user information and the network demand data corresponding to each user are vectorized, so that the value range of the key demand characteristics is wider, the difference between the key demand characteristics corresponding to different users is larger, and the vector formed based on the key demand characteristics and the non-key demand characteristics is more specialized, thereby being beneficial to distinguishing different users through the vector.
Based on the same inventive concept, the embodiment of the present disclosure discloses yet another method for allocating computing power resources, and fig. 5 shows a flowchart of yet another method for allocating computing power resources in the embodiment of the present disclosure, as shown in fig. 5, where the difference between the embodiment of the present disclosure and the above embodiment is that, before S206, the method for allocating computing power resources may further include:
s502, acquiring resource request feature data of a plurality of historical users and user evaluation information corresponding to each historical user.
The computing power resource allocation device may automatically collect the evaluation of the historical user.
As a specific example, after the computing power resource allocation device collects the rating of the history user, the collected rating of the history user may be correlated with the history user. Wherein the historical users correspond to resource allocation modes of the historical users.
S504, screening out the resource request characteristic data of the historical users corresponding to the user evaluation information which does not meet the preset conditions, and obtaining the resource request characteristic data of the historical users corresponding to the user evaluation information which meets the preset conditions.
The user evaluation information may be positive user evaluation information and negative user evaluation information.
In order to avoid that the computing power resource allocation mode of the historical user corresponding to the negative user evaluation information is used as the computing power resource allocation mode of the current target user, the computing power resource allocation mode of the user can be screened based on the user evaluation information so as to obtain the computing power resource part allocation mode corresponding to the positive user evaluation information.
The user evaluation information may be a user evaluation score, and the computing power resource allocation mode corresponding to the user evaluation information lower than the preset score may be deleted.
According to the method and the device for computing power resource allocation, computing power resource allocation modes of users are screened according to the user evaluation information, so that computing power resource allocation modes corresponding to higher user evaluation are obtained, and then computing power resource allocation is carried out for target users according to the computing power resource allocation modes corresponding to the higher user evaluation, so that computing power resource allocation can be more accurate.
In some embodiments, in order to be able to obtain the user evaluation information of the historical user, after the computing power resource allocation to the target user is completed, the user evaluation information of the target user based on the decomposition result of the computing power resource allocation may be obtained, and then the user evaluation information may be stored.
Based on the same inventive concept, an apparatus for distributing computing power resources is also provided in the embodiments of the present disclosure, such as the following embodiments. Since the principle of solving the problem of the embodiment of the device is similar to that of the embodiment of the method, the implementation of the embodiment of the device can be referred to the implementation of the embodiment of the method, and the repetition is omitted.
Fig. 6 shows a schematic diagram of a computing power resource allocation apparatus according to an embodiment of the disclosure, as shown in fig. 6, the apparatus includes:
a first obtaining module 602, configured to obtain a resource request of a target user, where the resource request includes user information of the target user and user resource requirement information;
a determining module 604, configured to determine the resource request feature data of the target user according to the user information and the user resource requirement information;
the matching module 606 is configured to match the resource request feature data of the target user with the resource request feature data of a plurality of historical users, so as to obtain a plurality of matching results;
and the allocation module 608 is configured to allocate the computing power resources for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result when the matching result satisfying the preset condition exists in the plurality of matching results.
In the computing power resource allocation device provided by the embodiment of the disclosure, a first acquisition module is used for acquiring a resource request of a target user, then user information and user resource demand information in the resource request are sent to a computing power resource matching platform, a determination module is used for determining resource request characteristic data of the target user according to the user information and the user resource demand information in the resource request, then a matching module is used for matching the resource request characteristic data of the target user with resource request characteristic data of a plurality of historical users sent by a historical resource management platform respectively according to the resource request characteristic data of the target user to obtain a plurality of matching results, and computing power resource allocation is carried out for the target user according to a computing power resource allocation mode corresponding to the historical user corresponding to the current matching result when the matching results meeting preset conditions exist in the plurality of matching results. Because the computing power resource is allocated to the user according to the user information of the target user and the user resource demand information, the computing power resource is allocated on the basis of multiple dimensions, so that the computing power resource allocation is more accurate, and the efficiency and the accuracy of the computing power resource allocation are improved.
In some embodiments, the determining module 604 includes:
A first determining unit, configured to determine a resource request vector of a target user according to the user information and the user resource requirement information;
and the second determining unit is used for determining the resource request vector of the target user as the resource request characteristic data of the target user.
In the embodiment of the disclosure, the resource request characteristic data of the target user is determined by vectorizing the user information and the user resource demand information. The resource request characteristic data based on the vector representation can be made clearer because the vector has the characteristic of being clear and easy to observe.
