CN115987813B - Domain distribution device, method and system and intelligent vehicle - Google Patents
Domain distribution device, method and system and intelligent vehicle Download PDFInfo
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Abstract
The utility model discloses a domain allocation device, a method, a system and an intelligent vehicle, which relate to the technical field of computers, and are characterized in that the device is used for leading processes corresponding to all services in a current system into a domain allocation network model, then calculating an output matrix, and the output matrix contains memory occupation corresponding to a domain allocation mode, selecting a target memory occupation meeting a set condition, and finally allocating domain identifications for all services according to a domain identification allocation mode of the target memory occupation, thereby solving the problem that the current domain allocation mode obviously increases memory consumption, further reducing the memory occupation of the domain allocation mode and reducing the memory consumption.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a domain allocation device, method, system, and intelligent vehicle.
Background
Currently, DDS (Data Distribution Service ) is a middleware protocol and API standard based on DCPS (Data-Centric publishing-subscore) model defined by OMG (Object Management Group, object management organization), so DDS integrates the components of the system together, providing low latency Data connections, extremely high reliability and scalable architecture required for business and mission critical internet of things (IoT) applications.
According to the application characteristics of the DDS, a Domain needs to be assigned to each communication Node, each communication Node can only communicate within the same Domain, each communication Node can assign a plurality of domains, according to the characteristics of the DDS, the communication Node assigns a Domain to generate a Domain participant buffer (participant buffer) required for maintaining the Domain to communicate with other communication nodes, that is, pre-assigned memory consumption is required, the size of the pre-assigned memory consumption is proportional to the number of communication nodes in the Domain, for example, 5 nodes in one Domain, and each Node maintains 4 copies participant buffer.
At present, a DDS is also used in the automotive field as a communication middleware framework, and basically one Domain is adopted to manage all communication nodes, so that communication can be ensured between any two communication nodes, but each communication node needs to be stored and participant buffer of all other communication nodes in the field is also caused by the mode, so that memory consumption is increased remarkably.
Disclosure of Invention
The application provides a domain allocation device, a domain allocation method, a domain allocation system and an intelligent vehicle, which are used for reducing the memory consumption of communication nodes in a DDS.
In a first aspect, the present application provides a domain allocation apparatus, including a processor and a memory, the memory being configured to store a program executable by the processor, the processor being configured to read the program in the memory and perform the steps of:
determining each service in a current system and a process corresponding to each service, wherein the service is provided for a communication node in the current system or used by the communication node;
inputting the processes corresponding to the services into a domain distribution network model to obtain each domain distribution mode and the memory occupation amount corresponding to each domain distribution mode, wherein each domain distribution mode comprises a domain identifier and all services associated with the domain identifier;
determining a target memory occupation amount meeting a set condition from all memory occupation amounts, and taking a domain allocation mode corresponding to the target memory occupation amount as a target domain identification allocation mode;
and distributing the domain identifier for each service according to the target domain identifier distribution mode.
By the device, the processes corresponding to the services in the current system are imported into the domain allocation network model, then the output matrix is calculated, the memory occupation amount corresponding to the domain allocation mode is contained in the output matrix, the target memory occupation amount meeting the set condition is selected, finally, the domain identifications are allocated to the services according to the domain identification allocation mode of the target memory occupation amount, and therefore the current domain identification allocation mode is guaranteed to reduce the memory occupation amount and reduce the memory consumption.
In an alternative embodiment, the processor is specifically configured to perform:
acquiring N service combinations, and constructing a process associated with each service combination into a process matrix to obtain N process matrixes, wherein the service combinations comprise at least one service, and N is an integer greater than 2;
constructing an output matrix of a designated network model, wherein the output matrix comprises a domain identifier and all services associated with the domain identifier;
and training a designated network model through the N process matrixes and the output matrixes to obtain the domain distribution network model.
