CN115086317A - Cable monitoring method and device, nonvolatile storage medium and electronic equipment - Google Patents
Cable monitoring method and device, nonvolatile storage medium and electronic equipment Download PDFInfo
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Abstract
The invention discloses a cable monitoring method and device, a nonvolatile storage medium and electronic equipment. Wherein, the method comprises the following steps: acquiring a data processing model from a server; acquiring target data generated by terminal equipment, wherein the terminal equipment is positioned in a cable tunnel, and the target data is cable related data acquired by the terminal equipment; and processing the target data based on the data processing model, and determining the running state of the cable according to the processing result. The invention solves the technical problem that the operation condition of the cable cannot be accurately judged due to the fact that the cable monitoring information cannot be fed back in time in the related technology.
Description
Technical Field
The invention relates to the field of power systems, in particular to a cable monitoring method and device, a nonvolatile storage medium and electronic equipment.
Background
Currently, in the related art, when cable data is monitored and analyzed, a cloud computing manner is generally adopted to analyze the cable data. However, for cables with longer distances, data related to the cables cannot be processed in time when the cables are transmitted with longer distances, so that the operation condition of the cables cannot be determined in real time.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a cable monitoring method and device, a nonvolatile storage medium and electronic equipment, which at least solve the technical problem that the operation condition of a cable cannot be accurately judged due to the fact that cable monitoring information cannot be fed back in time in the related technology.
According to an aspect of an embodiment of the present invention, there is provided a cable monitoring method including: acquiring a data processing model from a server; acquiring target data generated by terminal equipment, wherein the terminal equipment is positioned in a cable tunnel, and the target data is cable related data acquired by the terminal equipment; and processing the target data based on the data processing model, and determining the running state of the cable according to the processing result.
Optionally, before processing the target data based on the data processing model, the cable monitoring method further includes: determining a first computing resource required when processing target data; determining a second computing resource currently available to the edge device; the first computing resource and the second computing resource are compared, and the target data is sent to the server if it is determined that the second computing resource cannot cover the first computing resource.
Optionally, determining the first computing resource required in processing the target data comprises: determining the data quantity and the data type of target data, wherein the data type is a cable operation index corresponding to the target data; determining a processing time length threshold value based on the data category, wherein the processing time length threshold value is the longest allowable time length when the target data is processed; based on the processing duration threshold and the data volume, a first computing resource is determined.
Optionally, processing the target data based on the data processing model includes: dividing a processing process of processing target data into a plurality of subtasks; determining the task data processing amount corresponding to each subtask in the plurality of subtasks; determining the current data processing amount of the edge device; determining the number of subtasks which can be processed by the edge device according to the current processable data volume and the task data processing volume; and under the condition that the number of the plurality of subtasks is larger than the processable subtask number, determining a target number of the subtasks from the plurality of subtasks and sending the target number of the subtasks to the server, wherein the server is used for processing the target number of the subtasks, and the target number is equal to the number of the plurality of the subtasks minus the number of the subtasks processable by the edge device.
Optionally, after the target data is processed based on the data processing model, the cable monitoring method further includes: sending the target data and the processing result to a server, wherein the target data and the processing result are used for training a data processing model; and acquiring the trained data processing model distributed by the server.
According to another aspect of the embodiments of the present invention, there is also provided a cable monitoring system, including a plurality of terminal devices, a plurality of edge devices, and at least one server, where each terminal device in the plurality of terminal devices is connected to an edge device closest to the terminal device, is located in a cable tunnel, and is configured to collect relevant data of an electrical connection to generate target data, and send the target data to the edge device; the edge device is used for acquiring a data processing model from the server; acquiring target data generated by terminal equipment; processing the target data based on the data processing model, and determining the running state of the cable according to the processing result; the server is used for sending the data processing model to the edge equipment and receiving a processing result; and training the data processing model according to the processing result, and sending the trained data processing model to the edge device again.
