CN116662000A - Subway service processing method based on industrial personal computer cluster - Google Patents
Subway service processing method based on industrial personal computer cluster Download PDFInfo
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Abstract
The application relates to a cloud service technology and discloses a subway service processing method based on an industrial personal computer cluster. The method has the advantages that by means of clustering, hardware resources and software resources can be dynamically increased or reduced according to the service processing demand, the expandability is good, the resource utilization rate is improved, and the method is more energy-saving and low-carbon; and the purchasing cost of each terminal device is reduced, so that the operation cost of a subway operation company is reduced.
Description
Technical Field
The application relates to the technical field of cloud service, in particular to a subway service processing method based on an industrial personal computer cluster, electronic equipment and a storage medium.
Background
In subway stations, there are a large number of terminal devices responsible for handling subway traffic, such as automatic ticket machines (AGMs) responsible for handling gate ticket checking traffic, semi-automatic ticket machines (BOMs) responsible for handling ticket vending traffic, recharging traffic, trip handling traffic, automatic ticket machines (TVMs) responsible for handling ticket purchasing traffic, and automatic inquiring machines (TCMs) responsible for handling trip inquiring traffic.
In the prior art, each terminal device is internally provided with an industrial personal computer (simply referred to as SLE in the subway industry), and the industrial personal computer is responsible for running subway service software and processing various services such as passing a gate, recharging, ticketing, inquiring and the like. Each terminal device is internally provided with an industrial personal computer, the construction cost of the terminal device is high, the utilization rate of the terminal devices such as an automatic ticket checking machine, a self-service ticket purchasing machine and the like at remote or small passenger subway stations is low, and each terminal device is internally provided with an industrial personal computer, so that the waste of hardware resources of the industrial personal computer is caused.
Disclosure of Invention
In order to solve the problems in the prior art, the application provides a subway service processing method based on an industrial personal computer cluster, electronic equipment and a storage medium.
According to an aspect of the embodiment of the present application, there is disclosed a subway service processing method based on an industrial personal computer cluster, the subway service processing method being executed by a subway industrial personal computer cluster, the subway industrial personal computer cluster including a plurality of service processing nodes formed by a plurality of industrial personal computers, the service processing nodes running a container mirror image to process a subway service request, the subway service processing method including:
Receiving subway service requests sent by all terminal equipment in a subway station, and distributing the subway service requests to corresponding container images;
and running the container mirror image to process the subway service request, and returning a service processing result to the terminal equipment.
In an exemplary embodiment, the assigning the subway service request to a corresponding container image includes:
analyzing the subway service request to obtain a service class corresponding to the subway service request;
and distributing the subway service request to a corresponding container mirror image based on the service class corresponding to the subway service request.
In an exemplary embodiment, the assigning the subway service request to the corresponding container image based on the service class corresponding to the subway service request includes:
acquiring the load condition of each container mirror image corresponding to the business category of the subway business request;
and distributing the subway service requests according to the load condition of each container mirror image so as to balance the load of each container mirror image.
In an exemplary embodiment, when the subway service request is a gate ticket checking request, the receiving the subway service request sent by each terminal device in the subway station and distributing the subway service request to the corresponding container mirror image includes:
Receiving ticket passing ticket checking requests sent by all automatic ticket checking machines in a subway station, and distributing the ticket passing ticket checking requests to corresponding ticket checking container images;
and the running the container mirror image to process the subway service request and return a service processing result to the terminal equipment comprises the following steps:
running the ticket checking container mirror image to process the passing ticket checking request, and returning a processing result of the passing ticket checking request to the automatic ticket checking machine;
when the subway service request is a ticket buying request, the receiving the subway service request sent by each terminal device in the subway station and distributing the subway service request to the corresponding container mirror image includes:
receiving ticket buying requests sent by all automatic ticket vending machines in a subway station, and distributing the ticket buying requests to corresponding ticket buying container images;
and the running the container mirror image to process the subway service request and return a service processing result to the terminal equipment comprises the following steps:
running the ticket buying container mirror image to process the ticket buying request, and returning a ticket buying request processing result to the automatic ticket vending machine;
when the subway service request is a query request, the receiving the subway service request sent by each terminal device in the subway station and distributing the subway service request to a corresponding container mirror image includes:
Receiving inquiry requests sent by all automatic inquiry machines in a subway station, and distributing the inquiry requests to corresponding inquiry container images;
and the running the container mirror image to process the subway service request and return a service processing result to the terminal equipment comprises the following steps:
and running the query container mirror image to process the query request and returning a query request processing result to the automatic query machine.
In an exemplary embodiment, the subway service processing method further includes an industrial personal computer cluster updating step, where the industrial personal computer cluster updating step includes:
acquiring passenger flow information of the subway station, and determining the number of container images to be increased or decreased and the hardware configuration to be increased or decreased of the subway station according to the passenger flow information;
adding or reducing a corresponding number of container images in the subway industrial personal computer cluster;
the feedback requires increased or decreased hardware configuration to enable the staff to increase or decrease the corresponding hardware configuration in the subway industrial personal computer cluster.
In an exemplary embodiment, the determining, according to the traffic information, the number of container images that the subway station needs to increase or decrease and the hardware configuration that needs to increase or decrease include:
Inputting the passenger flow information into a target decision tree model;
and determining the number of container images which need to be increased or decreased and the hardware configuration which needs to be increased or decreased of the subway station by utilizing the target decision tree model.