In an alternative embodiment, the processor is specifically configured to perform:
carrying out N times of random combination on all the services in the current system to obtain N service combinations consisting of service combinations generated by each time of random combination, wherein the service combinations comprise at least one service;
and adding the processes associated with the service combination into a matrix as matrix elements to obtain N process matrixes.
In an alternative embodiment, the processor is specifically configured to perform:
determining a domain identifier and a memory occupation amount corresponding to each service combination in the N service combinations;
and constructing an output matrix of the specified network model comprising the memory occupation amount, the domain identifier and the service identifier.
In an alternative embodiment, the processor is specifically configured to perform:
and determining the minimum memory occupation amount from all the memory occupation amounts, and taking the minimum memory occupation amount as the target memory occupation amount.
In a second aspect, the present application provides a domain allocation method, the method comprising:
determining each service in a current system and a process corresponding to each service, wherein the service is provided for a communication node in the current system or used by the communication node;
inputting the processes corresponding to the services into a domain distribution network model to obtain each domain distribution mode and the memory occupation amount corresponding to each domain distribution mode, wherein each domain distribution mode comprises a domain identifier and all services associated with the domain identifier;
determining a target memory occupation amount meeting a set condition from all memory occupation amounts, and taking a domain allocation mode corresponding to the target memory occupation amount as a target domain identification allocation mode;
and distributing the domain identifier for each service according to the target domain identifier distribution mode.
By the method, the processes corresponding to the services in the current system are imported into the domain allocation network model, the output matrix is calculated, the memory occupation amount corresponding to the domain allocation mode is contained in the output matrix, the target memory occupation amount meeting the set condition is selected, and finally, the domain identifications are allocated to the services according to the domain identification allocation mode of the target memory occupation amount, so that the current domain identification allocation mode is guaranteed, the memory occupation amount can be reduced, and the memory consumption is reduced.
In an alternative embodiment, before determining each service in the current system and the process corresponding to each service, the method further includes:
acquiring N service combinations, and constructing a process associated with each service combination into a process matrix to obtain N process matrixes, wherein the service combinations comprise at least one service, and N is an integer greater than 2;
constructing an output matrix of a designated network model, wherein the output matrix comprises a domain identifier and all services associated with the domain identifier;
and training a designated network model through the N process matrixes and the output matrixes to obtain the domain distribution network model.
In a third aspect, the present application provides an intelligent vehicle comprising any one of the domain allocation devices described above.
In a fourth aspect, the present application provides a domain allocation system comprising at least a controller; the controller is specifically configured to perform any of the domain allocation methods described above.
In a fifth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements any of the domain allocation methods described above.
Drawings
Fig. 1 is a schematic structural diagram of a domain allocation device provided in the present application;
FIG. 2 is a schematic diagram of a relationship between a service and a communication node in the system provided by the present application;
fig. 3 is a flowchart of a domain allocation method provided in the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, 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 be within the scope of the invention.
In the embodiment of the invention, the term "and/or" describes the association relation of the association objects, which means that three relations can exist, for example, a and/or B can be expressed as follows: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
The application scenario described in the embodiment of the present invention is for more clearly describing the technical solution of the embodiment of the present invention, and does not constitute a limitation on the technical solution provided by the embodiment of the present invention, and as a person of ordinary skill in the art can know that the technical solution provided by the embodiment of the present invention is applicable to similar technical problems as the new application scenario appears. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
Currently, DDS is defined by OMG, based on one middleware protocol and API standard of DCPS model, so DDS integrates the components of the system, providing low latency data connections, extremely high reliability and scalable architecture required for business and mission critical internet of things (IoT) applications.
According to the application characteristics of the DDS, a Domain needs to be assigned to each communication Node, each communication Node can only communicate within the same Domain, each communication Node can assign a plurality of domains, according to the characteristics of the DDS, the communication Node assigns a Domain to generate a Domain participant buffer (participant buffer) required for maintaining the Domain to communicate with other communication nodes, that is, pre-assigned memory consumption is required, the size of the pre-assigned memory consumption is proportional to the number of communication nodes in the Domain, for example, 5 nodes in one Domain, and each Node maintains 4 copies participant buffer.