In some embodiments, the first determining unit comprises:
the classification subunit is used for classifying the user information and the user resource demand information based on a preset rule to obtain key demand characteristics and non-key demand characteristics;
the coding subunit is used for coding the non-key demand characteristics to obtain coded non-key demand characteristics;
and the determining subunit is used for determining the resource request vector of the target user according to the key demand characteristics and the encoded non-key demand characteristics.
In the embodiment of the disclosure, the user information and the network demand data are divided into the key demand characteristics and the non-key demand characteristics, and on the basis, the user information and the network demand data corresponding to each user are vectorized, so that the value range of the key demand characteristics is wider, the difference between the key demand characteristics corresponding to different users is larger, and the vector formed based on the key demand characteristics and the non-key demand characteristics is more specialized, thereby being beneficial to distinguishing different users through the vector.
In some embodiments, the user information includes service level data, consumption characteristics data, price demand data, user location data, and network demand data, wherein the network demand data includes bandwidth demand data, latency demand data, security demand data, and reliability demand data;
the user resource demand information comprises calculation force size demand data, calculation force type demand data, calculation force source demand data and calculation force form demand data;
the key demand features include calculation force size demand data, calculation force type demand data, bandwidth demand data, and time demand data.
In some embodiments, the computing power resource allocation apparatus 600 further comprises:
the second obtaining module 610 is configured to obtain the resource request feature data of the plurality of historical users and the user evaluation information corresponding to each historical user before matching the resource request feature data of the target user with the resource request feature data of the plurality of historical users to obtain a plurality of matching results;
and the screening module 612 is configured to screen out the resource request feature data of the historical user corresponding to the user evaluation information that does not meet the preset condition, so as to obtain the resource request feature data of the historical user corresponding to the user evaluation information that meets the preset condition.
In some embodiments, the computing power resource allocation apparatus 600 further comprises:
and a third obtaining module 614, configured to obtain a user evaluation of the target user based on the allocation result of the computing power resource allocation after performing computing power resource allocation for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result, and store the user evaluation.
According to the method and the device for computing power resource allocation, computing power resource allocation modes of users are screened according to the user evaluation information, so that computing power resource allocation modes corresponding to higher user evaluation are obtained, and then computing power resource allocation is carried out for target users according to the computing power resource allocation modes corresponding to the higher user evaluation, so that computing power resource allocation can be more accurate.
Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, various aspects of the disclosure 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 700 according to such an embodiment of the present disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is merely an example and should not be construed to limit the functionality and scope of use of embodiments of the present disclosure in any way.
As shown in fig. 7, the electronic device 700 is embodied in the form of a general purpose computing device. Components of electronic device 700 may include, but are not limited to: the at least one processing unit 710, the at least one memory unit 720, and a bus 730 connecting the different system components, including the memory unit 720 and the processing unit 710.
Wherein the storage unit stores program code that is executable by the processing unit 710 such that the processing unit 710 performs steps according to various exemplary embodiments of the present disclosure described in the above-described "exemplary methods" section of the present specification. For example, the processing unit 710 may perform the following steps of the method embodiment described above:
acquiring a resource request of a target user, wherein the resource request comprises user information of the target user and user resource demand information;
determining resource request characteristic data of a target user according to the user information and the user resource demand information;
matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of historical users respectively to obtain a plurality of matching results;
And under the condition that the matching results meeting the preset conditions exist in the plurality of matching results, performing computing power resource allocation for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result.
The memory unit 720 may include readable media in the form of volatile memory units, such as Random Access Memory (RAM) 7201 and/or cache memory 7202, and may further include Read Only Memory (ROM) 7203.
The storage unit 720 may also include a program/utility 7204 having a set (at least one) of program modules 7205, such program modules 7205 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.
Bus 730 may be a bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 700 may also communicate with one or more external devices 740 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 700, and/or any device (e.g., router, modem, etc.) that enables the electronic device 700 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 750. Also, electronic device 700 may 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 network adapter 760. As shown, network adapter 760 communicates with other modules of electronic device 700 over bus 730. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 700, including, but not limited to: microcode, device drivers, redundant processing units, 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, which may be a readable signal medium or a readable storage medium, is also provided. On which a program product is stored which enables the implementation of the method described above of the present disclosure. In some possible implementations, various aspects of the disclosure 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 disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.
More specific examples of the computer readable storage medium in the present disclosure may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In this disclosure, a computer readable storage 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.
Alternatively, the program code embodied on a computer readable storage 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.