In an exemplary embodiment, before inputting the traffic information into the target decision tree model, the subway industrial personal computer cluster updating step further includes:
constructing an initial decision tree model;
inputting training data into the initial decision tree model to train to obtain a target decision tree model, wherein the training data comprises passenger flow of subway stations, hardware configuration in the subway stations, configuration parameters of a single industrial personal computer, recommended container mirror image number and hardware configuration.
In an exemplary embodiment, the industrial personal computer cluster updating step further includes:
acquiring the running state of the container mirror image;
and if the container mirror image cannot normally operate, sending out alarm information for indicating that the container mirror image cannot normally operate.
In an exemplary embodiment, the industrial personal computer cluster updating step further includes:
and when the subway station needs to be added with hardware configuration according to the passenger flow information, sending alarm information for indicating that the hardware configuration is insufficient.
According to an aspect of an embodiment of the present application, there is disclosed an electronic device including:
one or more processors;
and the memory is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the electronic equipment realizes the subway service processing method.
According to an aspect of an embodiment of the present application, there is disclosed a computer-readable storage medium storing computer-readable instructions that, when executed by a processor of a computer, cause the computer to perform the aforementioned subway service processing method.
The technical scheme provided by the embodiment of the application at least comprises the following beneficial effects:
according to the technical scheme provided by the application, the subway industrial personal computer cluster is used as a unit to provide business processing service to the outside, the subway industrial personal computer cluster receives and processes subway business requests sent by all terminal equipment in a subway station, and then business processing results are returned to the terminal equipment. The method has the advantages that by means of clustering, hardware resources and software resources can be dynamically increased or reduced according to the service processing demand, the expandability is good, the resource utilization rate is improved, and the method is more energy-saving and low-carbon; meanwhile, each terminal device in the subway station can be free from arranging an industrial personal computer, so that the purchase cost of each terminal device can be reduced, and the operation cost of a subway operation company is reduced.
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 application as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
FIG. 1 is a schematic diagram showing the composition of an automated ticket gate in the prior art;
fig. 2 shows a schematic diagram of an exemplary subway service processing system architecture to which the technical scheme of the first embodiment of the present application may be applied;
fig. 3 shows a schematic diagram of an exemplary metro industrial personal computer cluster architecture to which the technical solution of the first embodiment of the present application may be applied;
fig. 4 shows a flowchart of a subway service processing method according to the first embodiment of the present application;
fig. 5 shows a detailed flowchart corresponding to step S410 in fig. 4;
fig. 6 shows a flowchart of a subway service processing method according to a second embodiment of the present application;
fig. 7 shows a flowchart of a subway service processing method according to a third embodiment of the present application;
fig. 8 shows a flowchart of a subway service processing method according to a fourth embodiment of the present application;
fig. 9 shows a flowchart of a metro industrial personal computer cluster update procedure in a fifth embodiment of the present application;
FIG. 10 is a diagram of training data according to a fifth embodiment of the present application;
Fig. 11 shows a flowchart of a step of updating a group of ground iron industrial personal computers according to a sixth embodiment of the present application;
fig. 12 shows a block diagram of a subway service processing apparatus according to a seventh embodiment of the present application;
fig. 13 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.
The reference numerals are explained as follows:
100. an automatic ticket checker; 101. a housing; 102. an NFC antenna module; 103. an industrial personal computer; 104. a gate controller; 200. a system architecture; 201. the subway industrial personal computer cluster; 202a/202b/202c/202d, and terminal equipment; 2021. a housing; 2022. an NFC antenna module; 2023. a gate controller; 301. the physical industrial personal computer; 302. a load balancing module; 303. a container mirror image; 304. a container management module; 305. a virtualization module; 306. an intelligent deployment platform; 307. a passenger flow prediction system; 1200. subway service processing device; 1201. a service receiving and distributing module; 1202. the subway service processing module; 1203. a software and hardware deployment recommendation module; 1204. a container mirror image increasing and decreasing module; 1205. an information feedback module; 1206. a model training module; 1300. a computer system; 1301. a CPU; 1302. a ROM; 1303. a RAM; 1304. a bus; 1305. an I/O interface; 1306. an input section; 1307. an output section; 1308. a storage section; 1309. a communication section; 1310. a driver; 1311. removable media.
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.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the application may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the application.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the 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.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
In the related art, in a subway station, an industrial personal computer is built in each terminal device, taking an automatic ticket checker (also called gate) as an example, as shown in fig. 1, the automatic ticket checker 100 includes a casing 101, and an NFC antenna module 102, an industrial personal computer 103 and a gate controller 104 which are built in the casing 101, when a passenger swipes a card, the NFC antenna module 102 recognizes the card, judges the authenticity of the card, and deducts fees; then, the NFC antenna module 102 sends the card transaction data to the industrial personal computer 103 through a serial port (e.g., RS 232); after the industrial personal computer 103 processes the transaction data, a door opening instruction is sent to the gate controller 104 through a serial port (such as RS 232); the gate controller 104 controls the gate to open, at which time passengers may pass the gate.