At present, a DDS is also used in the automotive field as a communication middleware framework, and basically one Domain is adopted to manage all communication nodes, so that communication can be ensured between any two communication nodes, but each communication node needs to be stored and participant buffer of all other communication nodes in the field is also caused by the mode, so that memory consumption is increased remarkably.
In order to solve the above problems, in this embodiment of the present application, a domain allocation device is provided, by which domain identifiers are allocated to each service in a current system according to different modes, so as to obtain various different domain identifier allocation modes, then, memory occupancy amounts corresponding to each domain allocation mode are calculated, a target memory occupancy amount meeting a set condition is determined in the memory occupancy amounts, and finally, the domain identifiers are allocated to each service according to the domain identifier allocation mode of the target memory occupancy amount, so that the current domain identifier allocation mode can reduce the memory occupancy amount and reduce the memory consumption.
Referring to fig. 1, a domain allocation apparatus provided in an embodiment of the present application includes a processor 10 and a memory 11, where the memory 11 is used for storing a program executable by the processor 10, and the processor 10 is used for reading the program in the memory 11 and executing the following steps:
determining each service in the current system and a process corresponding to each service;
referring to fig. 2, the service provides or is a service used by a communication node in the current system, and in fig. 2, each service is associated with a communication node;
inputting the processes corresponding to the services into a domain distribution network model to obtain each domain distribution mode and the memory occupation amount corresponding to each domain distribution mode, wherein each domain distribution mode comprises a domain identifier and all services associated with the domain identifier;
determining a target memory occupation amount meeting a set condition from all memory occupation amounts, and taking a domain allocation mode corresponding to the target memory occupation amount as a target domain identification allocation mode;
and distributing the domain identifier for each service according to the target domain identifier distribution mode.
Specifically, before determining each service in the current system, a specific network model needs to be trained to obtain the domain distribution network model, and the specific implementation method is as follows:
firstly, determining all services in a current system, then randomly combining the services, for example, a service 1, a service 2, a service 3 and a service 4 exist in the current system, combining the service 1 with the service 2, combining the service 3 with the service 4, and combining the service 1 with the service 3 to obtain a plurality of service combinations, thereby obtaining N service combinations formed by the service combinations generated by random combination each time. At least one service is included in each service combination.
Here, it should be noted that a single service is also used as a combination, and for example, the service 1, the service 2, the service 3, and the service 4 are all a service combination.
After N service combinations are obtained, processes associated with the service combinations are added into the matrix as matrix elements, and N process matrices are obtained.
For example, the processes associated with service 1 are p00, p01, p02 … p0m, the processes associated with service 2 are p10, p11, p12 … p1m, the processes associated with service 3 are p20, p21, p22 … p2m, and the processes associated with service 4 are p30, p31, p32 … p3m.
At this time, the service 1, the service 2, the service 3 and the service 4 can be independently used as a service combination, and the process matrix corresponding to the service 1 independently used as a service combination is as follows:
[p00 p01 …… p0m]
[ 0 0 ……… 0]
…
[ 0 0 ……… 0]
it should be noted that, the number of rows of the process matrix is related to the number of all services in the current system, that is, the number of services in the current system is 4, and the process matrix includes 4 rows, where each row represents a process associated with one service.
In the above example, since service 1 alone is a service combination, the first row in the process matrix is the process associated with service 1, and the other rows are filled with "0". Of course, the method of constructing the process matrix by other services alone is the same as that of constructing the process matrix by the service 1, and will not be described herein.