Optionally, the edge device processes the target data based on the data processing model, including: dividing a processing process of processing target data into a plurality of subtasks; determining the task data processing amount corresponding to each subtask in the plurality of subtasks; determining the current data processing amount of the edge device; determining the number of subtasks which can be processed by the edge equipment according to the current data processing amount and the task data processing amount; and under the condition that the number of the plurality of subtasks is larger than the processable subtask number, determining a target number of the subtasks from the plurality of subtasks and sending the target number of the subtasks to the server, wherein the server is used for processing the target number of the subtasks, and the target number is equal to the number of the plurality of the subtasks minus the number of the subtasks processable by the edge device.
According to another aspect of the embodiments of the present invention, there is also provided an electrical connection monitoring apparatus, which is suitable for an edge device, and includes: the first communication module is used for acquiring a data processing model from the server; the second communication module is used for acquiring target data generated by the terminal equipment, wherein the terminal equipment is positioned in the cable tunnel, and the target data is cable related data acquired by the terminal equipment; and the processing module is used for processing the target data based on the data processing model and determining the running state of the cable according to the processing result.
According to another aspect of the embodiments of the present invention, there is provided a non-volatile storage medium including a stored program, wherein the apparatus in which the non-volatile storage medium is controlled to execute the cable monitoring method when the program is executed.
According to another aspect of the embodiments of the present invention, there is provided an electronic device including a processor for executing a program, wherein the program controls a device in which a nonvolatile storage medium is located to perform a cable monitoring method when the program is executed.
In the embodiment of the invention, a data processing model is obtained from a server; acquiring target data generated by terminal equipment, wherein the terminal equipment is positioned in a cable tunnel, and the target data is cable related data acquired by the terminal equipment; based on the data processing model, the target data are processed, the running state of the cable is determined according to the processing result, the cable data are processed through linkage of the server and the edge device, the purpose of rapidly analyzing data generated under a cable tunnel scene is achieved, the technical effect of timely feeding back monitoring information is achieved, and the technical problem that the running state of the cable cannot be accurately judged due to the fact that the cable monitoring information cannot be fed back timely in the related technology is solved.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a schematic flow chart of a cable monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a cable monitoring system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a cable monitoring and management platform according to an embodiment of the present invention;
FIG. 4 is a diagram of a design architecture of a cable monitoring management platform according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a cloud-edge collaborative model according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a cable monitoring device according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The cloud edge cooperation technology relates to cooperation of edge terminals and cloud infrastructure, namely services, platforms, namely services, and software, namely services. Specifically, resource coordination of a network, virtualized resources, security and the like can be realized between the edge and the cloud; data coordination, intelligent coordination, business arrangement coordination and application management coordination can be realized between the edge and the cloud; and service cooperation can be realized between the edge and the cloud. Therefore, cloud-edge collaboration mainly includes 6 kinds of collaboration technologies: resource collaboration, data collaboration, intelligent collaboration, business orchestration collaboration, application management collaboration, and service collaboration.
The resource cooperation includes cooperation of infrastructure resources such as calculation, storage, network and virtualization provided by the edge node for the value-added network service, and life cycle management cooperation of the edge node device. Specifically, the computing resource cooperation means that resources of a central cloud can be called to supplement and meet the requirements of edge-side applications on the resources under the condition that the edge cloud resources are insufficient, and the resources that the central cloud can provide include bare computers, virtual machines and containers. The network resource cooperation means that there may be multiple connection networks between the edge side and the central cloud, and when the network closest to the edge is congested, the network controller may sense and introduce traffic onto a relatively idle link, and the controller is usually deployed on the central cloud, and the network probe is deployed at the edge of the cloud. The storage resource cooperation means that when the storage in the edge cloud is insufficient, a part of data is stored in the center cloud, and the data is transmitted to the client through the network when the application is needed, so that the storage resource of the edge side is saved.
The security policy cooperation includes that the edge node provides part of security policies including firewall, security group and the like of the access end, and the central cloud provides more complete security policies including flow cleaning, flow analysis and the like. In the process of security policy cooperation, if a central cloud finds that malicious traffic exists in a certain edge cloud, the central cloud can block the malicious traffic, so that the malicious traffic is prevented from spreading in the whole edge cloud platform.