Each terminal device is internally provided with an industrial personal computer, and has the following defects: 1. whether the utilization rate of the terminal equipment is high or low or not is limited, an industrial personal computer is arranged, so that the construction cost of the terminal equipment is high, and the purchase cost of the terminal equipment is high; 2. in a remote or small passenger subway station, the utilization rate of terminal equipment is low, an industrial personal computer is built in each terminal equipment, so that the hardware resource waste of the industrial personal computer is caused, and for a conventional passenger subway station, the phenomenon that passengers frequently use a plurality of terminal equipment, for example, passengers often use a plurality of gate passing channels to pass through, and the hardware resource waste of the industrial personal computer is also caused; 3. the hardware resource is wasted due to excessive configuration of the hardware resource of the industrial personal computer, for example, the memory usage of most automatic ticket detectors is generally less than 20%, the processor occupies less than 15%, and the performance is excessive; 4. whether the terminal equipment is in use or not, all industrial personal computers of the terminal equipment are in an electrified working state, so that the energy consumption is high, and the power resource waste is particularly obvious at subway stations with small passenger flows; 5. in order to meet the operation and maintenance requirements of an industrial personal computer, the terminal equipment is provided with a USB interface, and the USB interface is exposed at a subway station and is unsafe.
Therefore, the application provides a new subway service processing method and a related device, wherein the subway service processing method is executed by the subway industrial personal computer cluster, and the subway industrial personal computer cluster is used as a unit to provide service for the outside, so that the operation cost of a subway operation company can be reduced.
The subway service processing method and the related device provided by the application are described in detail below with reference to specific embodiments.
Fig. 2 shows a schematic diagram of an exemplary subway service processing system architecture to which the technical scheme of the first embodiment of the present application can be applied.
As shown in fig. 2, the system architecture 200 may include a ground iron industrial personal computer cluster 201 and a plurality of terminal devices (e.g., terminal device 202a, terminal device 202b, terminal device 202c, terminal device 202d shown in fig. 2). Each terminal device can establish communication connection with the subway industrial personal computer cluster 201, so as to realize the sending of the subway service request and the receiving of the service processing result. It should be understood that the number of terminal devices shown in fig. 2 is merely illustrative, and that any number of terminal devices may be present in a subway station, as desired for implementation.
The terminal device 202a/202b/202c/202d may be an automatic ticket gate machine (AGM), an automatic Ticket Vending Machine (TVM), a window ticket making machine (BOM), an automatic inquiring machine (TCM), etc., when the terminal device is an automatic ticket gate machine (AGM), the subway service request is a passing ticket gate checking request, when the terminal device is an automatic Ticket Vending Machine (TVM), the subway service request is a ticket purchasing request, when the terminal device is an automatic inquiring machine (TCM), the subway service request is an inquiring request, when the terminal device is a window ticket making machine (BOM), the subway service request may be a recharging request, a travel processing request, etc.
Taking an automatic ticket checking machine (AGM) as an example, as shown in fig. 2, the terminal device includes a housing 2021, an NFC antenna module 2022 and a gate controller 2023, wherein the NFC antenna module 2022 is arranged in the housing 2021, and when a passenger swipes a card, the NFC antenna module 2022 recognizes the card, judges the authenticity of the card and deducts fees; then, the NFC antenna module 2022 sends the card transaction data to the subway industrial personal computer cluster 201 through the network; after the subway industrial personal computer cluster 201 processes the transaction data, a door opening command is sent to the gate controller 2023 through a network; the gate controller 2023 controls gate opening, at which time passengers can pass through the gate.
Fig. 3 shows a schematic diagram of an exemplary metro industrial personal computer cluster architecture to which the technical solution of the first embodiment of the present application may be applied.
As shown in fig. 3, the subway industrial personal computer cluster architecture includes a hardware portion and a software portion.
The hardware part includes a plurality of physical computers 301 and at least one cluster server. The plurality of physical industrial personal computers 301 form a plurality of service processing nodes, and the service processing nodes run software for processing subway service requests, and the software is deployed in a container in a mirror image manner, so the software is called container mirror image.
The software portion may be loaded in a cluster server, including a load balancing module 302, a plurality of container images 303, a container management module 304, and a virtualization module 305, among others.
The load balancing module 302 is configured to receive subway service requests (such as a ticket checking request, a ticket purchasing request, a recharging request, a query request, etc.) sent by each terminal device, and distribute the subway service requests sent by each terminal device to the corresponding container mirror 303 in a load balancing manner.
The plurality of container images 303 include AGM container images (ticket container images), BOM container images, TVM container images (ticket purchasing container images), TCM container images (query container images), etc., the container images 303 are deployed in a virtualized environment and can dynamically increase or decrease the number thereof. The container image 303 contains a packaged application and its dependencies, as well as the process information it runs at start-up. The container mirror 303 can be operated by a service processing node to process subway service requests such as a pass ticket inspection request, a ticket purchase request, a recharge request, a query request, and the like.
The container management module 304 is used to manage and maintain the container images 303 and dynamically increase or decrease the container images 303.
The virtualization module 305 virtualizes the plurality of physical industrial computers 301 to form one or more virtual machines, and provides a hardware base for service operation outside the virtual machines.
Further, in an embodiment of the present application, the cluster server is further loaded with an intelligent deployment platform 306, and the intelligent deployment platform 306 can support a worker to remotely pass through the platform to perform manual software resource increase and decrease, and can dock the passenger flow prediction system 307 to obtain passenger flow information of the subway station, and further give a hardware resource and software resource configuration suggestion according to the passenger flow information, and alarm when the resource is insufficient.