In particular implementations, the program code for carrying out operations of the present disclosure 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).
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.
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 in order 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 description of the above 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.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. A method of computing power resource allocation, the method comprising:
acquiring a resource request of a target user, wherein the resource request comprises user information of the target user and user resource demand information;
determining resource request characteristic data of a target user according to the user information and the user resource demand information;
matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of historical users respectively to obtain a plurality of matching results;
and under the condition that the matching results meeting the preset conditions exist in the plurality of matching results, performing computing power resource allocation for the target user according to the computing power resource allocation mode corresponding to the historical user corresponding to the current matching result.
2. The method of claim 1, wherein determining the resource request characteristic data of the target user based on the user information and user resource demand information comprises:
determining a resource request vector of a target user according to the user information and the user resource demand information;
and determining the resource request vector of the target user as the resource request characteristic data of the target user.
3. The method of claim 2, wherein determining the resource request vector for the target user based on the user information and user resource demand information comprises:
Classifying the user information and the user resource demand information based on a preset rule to obtain key demand characteristics and non-key demand characteristics;
coding the non-critical demand features to obtain coded non-critical demand features;
and determining a resource request vector of the target user according to the key demand characteristics and the coded non-key demand characteristics.
4. The method of claim 3, wherein the user information comprises service level data, consumption characteristics data, price demand data, user location data, and network demand data, wherein the network demand data comprises bandwidth demand data, latency demand data, security demand data, and reliability demand data;
the user resource demand information comprises calculation force size demand data, calculation force type demand data, calculation force source demand data and calculation force form demand data;
the key demand features include calculation force size demand data, calculation force type demand data, bandwidth demand data, and time demand data.
5. The method of claim 1, wherein before matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of history users, respectively, to obtain a plurality of matching results, the method further comprises:
Acquiring resource request feature data of a plurality of historical users and user evaluation information corresponding to each historical user;
screening out the resource request characteristic data of the historical users corresponding to the user evaluation information which does not meet the preset conditions, and obtaining the resource request characteristic data of the historical users corresponding to the user evaluation information which meets the preset conditions.
6. The method according to claim 1, wherein after performing the computing power resource allocation for the target user according to the computing power resource allocation manner corresponding to the historical user corresponding to the current matching result, the method further comprises:
and acquiring user evaluation information of a target user based on an allocation result of computing power resource allocation, and storing the user evaluation information.
7. A computing power resource allocation system, the system comprising: the system comprises an computing power resource matching platform, a resource management platform and a history resource management platform;
the computing power resource matching platform is used for determining resource request feature data of a target user according to user information and user resource demand information, respectively matching the resource request feature data of the target user with the resource request feature data of a plurality of historical users to obtain a plurality of matching results, and performing computing power resource allocation for the target user according to a computing power resource allocation mode corresponding to the historical user corresponding to the current matching result when the matching result meeting the preset condition exists in the plurality of matching results;
The resource management platform is used for sending a resource request of a target user to the computing power resource matching platform, wherein the resource request comprises user information of the target user and user resource demand information;
the history resource management platform is used for sending the resource request characteristic data of the preset history user to the computing power resource matching platform.
8. A computing power resource allocation apparatus, the apparatus comprising:
the first acquisition module is used for acquiring a resource request of a target user, wherein the resource request comprises user information of the target user and user resource demand information;
the determining module is used for determining the resource request characteristic data of the target user according to the user information and the user resource demand information;
the matching module is used for respectively matching the resource request characteristic data of the target user with the resource request characteristic data of a plurality of historical users to obtain a plurality of matching results;
and the distribution module is used for distributing the computing power resources for the target user according to the computing power resource distribution mode corresponding to the historical user corresponding to the current matching result when the matching result meeting the preset condition exists in the plurality of matching results.
9. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the computing power resource allocation method of any one of claims 1-6 via execution of the executable instructions.
10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the computing power resource allocation method of any of claims 1 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117687798A (en) * | 2024-02-01 | 2024-03-12 | 浪潮通信信息系统有限公司 | Management and control method, system and storage medium for original application of computing power network |
| CN117687798B (en) * | 2024-02-01 | 2024-05-10 | 浪潮通信信息系统有限公司 | Management and control method, system and storage medium for original application of computing power network |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117687798A (en) * | 2024-02-01 | 2024-03-12 | 浪潮通信信息系统有限公司 | Management and control method, system and storage medium for original application of computing power network |
| CN117687798B (en) * | 2024-02-01 | 2024-05-10 | 浪潮通信信息系统有限公司 | Management and control method, system and storage medium for original application of computing power network |
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