The application management cooperation comprises that the edge node provides a network value-added application deployment and running environment; the cloud end realizes life cycle management of the edge node value-added network application, including pushing, installation, uninstallation, updating, monitoring, logging and the like of the application. The central node can hatch and start the existing application images on different edge clouds to complete high-availability guarantee and hot migration of the applications.
The service management cooperation comprises that the edge node provides a value-added network service application example; the cloud provides the uniform service arrangement capability of the value-added network service, and provides the relevant network value-added service for the client according to the requirement. Due to the shortage of resources on the edge side, the central cloud can perform high-priority processing on some applications, so that the services are classified and processed with different priorities.
The different-domain edge collaboration is included in some applications such as a scene of car networking, for example, in the process that a vehicle is continuously driving, the applications need to be deployed simultaneously in different domains or the applications need to be subjected to hot migration, the central cloud needs to deploy the applications in advance according to the domain requirements of the applications in different periods, and a policy is issued to achieve smooth migration of the applications.
It can be seen that cloud-edge coordination has significant advantages over conventional cloud servers or pure edge computing in data processing, and thus, in accordance with an embodiment of the present invention, a method embodiment of a cable monitoring method is provided based on cloud-edge coordination, it being noted that the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a method for monitoring a cable according to an embodiment of the present invention, which is suitable for use in an edge device, as shown in fig. 1, and includes the following steps:
step S102, acquiring a data processing model from a server;
in some embodiments of the present application, different data processing models are stored in the server, and are suitable for different service scenarios, for example, electrical parameter analysis and cable tunnel environment parameter (such as temperature, humidity, etc.) analysis during a cable operation process respectively correspond to different data processing models.
Step S104, acquiring target data generated by the terminal equipment, wherein the terminal equipment is positioned in the cable tunnel, and the target data is cable related data acquired by the terminal equipment;
in some embodiments of the present application, the data related to the cable collected by the terminal device includes the electrical parameters of the cable itself during operation, and also includes the environmental data in the cable tunnel.
And S106, processing the target data based on the data processing model, and determining the running state of the cable according to the processing result.
In some embodiments of the present application, when the cable monitoring method is used to monitor the state of a cable, the task time delay corresponding to each edge network node may also be determined first. Specifically, the task processing delay is a delay in time taken for each part of data to be rapidly processed at the edge network node. Therefore, the working states of different devices are controlled based on task delay, the pressure of network bandwidth can be reduced, and the energy consumption of intelligent devices at the edge of the network is reduced.
In some embodiments of the present application, before processing the target data based on the data processing model, in order to determine whether the target data is processed by an edge device or a cloud server, the cable monitoring method further includes: determining a first computing resource required when the target data is processed; determining a second computing resource currently available to the edge device; the first computing resource and the second computing resource are compared, and the target data is sent to the server if it is determined that the second computing resource cannot cover the first computing resource.
Specifically, determining a first computing resource required in processing the target data includes: determining the data quantity and the data type of the target data, wherein the data type is a cable operation index corresponding to the target data; determining a processing time threshold based on the data category, wherein the processing time threshold is the longest allowable time when the target data is processed; determining the first computing resource based on the processing duration threshold and the data volume.
In some embodiments of the present application, based on the data processing model, when the target data is processed, the edge device and the cloud server may cooperate to process the target data. Specifically, dividing a processing process for processing the target data into a plurality of subtasks; determining the task data processing amount corresponding to each subtask in the plurality of subtasks; determining the amount of data currently processable by the edge device; determining the number of subtasks which can be processed by the edge device according to the current processable data volume and the task data processing volume; and under the condition that the number of the plurality of subtasks is larger than the processable subtask number, determining a target number of subtasks from the plurality of subtasks and sending the target number of the subtasks to the server, wherein the server is used for processing the target number of the subtasks, and the target number is equal to the number of the plurality of the subtasks minus the processable subtask number of the edge device.