Fig. 4 is a flowchart of a subway service processing method according to the first embodiment of the present application, where the subway service processing method is performed by a subway industrial personal computer cluster, and the subway industrial personal computer cluster may be the subway industrial personal computer cluster shown in fig. 2 and implemented by using the architecture shown in fig. 3. Referring to fig. 4, the subway service processing method at least includes steps S410 to S420, and is described in detail as follows:
in step S410, a subway service request sent by each terminal device in a subway station is received, and the subway service request is allocated to a corresponding container mirror image.
Since various types of terminal devices can be set in the subway station to accept various types of subway service requests and perform service processing through the subway industrial personal computer cluster, for example, an automatic ticket machine (AGM) is set to accept the gate ticket checking request, a Ticket Vending Machine (TVM) is set to accept the ticket purchasing request, and an automatic query machine (TCM) is set to accept the query request, etc., when the subway service request is allocated, allocation is required based on the service class corresponding to the subway service request.
In one embodiment of the present application, as shown in fig. 5, step S410 includes the following steps S510 to S530, which are described in detail below:
in step S510, a subway service request sent by each terminal device in a subway station is received.
In detail, the metro service request may be a data packet, which includes an active address, a data portion and a target address, where the active address is an address of a terminal device, the metro industrial personal computer cluster feeds back a service processing result to a corresponding terminal device based on the active address, and the target address is an address of the metro industrial personal computer cluster, and the data portion includes specific service request content.
The subway industrial personal computer cluster is configured with a request receiving port, the address of the request receiving port is the target address in the subway service request, and each terminal device in the subway station can send the subway service request to the request receiving port through a network, so that the subway industrial personal computer cluster can receive the subway service request.
In step S520, the subway service request is parsed, and a service class corresponding to the subway service request is obtained.
As described above, the subway service request may be a data packet, which includes an active address, a data portion and a destination address, where the data portion includes specific service request contents, and the data portion may be obtained by parsing the subway service request, so as to further obtain a service class corresponding to the subway service request.
In some embodiments, the data portion may include specific service request content and a service class label, where the service class corresponding to the subway service request may be obtained by analyzing the subway service request to obtain the service class label.
In step S530, the subway service request is allocated to the corresponding container image based on the service class corresponding to the subway service request.
For subway service requests of different service types, processing is required to be performed through different container images, for example, for a passing ticket checking request, processing is required to be performed by running an AGM container image; for ticket buying requests, the TVM container mirror image needs to be operated for processing; for the recharging request, the BOM container mirror image needs to be operated for processing; for the query request, the TCM container mirror needs to be run for processing.
In step S530, the subway service request is allocated to the container mirror image adapted to the service type thereof based on the service class corresponding to the subway service request.
In order to realize more reasonable resource allocation in the subway industrial personal computer cluster so that the load of each service processing node is balanced and the service processing efficiency of the subway industrial personal computer cluster is improved, in one embodiment of the present application, step S530 includes: acquiring the load condition of each container mirror image corresponding to the business category of the subway business request; and distributing subway service requests according to the load conditions of the container images so as to balance the loads of the container images.
In detail, the subway service request is distributed according to the load condition of each container mirror image, namely, the subway service request is distributed to the container mirror image with the minimum current load capacity, so that the load of each container mirror image corresponding to the service category of the subway service request is balanced, and the load of each service processing node is balanced.
For example, the business category of the subway business request is a passing ticket, the subway business computer cluster comprises 15 AGM container images, in the 15 AGM container images, the 12 AGM container images respectively have 1 passing ticket checking request to be processed, the 3 AGM container images respectively have 0 passing ticket checking request to be processed, and the subway business request is distributed to any one of the 3 AGM container images.
For example, the business category of the subway business request is travel inquiry, the subway industrial personal computer cluster comprises 8 TCM container images, among the 8 TCM container images, 4 travel inquiry requests are respectively processed for 7 TCM container images, 3 travel inquiry requests are processed for 1 TCM container image, and then the subway business request is distributed to the 1 TCM container images.
In step S420, the container mirror is operated to process the subway service request, and a service processing result is returned to the terminal device.
That is, the container mirror image allocated in step S410 is operated to process the subway service request, and the service processing result is returned to the terminal device that transmitted the subway service request.
Fig. 6 shows a flowchart of a subway service processing method according to the second embodiment of the present application, where the subway service processing method is performed by a subway industrial personal computer cluster, and the subway industrial personal computer cluster may be the subway industrial personal computer cluster shown in fig. 2 and implemented by using the architecture shown in fig. 3, so as to process a ticket checking request. Referring to fig. 6, the subway service processing method at least includes steps S610 to S620, and is described in detail as follows:
in step S610, a pass ticket inspection request sent by each automatic ticket machine in the subway station is received, and the pass ticket inspection request is distributed to a corresponding ticket container mirror image.
In detail, in step S610, the load condition of each ticket container image may be acquired first, and then the pass ticket inspection request is distributed according to the load condition of each ticket container image, so as to balance the load of each ticket container image.
In step S620, the ticket container mirror is operated to process the pass ticket request, and the pass ticket request processing result is returned to the automatic ticket gate.