Of course, instead of building a process matrix from a single service, a process matrix may be built from a combination of multiple services, such as a service 1 and a service 3, which are specifically as follows:
[p00 p01 …… p0m]
[p20 p21 …… p2m]
…
[ 0 0 ……… 0]
of course, the process matrix may also be jointly constructed by the service 1, the service 2, the service 3 and the service 4, which is specifically as follows:
[p00 p01 …… p0m]
[p10 p11 …… p1m]
[P20 p21 …… p2m]
[p30 p31 …… p3m]
according to the method, N service combinations can be respectively constructed into corresponding process matrixes, so that N process matrixes are obtained. The N process matrices serve as inputs for training a specified network model.
In addition to the inputs, training the specified network model requires corresponding outputs, which are output matrices constructed from memory footprint, domain identification, and service identification. Specifically, first, a domain identifier and a memory occupation amount corresponding to each service combination in the N service combinations are determined, and an output matrix of a specified network model including the memory occupation amount, the domain identifier and the service identifier is constructed.
For example, if there are a total of 16 processes in the current system, at most 16 bits in a row in the output matrix, the output matrix corresponding to the process matrix is individually constructed for service 1, service 2, service 3, and service 4 as follows:
[0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0]
[id1 s1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id2 s2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id3 s3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id4 s4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
wherein 300 represents the memory occupation amount, id1, id2, id3 and id4 represent different domain identifiers, and s1, s2, s3 and s4 represent identifiers of service 1, service 2, service 3 and service 4.
Similarly, if the service 1, the service 2 and the service 3 form a service combination, the service 4 forms a service combination independently, and the corresponding output matrix is as follows:
[0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0]
[id4 s1 s2 s3 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id5 s4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
wherein 200 represents the memory occupation amount, id4 and id5 represent different domain identifiers, and s1, s2, s3 and s4 represent identifiers of service 1, service 2, service 3 and service 4 respectively.
In addition, if the service 1 and the service 2 form a service combination, and the service 3 and the service 4 form a service combination, the corresponding output matrix is:
[0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0]
[id6 s1 s2 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id7 s3 s4 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
wherein 100 represents the memory occupation amount, id6 and id6 represent the identifiers of different domains, and s1, s2, s3 and s4 represent the identifiers of service 1, service 2, service 3 and service 4.
Of course, the above examples are only illustrative of output matrices corresponding to several service combinations, and other possible service combinations are not illustrated.
After the input matrix and the output matrix of the specified network model are determined, the specified network model is trained through the input matrix and the output matrix, and whether training parameters of the specified network model are adjusted or not needs to be further determined through the output matrix of the specified network model in the training process.
Specifically, after the specified network model outputs the corresponding output matrix, a difference value between the output matrix and the actual output matrix is calculated, and training parameters of the specified network model are adjusted according to the difference value until the difference value between the output matrix and the actual output matrix of the specified network model is within a set range, and at this time, the specified network model is used as a domain distribution network model. Here, the actual output matrix is a preset output matrix corresponding to the input matrix.
By the method, the domain distribution network model can be accurately obtained, so that the domain distribution mode of each service in the current system can be determined through the domain distribution network model.
Therefore, after the domain distribution network model is obtained, each service in the current system and the process corresponding to each service are determined. And constructing an input matrix by the corresponding process of each service, and importing the input matrix into a domain distribution network model. The domain distribution network model directly calculates output matrices, where there is more than one output matrix, each representing a domain distribution pattern.
For example, the current system includes 6 services (service 1, service 2, service 3, service 4, service 5, service 6), and the 6 services include 6*m processes. The corresponding input matrix at this time is:
[p10 p11 …… p1m]
[p20 p21 …… p2m]
[P30 p31 …… p3m]
[p40 p41 …… p4m]
[p50 p51 …… p5m]
[p60 p61 …… p6m]
after importing the input matrix into the domain distribution network model, the domain distribution network model outputs various output matrices, such as output matrix 1, output matrix 2, output matrix 3, and output matrix 4.
Wherein, output matrix 1 is:
[0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0]
[id1 s1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id2 s2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id3 s3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id4 s4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id5 s5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id6 s6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
the output matrix is characterized in that a domain identifier is allocated to each of the service 1, the service 2, the service 3, the service 4, the service 5 and the service 6 separately, and the memory occupation amount corresponding to the domain allocation mode is 500.