Specifically, equipment in the cable tunnel can generate a large amount of data, great pressure can be caused to the high in the clouds in all uploading, in order to share the pressure of the central cloud node, the edge computing node needs to be responsible for data computing and storage work within the range of the edge computing node, and then the data are gathered to the central cloud server and are used for analyzing and mining the big data, sharing the data, and meanwhile training and upgrading of the algorithm model are completed. The updated algorithm can be pushed to the front-stage updating equipment to complete the closed loop of autonomous learning, and meanwhile, if the edge node breaks down, data processed by the central cloud server cannot be lost.
In addition, as shown in fig. 5, in the cable monitoring model based on cloud edge coordination provided in the embodiment of the present application, a two-hop network framework reaches a Relay node (Relay) from an edge mobile device through one hop, and then reaches a computing access terminal through one hop. In a cable tunnel, an MD may represent an edge termination device, such as: a water level sensor, an environment sensor and a grounding circulation device; relay represents a distributed node, such as an edge physical agent terminal, that is, an edge device; CAP denotes a cloud server of a distributed system.
In some embodiments of the present application, when the computing resources of the edge node are insufficient, the edge node may access the cloud to obtain more sufficient computing resources. The essence of cloud edge collaboration is that the edge nodes are required to effectively manage resources, and cooperate with the cloud end to receive or initiate resource scheduling of the central cloud node. In the cable monitoring model provided by the application, K relay nodes and M cloud computing terminals are assumed. The whole calculation process is modeled as follows:
the mobile device firstly sends a task to the relay node, and the relay divides the task into N subtasks or continues sending the tasks to the CAP according to some load strategies.
In the above formula, it can be known from shannon's theorem that: b is the signal bandwidth in Hertz; c is the maximum information transmission rate in unit time, k is the serial number corresponding to the relay node, P D |h k | 2 Is the average power of the transmitted signal in the channel, in watts, where P D For the transmit power of the transmission, | h k | 2 Energy spectral density, σ, for the kth relay node 2 Is the power of gaussian white noise in watts.
Taking the kth relay node and the mth CAP as an example, the data transmission rate from the MD to the kth relay node can be known according to shannon's theorem, that is, formula (1).
First hop of B fingerChannel bandwidth (Hertz), P, in a network D Which refers to the transmission power (watts), the channel gain follows a normal distribution, and the ambient noise is white gaussian noise by default, thereby obtaining the transmission delay and the energy consumed by the transmission. The transmission delay is the ratio of Lbits to the transmission rate, and the transmission energy consumption is the transmission time multiplied by the transmit power.
After receiving the task, the relay node divides the task into N subtasks. The size of the data amount of each subtask is l n By x nm To indicate whether the nth subtask is assigned to the mth CAP, wherein when x is nm When the value of (1) is 1, the nth subtask is allocated to the mth CAP, and when the value of (0) is 0, the nth subtask is not allocated to the mth CAP. This may be taken as an indication of whether a task is being processed at the edge node.
In some embodiments of the present application, the task offloading policy may be represented by constructing a matrix X, where the dimension of the matrix is N × (M +1), and M ═ 0 represents that the task has been completely processed at the edge end. However, in order to utilize the computing resources more effectively, each subtask can only be computed by one computing node, that is, each row in the matrix has only one element of 1, and then the computation delay model and the computation energy consumption model are divided into two cases, one is completely processed in the edge segment, that is, completely computed by the kth relay, and if the processing is completely processed in the edge segment, the following cases are adopted:
in the above formula, k in kn0 identifies the kth relay node, n represents the nth task, 0 represents that the edge calculation is completed, kn0 represents that the nth task on the kth relay node is completed as a whole,
the parameters which can be set by the target object according to the actual situation are used for reflecting the influence of various factors blocking the propagation in the whole transmission process on the propagation process.