Fig. 7 is a flowchart of a subway service processing method according to the third embodiment of the present application, where the subway service processing method is performed by a subway industrial personal computer cluster, and the subway industrial personal computer cluster may be the subway industrial personal computer cluster shown in fig. 2 and implemented by using the architecture shown in fig. 3, so as to process a ticket purchase request. Referring to fig. 7, the subway service processing method at least includes steps S710 to S720, and is described in detail as follows:
in step S710, ticket purchase requests sent by respective ticket vending machines in the subway station are received, and the ticket purchase requests are distributed to corresponding ticket purchase container images.
In detail, in step S710, the load condition of each ticket-buying container mirror image may be obtained first, and then the ticket-buying request may be allocated according to the load condition of each ticket-buying container mirror image, so as to balance the load of each ticket-buying container mirror image.
In step S720, the ticket container mirror image is operated to process the ticket purchase request, and the ticket purchase request processing result is returned to the ticket vending machine.
Fig. 8 is a flowchart of a subway service processing method according to the fourth embodiment of the present application, where the subway service processing method is performed by a subway industrial personal computer cluster, and the subway industrial personal computer cluster may be the subway industrial personal computer cluster shown in fig. 2 and implemented by using the architecture shown in fig. 3, so as to process a query request. Referring to fig. 8, the subway service processing method at least includes steps S810 to S820, and is described in detail as follows:
In step S810, a query request sent by each automatic query machine in the subway station is received, and the query request is distributed to a corresponding query container image.
In detail, in step S810, the load condition of each query container image may be obtained first, and then the query request may be allocated according to the load condition of each query container image, so as to balance the load of each query container image.
In step S820, the query container mirror is run to process the query request, and the query request processing result is returned to the automatic query machine.
It should be noted that, before the subway service processing method shown in the foregoing embodiments is executed, a local industrial personal computer cluster needs to be built first, and as to how to build the local industrial personal computer cluster, on the basis of the disclosure of the present application, a person skilled in the art may implement the method based on the existing cluster building technology, so that no further description is given here.
According to the technical scheme provided by the application, all industrial personal computers are extracted from terminal equipment and divided into the subway industrial personal computer clusters, business processing services are provided for the outside by taking the subway industrial personal computer clusters as units, the subway industrial personal computer clusters receive and process subway business requests sent by all the terminal equipment in a subway station, and then business processing results are returned to the terminal equipment. That is, each terminal device in the subway station can be no longer provided with an industrial personal computer, so that the purchase cost of each terminal device can be reduced, and the operation cost of a subway operation company is reduced; and by means of clustering, hardware resources and software resources can be dynamically increased or reduced according to the service processing demand, the expandability is good, the resource utilization rate is improved, and the energy is saved and the carbon is low.
In detail, during the peak of passenger flow, the hardware resources in the subway industrial personal computer cluster, such as the consumption of the memory, the disk and the processor, can be dynamically increased to the subway industrial personal computer cluster when the occupation is approaching the upper limit of the hardware resources of the subway industrial personal computer cluster, so as to expand the storage of the hardware such as the memory, the disk and the processor. In contrast, when the passenger flow is low, the hardware resources in the subway industrial personal computer cluster are reduced, so that the hardware resources can be dynamically reduced, and the resource allocation of an emergency office is reduced. In addition, the data analysis can be used for allocating a large number of industrial computers in the subway industrial computer cluster aiming at subway stations with large annual passenger flow, and allocating a small number of industrial computers in the subway industrial computer cluster aiming at subway stations with small passenger flow, so that resources can be allocated as required, and the cost control can be realized.
When the hardware resources (i.e. hardware configuration) in the subway industrial personal computer cluster are fixed, the software resources running in the subway industrial personal computer cluster can be dynamically increased and decreased according to the size of the processing service request, for example, when the passenger flow is in a peak, the container management unit dynamically and newly adds one or more AGM container images, and each AGM container image can share and process an external ticket checking and passing request; when the passenger flow is in a valley, the container management unit dynamically reduces one or more AGM container images, reduces the hardware resource usage (memory, processor performance and the like) in the subway industrial personal computer cluster, and reduces the power consumption.
Furthermore, the embodiment of the application further comprises a step of updating the local iron industrial personal computer cluster. Fig. 9 is a flowchart illustrating a metro industrial personal computer cluster updating step performed by a cluster server of a metro industrial personal computer cluster in the fifth embodiment of the present application, where the metro industrial personal computer cluster may be the metro industrial personal computer cluster shown in fig. 2 and is implemented by using the architecture shown in fig. 3. Referring to fig. 9, the subway industrial personal computer cluster updating step at least includes steps S910 to S930, which are described in detail as follows:
in step S910, passenger flow information of the subway station is acquired, and the number of container images to be added or reduced and the hardware configuration to be added or reduced of the subway station are determined according to the passenger flow information.
In detail, determining the number of container images to be increased or decreased and the hardware configuration to be increased or decreased for the subway station according to the passenger flow information may include: determining the number of target container images and target hardware configuration required by subway stations according to the passenger flow information; determining the number of the container images to be increased or decreased in the subway industrial personal computer cluster based on the current number of the container images and the target number of the container images of the subway station; and determining the hardware configuration which needs to be increased or decreased in the subway industrial personal computer cluster based on the current hardware configuration and the target hardware configuration of the subway station.
Specifically, the intelligent deployment platform receives the passenger flow information of the subway station, and further determines the number of container images to be increased or decreased and the hardware configuration to be increased or decreased of the subway station according to the passenger flow information.