Wherein, output matrix 2 is:
[0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0]
[id1 s1 s2 s3 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id2 s4 s5 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id3 s6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
the output matrix is characterized in that the service 1, the service 2 and the service 3 are allocated with the same domain identifier, the service 4 and the service 5 are allocated with the same domain identifier, the service 6 is separately allocated with a domain identifier, and the memory occupation amount corresponding to the domain allocation mode is 400.
The output matrix 3 is:
[0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0]
[id1 s1 s2 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id2 s3 s4 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id3 s5 s6 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
the output matrix is characterized in that the service 1 and the service 2 are allocated with the same domain identifier, the service 3 and the service 4 are allocated with the same domain identifier, the service 5 and the service 6 are allocated with the same domain identifier, and the memory occupation amount corresponding to the domain allocation mode is 300.
The output matrix 4 is:
[0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0]
[id1 s1 s2 s3 0 0 0 0 0 0 0 0 0 0 0 0 ]
[id2 s4 s5 s6 0 0 0 0 0 0 0 0 0 0 0 0 ]
the output matrix is characterized in that the service 1, the service 2 and the service 3 are allocated with the same domain identifier, the service 4, the service 5 and the service 6 are allocated with the same domain identifier, and the memory occupation amount corresponding to the domain allocation mode is 200.
After the above various output matrices are obtained, the target memory occupancy amounts with memory occupancy amounts satisfying the set conditions are selected from all the output matrices, for example, the memory occupancy amounts are sorted according to a small-to-large memory manner, any one of the first 2 memory occupancy amounts is taken as the target memory occupancy amount, for example, in the above example, the memory occupancy amounts are 200 and 300 as the target memory occupancy amounts, and the domain allocation mode corresponding to the output matrix is taken as the target domain allocation mode.
For example, in the above example, the memory occupation amount is determined to be 300 as the target memory occupation amount, and at this time, the domain allocation mode corresponding to the output matrix is used as the target domain allocation mode, that is, the service 1 and the service 2 are allocated with the same domain identifier, the service 3 and the service 4 are allocated with the same domain identifier, and the service 5 and the service 6 are allocated with the same domain identifier.
Of course, in the actual application scenario, the domain allocation mode with the smallest memory occupation amount may be used as the target domain allocation mode. For example, the memory occupation amount is 200, and at this time, service 1, service 2, and service 3 allocate the same domain identifier, and service 4, service 5, and service 6 allocate the same domain identifier.
The method can avoid the problem of large total memory occupation caused by using the same domain by all services, and can reduce the memory consumption caused by unreasonable domain allocation to the greatest extent.
Based on the same inventive concept, the embodiment of the present invention further provides a domain allocation method, and the principle of solving the problem of the method is similar to that of any domain allocation device described above, so that the implementation of the method can refer to the implementation of the device, and the repetition is omitted.
Referring to fig. 3, the domain allocation method has an implementation flow including:
s31, determining each service in the current system and a process corresponding to each service;
here, the service is a service provided by or used by the communication node in the current system;
s32, inputting the processes corresponding to the services into a domain distribution network model to obtain each domain distribution mode and the memory occupation amount corresponding to each domain distribution mode;
here, each domain allocation method includes a domain identifier and all services associated with the domain identifier;
s33, determining a target memory occupation amount meeting a set condition from all memory occupation amounts, and taking a domain allocation mode corresponding to the target memory occupation amount as a target domain identification allocation mode;
s34, distributing domain identifiers for each service according to the target domain identifier distribution mode.
In an alternative embodiment, N service combinations are obtained, a process associated with each service combination is constructed as a process matrix, N process matrices are obtained, an output matrix of a specified network model is constructed, and the specified network model is trained through the N process matrices and the output matrix, so that a domain distribution network model is obtained.