The calculation time is the total calculation time obtained by multiplying the number of cycles required by the CPU to calculate a single byte by the number of bytes of a single task and dividing the result by the frequency of the CPU-cycles. The calculated energy consumption is the time multiplied by a constant defined as the energy consumption per unit time. In another case, the subtasks are distributed to the cloud process, and the model is established as follows:
considering first the data transmission rate, again, using the shannon equation, equation (6), B can be obtained n Representing the bandwidth allocated to subtask n, and the subscript knm means the nth subtask that the kth relay node offloads to the mth CAP in the second hop network, B total Representing the total bandwidth allocated to all tasks. The sum of the bandwidths of all the subtasks is fixed, that is, the bandwidth to which one subtask is allocated is limited.
In the above formula T 2，knm And the delay of the nth subtask unloaded from the kth relay node to the mth CAP in the second-hop network is shown.
Similar to the transmission delay and transmission power consumption defined by the first network, the transmission delay and power consumption of the second hop network are defined. The cloud computing nodes are full of power, and energy consumption is not considered. Therefore, the calculation energy consumption is not considered, only the calculation time delay is considered, the calculation time delay of the cloud can be defined by a formula (5), and the difference from the edge section is that the CPU-cycle frequency (the cycle frequency of the CPU) of the cloud is different.
In some embodiments of the present application, the classification is discussed for the overall latency of the mth compute node in the CAP to complete the assigned task as both m ≠ 0 and m ≠ 0. Namely, the computation delay of the edge node in all the subtasks + the transmission delay of the second hop of the rest subtasks + the computation delay of the rest subtasks in the cloud.
In this model, the number of subtasks received by different CAPs may be different, but different subtasks must arrive one after another, and the sum of the transmission delay of each subtask and the cloud computing delay is calculated. Meanwhile, the condition of parallel computing is considered, namely the time delay caused by the cloud end CAP which finally completes the distributed task is the total time delay T from the relay node to the cloud end node RA . In addition to the above formula
The expression means the number of the M nodes belonging to the cloud computing terminals, M is the number of the cloud computing terminals,
the sum of the overall distributed nodes is represented, that is, the result obtained by the above formula is the synthesis of the transmission delay of the overall distributed nodes.
T total (X)＝T 1,K +T RA (X)(11)
E total (X)＝E 1,K +E RA (X)(12)
In the above three formulas, ERA is the power consumption of the edge node, and Etotal is the total power consumption.
The whole power consumption from the relay node to the cloud node comprises the power consumption of the relay processing subtask + the second hop transmission power consumption as follows:
wherein λ in the above formula is a parameter that can be set by the user for adjusting the weight.
The cost/objective function of the model is a linear function of time delay and power consumption, lambda is a parameter for adjusting weight, and the established optimization problem is as follows:
each parameter in the above formula is the optimized weight parameter.
In some embodiments of the present application, the data model stored in the cloud server may also be updated in real time according to the data processing analysis result. Specifically, after the target data is processed based on the data processing model, the cable monitoring method further includes: sending the target data and the processing result to the server, wherein the target data and the processing result are used for training the data processing model; and acquiring the trained data processing model distributed by the server.
By the cable monitoring method, the cloud edge coordination technology is applied to the data processing task in the cable tunnel scene, real-time or faster data processing and analysis are achieved, network flow is saved, offline operation can be achieved, breakpoint continuous transmission is supported, higher safety protection is provided for local data, the edge computing capability is improved, and the data transmission rate is accelerated.
In some embodiments of the present application, a cable monitoring system is provided as shown in fig. 2. As shown in fig. 2, the system includes a plurality of terminal devices 20, a plurality of edge devices 22, and at least one server 24, wherein each terminal device 20 in the plurality of terminal devices 20 is connected to the edge device 22 closest to the terminal device, is located in a cable tunnel, and is configured to collect relevant data of an electrical connection to generate target data, and send the target data to the edge device 22; an edge device 22 for obtaining a data processing model from a server 24; acquiring target data generated by the terminal device 20; processing the target data based on the data processing model, and determining the running state of the cable according to the processing result; a server 24 for sending the data processing model to the edge device 22 and receiving the processing result; the data processing model is trained according to the processing result, and the trained data processing model is sent to the edge device 22 again.