The hardware configuration may be the number of physical industrial computers, the memory size, the disk size, etc. The number of container images may be the number of AGM container images, the number of BOM container images, the number of TVM container images, the number of TCM container images, etc., and when various terminal devices are provided in the subway station, the number of container images includes the number of various container images.
In one embodiment of the present application, based on the machine learning decision tree theory and method, in step S910, the passenger flow information is input into the target decision tree model; the number of container images and the hardware configuration required to be increased or decreased for subway stations are determined by utilizing the target decision tree model.
Based on the machine learning decision tree theory and method, multiple influence factors are comprehensively considered, and the number of container images required to be increased or decreased and the hardware configuration required to be increased or decreased of subway stations can be accurately obtained.
In addition, the target decision tree model needs to be constructed before the passenger flow information is input into the target decision tree model. In detail, an initial decision tree model is built; preparing training data, wherein the training data comprise passenger flow volume of subway stations, hardware configuration in the subway stations, configuration parameters of a single industrial personal computer, recommended container mirror image number, hardware configuration and the like, and the training data can be specifically shown in FIG. 10; and inputting a large amount of training data into the initial decision tree model to train to obtain a target decision tree model. Finally, the target decision tree model file is built in the intelligent deployment platform to run; when the traffic changes, the target decision tree model can output the number of container images that need to be increased or decreased and the hardware configuration that needs to be increased or decreased.
For example, at the end of 4 months, the passenger flow prediction system predicts that a large number of passengers will rush into a certain subway station in a five-holiday period, the traffic of the subway industrial personal computer cluster will increase, an automatic ticket machine (AGM) and an automatic ticket machine (TVM) are busy, the passenger flow is predicted to be 10 ten thousand people daily, the intelligent deployment platform receives the passenger flow information and sends the passenger flow information into a target decision tree model for calculation, and a recommendation result is obtained that 20 AGM container images and 30 physical industrial personal computers need to be added to the subway industrial personal computer cluster.
For example, in 10 middle ten days of month, the passenger flow prediction system predicts that passenger flow of a certain subway station will be greatly reduced after a national celebration holiday, the cluster traffic of the subway industrial personal computers will be reduced, an automatic ticket machine (AGM) and a Ticket Vending Machine (TVM) are idle, the predicted passenger flow is 1 ten thousand people per day, the intelligent deployment platform receives the passenger flow information and sends the passenger flow information into a target decision tree model for calculation, and a recommended result is that the subway industrial personal computers cluster needs to be reduced by 20 AGM container images and 30 physical industrial personal computers.
In step S920, a corresponding number of container images are added or subtracted in the metro industrial personal computer cluster.
In step S930, the hardware configuration that needs to be increased or decreased is fed back, so that the staff member increases or decreases the corresponding hardware configuration in the local iron industrial personal computer cluster.
In addition, the number of the target container images and the target hardware configuration required by the subway station can be fed back, so that a worker can know the number of the target container images and increase or decrease corresponding hardware configuration in the subway industrial personal computer cluster based on the target hardware configuration.
Fig. 11 shows a flowchart of a step of updating a ground iron industrial personal computer cluster according to the sixth embodiment of the present application, as shown in fig. 11, further, in an embodiment, the step of updating a ground iron industrial personal computer cluster further includes: acquiring the running state of the container mirror image; if the container mirror image cannot normally operate, sending out alarm information for indicating that the container mirror image cannot normally operate.
Still further, in an embodiment, the step of updating the ground iron industrial personal computer cluster further includes: when the subway station needs to be added with the hardware configuration according to the passenger flow information, alarm information for indicating that the hardware configuration is insufficient is sent out.
When the container mirror image cannot normally run, alarm information is sent out to inform staff to process, for example, whether the container mirror image is normal or not is tested, whether upgrading is needed or not is judged. When the hardware configuration is insufficient, alarm information is sent out to inform workers to process, for example, the idle physical industrial computers are electrified and configured in a virtualized mode, so that new physical industrial computers are added in the cluster, and the subway service processing requirement is further met.
According to the passenger flow information of the subway station, the quantity of the container images to be increased or decreased and the hardware configuration to be increased or decreased of the subway station are determined, the quantity of the container images and the hardware configuration are further adjusted, the most suitable software and hardware configuration of the subway industrial personal computer cluster is obtained while the subway service processing requirement is met, the total power consumption is reduced, the energy is saved, the environment is protected, and meanwhile, the service processing efficiency is ensured; in addition, the subway industrial personal computer cluster can be customized according to specific application scenes, different requirements are met, and different devices in the subway industrial personal computer cluster can also be responsible for different business processes, so that the flexibility of the subway industrial personal computer cluster is improved.
Corresponding to the embodiment of the subway service processing method, the application also provides a subway service processing device.
Referring to fig. 12, fig. 12 is a block diagram of a subway service processing apparatus according to a seventh embodiment of the present application, which may be applied to a subway industrial personal computer cluster, to perform all or part of the steps of the subway service processing method shown in any one of fig. 4 to 9 and 11. As shown in fig. 12, the subway service processing apparatus 1200 includes, but is not limited to: the system comprises a business receiving and distributing module 1201, a subway business processing module 1202, a software and hardware deployment recommending module 1203, a container mirror image increasing and decreasing module 1204, an information feedback module 1205 and a model training module 1206.
The service receiving and distributing module 1201 is configured to receive a subway service request sent by each terminal device in a subway station, and distribute the subway service request to a corresponding container mirror image.