In an optional embodiment, all services in the current system are randomly combined for N times to obtain N service combinations composed of service combinations generated by random combination each time, wherein the service combinations all comprise at least one service;
and adding the processes associated with the service combination into a matrix as matrix elements to obtain N process matrixes.
In an optional embodiment, determining a domain identifier and a memory occupation amount corresponding to each of the N service combinations;
and constructing an output matrix of the specified network model comprising the memory occupation amount, the domain identifier and the service identifier.
How to obtain the domain allocation network model and how to determine the corresponding domain allocation method are described in detail in the foregoing embodiments, and will not be described in detail herein.
By the method, the processes corresponding to the services in the current system are imported into the domain allocation network model, then the output matrix is calculated, the memory occupation amount corresponding to the domain allocation mode is contained in the output matrix, the target memory occupation amount meeting the set condition is selected, finally, the domain identifications are allocated to the services according to the domain identification allocation mode of the target memory occupation amount, and therefore the current domain identification allocation mode is guaranteed to reduce the memory occupation amount and reduce the memory consumption.
Based on the same inventive concept, the embodiment of the present invention further provides a domain allocation system, which solves the problem on the principle similar to any one of the domain allocation methods, so that the implementation of the system can refer to the implementation of the method, and the repetition is omitted.
The system provided by the embodiment of the application at least comprises a controller; the controller is specifically configured to perform the steps of:
determining each service in a current system and a process corresponding to each service, wherein the service is provided for a communication node in the current system or used by the communication node;
inputting the processes corresponding to the services into a domain distribution network model to obtain each domain distribution mode and the memory occupation amount corresponding to each domain distribution mode, wherein each domain distribution mode comprises a domain identifier and all services associated with the domain identifier;
determining a target memory occupation amount meeting a set condition from all memory occupation amounts, and taking a domain allocation mode corresponding to the target memory occupation amount as a target domain identification allocation mode;
and distributing the domain identifier for each service according to the target domain identifier distribution mode.
In an alternative embodiment, the controller is specifically configured to perform:
acquiring N service combinations, and constructing a process associated with each service combination into a process matrix to obtain N process matrixes, wherein the service combinations comprise at least one service, and N is an integer greater than 2;
constructing an output matrix of a designated network model, wherein the output matrix comprises a domain identifier and all services associated with the domain identifier;
and training a designated network model through the N process matrixes and the output matrixes to obtain the domain distribution network model.
In an alternative embodiment, the controller is specifically configured to perform:
carrying out N times of random combination on all the services in the current system to obtain N service combinations consisting of service combinations generated by each time of random combination, wherein the service combinations comprise at least one service;
and adding the processes associated with the service combination into a matrix as matrix elements to obtain N process matrixes.
In an alternative embodiment, the controller is specifically configured to perform:
determining a domain identifier and a memory occupation amount corresponding to each service combination in the N service combinations;
and constructing an output matrix of the specified network model comprising the memory occupation amount, the domain identifier and the service identifier.
Based on the same inventive concept, the embodiment of the invention also provides an intelligent vehicle, which comprises any one of the domain allocation devices. The intelligent vehicle is used for realizing the function of distributing the domain identifiers of the services in the system based on any domain distribution device.
Based on the same inventive concept, embodiments of the present disclosure provide a computer storage medium, the computer storage medium including: computer program code which, when run on a computer, causes the computer to perform the domain allocation method as any of the preceding discussion. Since the principle of solving the problem by the computer storage medium is similar to that of the domain allocation method, the implementation of the computer storage medium can refer to the implementation of the method, and the repetition is omitted.
In a specific implementation, the computer storage medium may include: a universal serial bus flash disk (USB, universal Serial Bus Flash Drive), a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Based on the same inventive concept, the disclosed embodiments also provide a computer program product comprising: computer program code which, when run on a computer, causes the computer to perform the domain allocation method as any of the preceding discussion. Since the principle of the solution of the problem of the computer program product is similar to that of the domain allocation method, the implementation of the computer program product may refer to the implementation of the method, and the repetition is omitted.