In some embodiments of the present application, the processing of the target data by the edge device 22 based on the data processing model includes: dividing a processing process of processing target data into a plurality of subtasks; determining the task data processing amount corresponding to each subtask in the plurality of subtasks; determining the amount of data currently processable by the edge device 22; determining the number of subtasks that can be processed by the edge device 22 according to the current data processing amount and the task data processing amount; and determining a target number of the subtasks from the plurality of subtasks to send to the server 24 when the number of the plurality of the subtasks is larger than the processable number of the subtasks, wherein the server 24 is used for processing the target number of the subtasks, and the target number is equal to the number of the plurality of the subtasks minus the number of the subtasks processable by the edge device 22.
In some embodiments of the present application, there is also provided a cable monitoring management platform as shown in fig. 3. As shown in fig. 3, the system includes a cable lean management platform, edge devices and sensing devices for the terminals. As can be seen from fig. 3, the functions of the edge device include device information modeling, edge calculation, security protection, data storage and processing, protocol analysis, device management, and the like. And the edge device comprises a software platform, a hardware platform and a communication interface. And an operating system and a security reinforcement module of the edge device run on the software platform. The hardware platform comprises a processor, a memory, a power supply, a clock and an encryption module. The communication interface comprises an Ethernet interface, an RS485/232 interface, a wireless interface and other expansion interfaces, wherein the wireless interface comprises a Bluetooth interface, a public network interface, a Zigbee interface and the like.
In some embodiments of the present application, there is also provided a cable monitoring management platform as shown in fig. 4. As can be seen from fig. three, the management platform may implement interaction with the cloud server or other platforms, including but not limited to management interaction and business interaction. In addition, the cable monitoring management platform can provide advanced services such as a rule engine, function calculation, flow calculation, AI service and the like, and basic services such as end equipment management, model management, data center and the like realized by message routing.
In some embodiments of the present application, the cable monitoring management platform may further run a program or code such as an acquisition APP or an edge application APP.
In addition, the cable monitoring management platform can also provide system management service and safety service. The system management service comprises framework management, application/container management and edge device management, and the security service comprises security access, data encryption, trusted computing and a security baseline.
In some embodiments of the present application, the operating system running on the cable monitoring management platform includes network management, routing management, configuration management, resource management, and status monitoring functions.
In some embodiments of the present application, a cable monitoring device is also provided. Fig. 6 is a schematic structural diagram of a cable monitoring device provided according to an embodiment of the present application. As shown in fig. 6, the apparatus includes: a first communication module 60, configured to obtain a data processing model from a server; the second communication module 62 is configured to obtain target data generated by the terminal device, where the terminal device is located in the cable tunnel, and the target data is cable-related data acquired by the terminal device; and the processing module 64 is used for processing the target data based on the data processing model and determining the running state of the cable according to the processing result.
It should be noted that the apparatus shown in fig. 6 can be used to perform the method shown in fig. 1, and therefore, the explanation about the cable monitoring method shown in fig. 1 is also applicable to the apparatus shown in fig. 6.
In some embodiments of the present application, a non-volatile storage medium is also provided. The nonvolatile storage medium comprises a stored program, and the device where the nonvolatile storage medium is located is controlled to execute the following cable monitoring method when the program runs: acquiring a data processing model from a server; acquiring target data generated by terminal equipment, wherein the terminal equipment is positioned in a cable tunnel, and the target data is cable related data acquired by the terminal equipment; and processing the target data based on the data processing model, and determining the running state of the cable according to the processing result.
In some embodiments of the present application, there is also provided an electronic device comprising a processor for executing a program, wherein the program when executed performs the following cable monitoring method: acquiring a data processing model from a server; acquiring target data generated by terminal equipment, wherein the terminal equipment is positioned in a cable tunnel, and the target data is cable related data acquired by the terminal equipment; and processing the target data based on the data processing model, and determining the running state of the cable according to the processing result.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A cable monitoring method for use in an edge device, comprising:
acquiring a data processing model from a server;
acquiring target data generated by terminal equipment, wherein the terminal equipment is positioned in a cable tunnel, and the target data is cable related data acquired by the terminal equipment;
and processing the target data based on the data processing model, and determining the running state of the cable according to the processing result.