In some embodiments of the present application, based on the foregoing scheme, the service reception allocation module 1201 is configured to: analyzing the subway service request to obtain a service class corresponding to the subway service request; and distributing the subway service request to the corresponding container mirror image based on the service class corresponding to the subway service request.
In some embodiments of the present application, based on the foregoing scheme, the service reception allocation module 1201 is configured to: acquiring the load condition of each container mirror image corresponding to the business category of the subway business request; and distributing subway service requests according to the load conditions of the container images so as to balance the loads of the container images.
In some embodiments of the present application, based on the foregoing solution, when the subway service request is a transit ticket check request, the service receiving and distributing module 1201 is configured to: receiving ticket passing ticket checking requests sent by all automatic ticket checking machines in a subway station, and distributing the ticket passing ticket checking requests to corresponding ticket checking container images; the subway service processing module 1202 is configured to: and running the ticket checking container mirror image to process the passing ticket checking request, and returning the processing result of the passing ticket checking request to the automatic ticket checking machine.
In some embodiments of the present application, based on the foregoing solution, when the subway service request is a ticket purchase request, the service receiving and distributing module 1201 is configured to: receiving ticket buying requests sent by all automatic ticket vending machines in a subway station, and distributing the ticket buying requests to corresponding ticket buying container images; the subway service processing module 1202 is configured to: and running the ticket buying container mirror image to process the ticket buying request, and returning the ticket buying request processing result to the automatic ticket vending machine.
In some embodiments of the present application, based on the foregoing solution, when the subway service request is a query request, the service receiving and distributing module 1201 is configured to: receiving inquiry requests sent by all automatic inquiry machines in a subway station, and distributing the inquiry requests to corresponding inquiry container images; the subway service processing module 1202 is configured to: the query container mirror is run to process the query request and return the query request processing results to the automated querying machine.
The software and hardware deployment recommendation module 1203 is configured to obtain passenger flow information of a subway station, and determine, according to the passenger flow information, the number of container images that need to be added or reduced and the hardware configuration that needs to be added or reduced for the subway station.
In some embodiments of the present application, based on the foregoing scheme, the software and hardware deployment recommendation module 1203 is configured to: inputting passenger flow information into a target decision tree model; the number of container images and the hardware configuration required to be increased or decreased for subway stations are determined by utilizing the target decision tree model.
The model training module 1206 is configured to construct an initial decision tree model, and input training data into the initial decision tree model to train to obtain a target decision tree model.
The training data comprise passenger flow volume of the subway station, hardware configuration in the subway station, configuration parameters of a single industrial personal computer, recommended container mirror image number and hardware configuration.
The container mirror image increasing and decreasing module 1204 is used for increasing or decreasing the corresponding number of container mirror images in the subway industrial personal computer cluster.
The information feedback module 1205 is configured to feed back the hardware configuration that needs to be increased or decreased, so that the staff can increase or decrease the corresponding hardware configuration in the local iron industrial personal computer cluster.
In some embodiments of the present application, based on the foregoing, the information feedback module 1205 is configured to obtain the running state of the container image; if the container mirror image cannot normally operate, sending out alarm information for indicating that the container mirror image cannot normally operate.
In some embodiments of the present application, based on the foregoing scheme, the information feedback module 1205 is configured to: when the subway station needs to be added with the hardware configuration according to the passenger flow information, alarm information for indicating that the hardware configuration is insufficient is sent out.
The implementation process of the functions and roles of each module of the subway service processing apparatus 1200 is specifically described in the implementation process of the corresponding steps in the subway service processing method, and will not be described herein again.
Corresponding to the foregoing embodiment of the subway service processing method, the present application further provides an electronic device, which may be applied to a subway industrial personal computer cluster to execute all or part of the steps of the subway service processing method shown in any one of fig. 4 to 9 and 11.
Fig. 13 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.
It should be noted that, the computer system 1300 of the electronic device shown in fig. 13 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present application.
As shown in fig. 13, the computer system 1300 includes a central processing unit (Central Processing Unit, CPU) 1301, which can perform various appropriate actions and processes, such as performing the methods in the above-described embodiments, according to a program stored in a Read-Only Memory (ROM) 1302 or a program loaded from a storage portion 1308 into a random access Memory (Random Access Memory, RAM) 1303. In the RAM 1303, various programs and data required for the system operation are also stored. The CPU 1301, ROM 1302, and RAM 1303 are connected to each other through a bus 1304. An Input/Output (I/O) interface 1305 is also connected to bus 1304.
The following components are connected to the I/O interface 1305: an input section 1306 including a keyboard, a mouse, and the like; an output portion 1307 including a Cathode Ray Tube (CRT), a liquid crystal display (Liquid Crystal Display, LCD), and the like, a speaker, and the like; a storage portion 1308 including a hard disk or the like; and a communication section 1309 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 1309 performs a communication process via a network such as the internet. The drive 1310 is also connected to the I/O interface 1305 as needed. Removable media 1311, such as magnetic disks, optical disks, magneto-optical disks, semiconductor memory, and the like, is installed as needed on drive 1310 so that a computer program read therefrom is installed as needed into storage portion 1308.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such embodiments, the computer program may be downloaded and installed from a network via the communication portion 1309 and/or installed from the removable medium 1311. When executed by a Central Processing Unit (CPU) 1301, performs various functions defined in the system of the present application.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but 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 of the computer-readable storage medium 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 (Erasable Programmable Read Only Memory, EPROM), 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 the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program 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 computer readable signal medium may also be any computer readable medium that is not a computer 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. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
As another aspect, the present application also provides a computer-readable medium that may be contained in the electronic device described in the above embodiment; or may exist alone without being incorporated into the electronic device. The computer-readable medium carries one or more programs which, when executed by one of the electronic devices, cause the electronic device to implement the methods of the above-described embodiments.