The computer 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 methods in this application may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described herein are performed in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, a network device, a user device, a core network device, an OAM, or other programmable apparatus.
The computer program or instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer program or instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that integrates one or more available media. The usable medium may be a magnetic medium, e.g., floppy disk, hard disk, tape; but also optical media such as digital video discs; but also semiconductor media such as solid state disks. The computer readable storage medium may be volatile or nonvolatile storage medium, or may include both volatile and nonvolatile types of storage medium.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A domain allocation apparatus comprising a processor and a memory, said memory for storing a program executable by said processor, said processor for reading the program in said memory and performing the steps of:
determining each service in a current system and a process corresponding to each service, wherein the service is provided for a communication node in the current system or used by the communication node;
inputting the processes corresponding to the services into a domain distribution network model to obtain each domain distribution mode and the memory occupation amount corresponding to each domain distribution mode, wherein each domain distribution mode comprises a domain identifier and all services associated with the domain identifier;
determining a target memory occupation amount meeting a set condition from all memory occupation amounts, and taking a domain allocation mode corresponding to the target memory occupation amount as a target domain identification allocation mode;
and distributing the domain identifier for each service according to the target domain identifier distribution mode.
2. The apparatus of claim 1, wherein the processor is specifically configured to perform:
acquiring N service combinations, and constructing a process associated with each service combination into a process matrix to obtain N process matrixes, wherein the service combinations comprise at least one service, and N is an integer greater than 2;
constructing an output matrix of a designated network model, wherein the output matrix comprises a domain identifier and all services associated with the domain identifier;
and training a designated network model through the N process matrixes and the output matrixes to obtain the domain distribution network model.
3. The apparatus of claim 2, wherein the processor is specifically configured to perform:
carrying out N times of random combination on all the services in the current system to obtain N service combinations consisting of service combinations generated by each time of random combination, wherein the service combinations comprise at least one service;
and adding the processes associated with the service combination into a matrix as matrix elements to obtain N process matrixes.
4. The apparatus of claim 2, wherein the processor is specifically configured to perform:
determining a domain identifier and a memory occupation amount corresponding to each service combination in the N service combinations;
and constructing an output matrix of the specified network model comprising the memory occupation amount, the domain identifier and the service identifier.
5. The apparatus of claim 1, wherein the processor is specifically configured to perform:
and determining the minimum memory occupation amount from all the memory occupation amounts, and taking the minimum memory occupation amount as the target memory occupation amount.
6. A method of domain allocation, the method comprising:
determining each service in a current system and a process corresponding to each service, wherein the service is provided for a communication node in the current system or used by the communication node;
inputting the processes corresponding to the services into a domain distribution network model to obtain each domain distribution mode and the memory occupation amount corresponding to each domain distribution mode, wherein each domain distribution mode comprises a domain identifier and all services associated with the domain identifier;
determining a target memory occupation amount meeting a set condition from all memory occupation amounts, and taking a domain allocation mode corresponding to the target memory occupation amount as a target domain identification allocation mode;
and distributing the domain identifier for each service according to the target domain identifier distribution mode.
7. The method of claim 6, wherein prior to determining each service in the current system, and the process to which each service corresponds, the method further comprises:
acquiring N service combinations, and constructing a process associated with each service combination into a process matrix to obtain N process matrixes, wherein the service combinations comprise at least one service, and N is an integer greater than 2;
constructing an output matrix of a designated network model, wherein the output matrix comprises a domain identifier and all services associated with the domain identifier;
and training a designated network model through the N process matrixes and the output matrixes to obtain the domain distribution network model.
8. An intelligent vehicle, characterized in that it comprises an apparatus according to any one of claims 1-5.
9. A domain distribution system comprising at least a controller; the controller is specifically configured to perform the method of any one of claims 6-7.
10. A computer readable storage medium having stored thereon a computer program, which, when executed by a processor, implements the method of any of claims 6-7.
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