2. The cable monitoring method of claim 1, wherein prior to processing the target data based on the data processing model, the cable monitoring method further comprises:
determining a first computing resource required when the target data is processed;
determining a second computing resource currently available to the edge device;
the first computing resource and the second computing resource are compared, and the target data is sent to the server if it is determined that the second computing resource cannot cover the first computing resource.
3. The cable monitoring method of claim 2, wherein determining the first computing resource required to process the target data comprises:
determining the data quantity and the data type of the target data, wherein the data type is a cable operation index corresponding to the target data;
determining a processing time threshold based on the data category, wherein the processing time threshold is the longest allowable time when the target data is processed;
determining the first computing resource based on the processing duration threshold and the data volume.
4. The cable monitoring method of claim 1, wherein processing the target data based on the data processing model comprises:
dividing a processing process for processing the target data into a plurality of subtasks;
determining the task data processing amount corresponding to each subtask in the plurality of subtasks;
determining the amount of data currently processable by the edge device;
determining the number of subtasks which can be processed by the edge device according to the current processable data volume and the task data processing volume;
and under the condition that the number of the plurality of subtasks is larger than the processable subtask number, determining a target number of subtasks from the plurality of subtasks and sending the target number of the subtasks to the server, wherein the server is used for processing the target number of the subtasks, and the target number is equal to the number of the plurality of the subtasks minus the processable subtask number of the edge device.
5. The cable monitoring method of claim 1, wherein after processing the target data based on the data processing model, the cable monitoring method further comprises:
sending the target data and the processing result to the server, wherein the target data and the processing result are used for training the data processing model;
and acquiring the trained data processing model distributed by the server.
6. A cable monitoring system comprising a plurality of end devices, a plurality of edge devices, at least one server, wherein,
each terminal device in the plurality of terminal devices is connected with the edge device closest to the terminal device, is positioned in the cable tunnel, and is used for acquiring relevant data of an electric connection to generate target data and sending the target data to the edge device;
the edge device is used for acquiring a data processing model from the server; acquiring target data generated by terminal equipment; processing the target data based on the data processing model, and determining the running state of the cable according to the processing result;
the server is used for sending a data processing model to the edge device and receiving the processing result; and training the data processing model according to the processing result, and sending the trained data processing model to the edge device again.
7. The cable monitoring system of claim 6, wherein the edge device processing the target data based on the data processing model comprises:
dividing a processing process for processing the target data into a plurality of subtasks;
determining the task data processing amount corresponding to each subtask in the plurality of subtasks;
determining the amount of data currently processable by the edge device;
determining the number of subtasks which can be processed by the edge device according to the current processable data volume and the task data processing volume;
and under the condition that the number of the plurality of subtasks is larger than the processable subtask number, determining a target number of subtasks from the plurality of subtasks and sending the target number of the subtasks to the server, wherein the server is used for processing the target number of the subtasks, and the target number is equal to the number of the plurality of the subtasks minus the processable subtask number of the edge device.
8. A cable monitoring device adapted for use in an edge device, comprising:
the first communication module is used for acquiring a data processing model from the server;
the second communication module is used for acquiring target data generated by terminal equipment, wherein the terminal equipment is positioned in a cable tunnel, and the target data is cable related data acquired by the terminal equipment;
and the processing module is used for processing the target data based on the data processing model and determining the running state of the cable according to a processing result.
9. A non-volatile storage medium, comprising a stored program, wherein the program, when executed, controls a device in which the non-volatile storage medium is located to perform the cable monitoring method of any one of claims 1 to 5.
10. An electronic device comprising a processor, wherein the processor is configured to execute a program, wherein the program is configured to execute the cable monitoring method according to any one of claims 1 to 5 when the program is executed.
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