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 functions of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the application. 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.
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 application 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, and includes several instructions to cause a computing device (may be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the method according to the embodiments of the present application.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains.
It is to be understood that the application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (10)
1. The subway service processing method based on the industrial personal computer cluster is characterized in that the subway service processing method is executed by the subway industrial personal computer cluster, the subway industrial personal computer cluster comprises a plurality of service processing nodes formed by a plurality of industrial personal computers, the service processing nodes run container mirror images to process subway service requests, and the subway service processing method comprises the following steps:
receiving subway service requests sent by all terminal equipment in a subway station, and distributing the subway service requests to corresponding container images;
And running the container mirror image to process the subway service request, and returning a service processing result to the terminal equipment.
2. The subway service processing method according to claim 1, wherein the assigning the subway service request to the corresponding container image includes:
analyzing the subway service request to obtain a service class corresponding to the subway service request;
and distributing the subway service request to a corresponding container mirror image based on the service class corresponding to the subway service request.
3. The subway service processing method according to claim 2, wherein the assigning the subway service request to the corresponding container image based on the service class corresponding to the subway service request includes:
acquiring the load condition of each container mirror image corresponding to the business category of the subway business request;
and distributing the subway service requests according to the load condition of each container mirror image so as to balance the load of each container mirror image.
4. The subway service processing method according to claim 1, wherein,
when the subway service request is a gate ticket checking request, the receiving the subway service request sent by each terminal device in the subway station and distributing the subway service request to a corresponding container mirror image includes:
Receiving ticket passing ticket checking requests sent by all automatic ticket checking machines in a subway station, and distributing the ticket passing ticket checking requests to corresponding ticket checking container images;
and the running the container mirror image to process the subway service request and return a service processing result to the terminal equipment comprises the following steps:
running the ticket checking container mirror image to process the passing ticket checking request, and returning a processing result of the passing ticket checking request to the automatic ticket checking machine;
when the subway service request is a ticket buying request, the receiving the subway service request sent by each terminal device in the subway station and distributing the subway service request to the corresponding container mirror image includes:
receiving ticket buying requests sent by all automatic ticket vending machines in a subway station, and distributing the ticket buying requests to corresponding ticket buying container images;
and the running the container mirror image to process the subway service request and return a service processing result to the terminal equipment comprises the following steps:
running the ticket buying container mirror image to process the ticket buying request, and returning a ticket buying request processing result to the automatic ticket vending machine;
when the subway service request is a query request, the receiving the subway service request sent by each terminal device in the subway station and distributing the subway service request to a corresponding container mirror image includes:
Receiving inquiry requests sent by all automatic inquiry machines in a subway station, and distributing the inquiry requests to corresponding inquiry container images;
and the running the container mirror image to process the subway service request and return a service processing result to the terminal equipment comprises the following steps:
and running the query container mirror image to process the query request and returning a query request processing result to the automatic query machine.
5. The subway service processing method according to any one of claims 1 to 4, further comprising an industrial personal computer cluster updating step, the industrial personal computer cluster updating step comprising:
acquiring passenger flow information of the subway station, and determining the number of container images to be increased or decreased and the hardware configuration to be increased or decreased of the subway station according to the passenger flow information;
adding or reducing a corresponding number of container images in the subway industrial personal computer cluster;
the feedback requires increased or decreased hardware configuration to enable the staff to increase or decrease the corresponding hardware configuration in the subway industrial personal computer cluster.
6. The subway service processing method according to claim 5, wherein the determining, from the traffic information, the number of container images to be increased or decreased and the hardware configuration to be increased or decreased at the subway station includes:
Inputting the passenger flow information into a target decision tree model;
and determining the number of container images which need to be increased or decreased and the hardware configuration which needs to be increased or decreased of the subway station by utilizing the target decision tree model.
7. The subway service processing method according to claim 6, wherein the subway industrial personal computer cluster updating step further includes, before inputting the passenger flow volume information into the target decision tree model:
constructing an initial decision tree model;
inputting training data into the initial decision tree model to train to obtain a target decision tree model, wherein the training data comprises passenger flow of subway stations, hardware configuration in the subway stations, configuration parameters of a single industrial personal computer, recommended container mirror image number and hardware configuration.
8. The subway service processing method according to claim 5, wherein the industrial personal computer cluster updating step further comprises:
acquiring the running state of the container mirror image;
if the container mirror image cannot normally operate, sending alarm information for indicating that the container mirror image cannot normally operate;
and when the subway station needs to be added with hardware configuration according to the passenger flow information, sending alarm information for indicating that the hardware configuration is insufficient.
9. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs that, when executed by the one or more processors, cause the electronic device to implement the subway service processing method of any one of claims 1 to 8.
10. A computer-readable storage medium storing computer-readable instructions that, when executed by a processor of a computer, cause the computer to perform the subway service processing method according to any one of claims 1 to 8.
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