CN113938508B - Low-delay communication method and system for intelligent tower crane remote control - Google Patents
Low-delay communication method and system for intelligent tower crane remote control Download PDFInfo
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Abstract
The embodiment of the application provides a low-delay communication method and system for intelligent tower crane remote control. The method comprises the following steps: the cloud server sends a tower crane task set to the edge server cluster, each edge server identifies and analyzes the received tower crane task set, acquires tasks belonging to a plurality of tower cranes corresponding to the edge server, and performs first task splitting; aiming at the task of each tower crane, the edge server performs second task splitting, performs local calculation on the task with high calculation requirement, and then sends the task to the 5G communication module corresponding to the single tower crane; the data processing module on each tower crane receives the low-calculation-demand task and the calculated high-calculation-demand task forwarded by the 5G communication module in real time so as to execute the corresponding tower crane task. According to the method, the edge computing platform is built between the plurality of tower cranes and the cloud server, the task with high operation amount is locally computed on the edge server, the computing pressure of the cloud server is reduced, the delay time of tower crane control is greatly reduced, and the operation efficiency and the robustness of the system are improved.
Description
Technical Field
The application relates to the technical field of intelligent tower cranes, in particular to a low-delay communication method and system for intelligent tower crane remote control.
Background
At present, the tower crane is basically operated by personnel in a central control room on the tower crane. For the tower crane industry, the current development direction is unmanned tower crane and intelligent tower crane, so that a plurality of technical problems are encountered in the process of industrial upgrading.
At present, in the process of hoisting a plurality of tower cranes simultaneously, as a plurality of control and sensors are arranged on each tower crane, video and other signals shot by a camera are transmitted to a remote cloud server or a control center in real time, the calculation load of the cloud server is huge, the calculation speed is slow, and thus the remote control delay of the tower crane is very high.
Disclosure of Invention
In view of this, the purpose of the present application is to provide a low-delay communication method and system for remote control of an intelligent tower crane, which can specifically solve the problem of high communication delay in the existing multi-tower crane operation.
Based on the above objects, the present application proposes a low-delay communication method for remote control of an intelligent tower crane, comprising:
each tower crane in the intelligent tower crane cluster is provided with a 5G communication module and a data processing module, the intelligent tower crane cluster is divided into a plurality of areas, and an edge server is deployed in each area to form an edge server cluster;
binding and registering each edge server with each tower crane in the area where the edge server is located;
the cloud server sends a tower crane task set to an edge server cluster, each edge server identifies and analyzes the received tower crane task set, acquires tasks belonging to a plurality of tower cranes corresponding to the edge server, and performs first task splitting, and first splits the tasks into different tasks corresponding to single tower cranes;
aiming at the task of each tower crane, the edge server performs second task splitting to split the task into a low-computation-demand task and a high-computation-demand task, the low-computation-demand task is sent to a 5G communication module corresponding to a single tower crane, and the high-computation-demand task is sent to the 5G communication module corresponding to the single tower crane after being subjected to local computation;
and the data processing module on each tower crane receives and analyzes the low-calculation-demand task and the calculated high-calculation-demand task forwarded by the 5G communication module in real time so as to execute the corresponding tower crane task.
Further, the tower crane comprises a luffing trolley, wherein the luffing trolley is used for controlling the lifting height and the transverse position of the lifting hook.
Further, the binding and registering each edge server with each tower crane in the area where the edge server is located includes:
determining the tower crane which establishes a binding relation with the edge server in advance; sending a tower crane state information acquisition request to a 5G communication module of the tower crane; receiving tower crane state information returned by the tower crane based on the tower crane state information acquisition request, wherein the tower crane state information comprises: whether the gear is the P gear, whether the tower crane is flameout or not, and whether the vehicle door is closed or not;
the method comprises the steps that an edge server sends a registration request to a 5G communication module of a tower crane, wherein the registration request comprises a tower crane identifier and a registration type, corresponding subscription information is obtained, and the tower crane corresponding to the tower crane identifier is registered according to the subscription information.
Further, the cloud server sends a tower crane task set to an edge server cluster, each edge server identifies and analyzes the received tower crane task set, acquires tasks belonging to a plurality of tower cranes corresponding to the edge server, performs first task splitting, and first splits the tasks into different tasks corresponding to single tower cranes, including:
the cloud server sends a tower crane task set to the edge server cluster;
each edge server identifies and analyzes the received tower crane task set, extracts a plurality of initial feature vectors of the tower crane task set, and acquires task categories belonging to a plurality of tower cranes corresponding to the edge server according to the plurality of initial feature vectors;
carrying out first task splitting into tasks corresponding to different single tower cranes, wherein the splitting comprises the following steps: splitting subtasks according to the dependency relationship among all subtasks in a complete task by using a method represented by a DAG scheduling graph according to the task categories of the plurality of tower cranes; and processing the subtasks with low front-back coupling degree by using an edge server in a splitting and parallelizing mode, and processing the subtasks with high front-back coupling degree in a serializing mode.
Further, the splitting the second task into a low-computation-demand task and a high-computation-demand task by the edge server for each task of the tower crane, sending the low-computation-demand task to the 5G communication module corresponding to the single tower crane, and sending the high-computation-demand task to the 5G communication module corresponding to the single tower crane after performing local computation, including:
aiming at the task of each tower crane, the edge server performs second task splitting into a low-calculation-demand task and a high-calculation-demand task, and the method comprises the following steps: acquiring a preset first encryption matrix, determining a target line number according to the total number of tasks with low calculation requirements and the total line number of the first encryption matrix, splitting the first encryption matrix according to the line number, and splitting each target line number into a sub-matrix so as to correspond to the tasks with low calculation requirements; acquiring a preset second encryption matrix, determining a target column number according to the total number of tasks with high computing demands and the total column number of the second encryption matrix, splitting the second encryption matrix according to columns, and splitting each target column number into a sub-matrix so as to correspond to the tasks with high computing demands;
and sending the task with low calculation requirement to a 5G communication module corresponding to the single tower crane, and sending the task with high calculation requirement to the 5G communication module corresponding to the single tower crane after carrying out local calculation.
Further, the data processing module on each tower crane receives and parses the low-computation-demand task and the computed high-computation-demand task forwarded by the 5G communication module in real time, so as to execute the corresponding tower crane task, including:
the data processing module on each tower crane receives the low-calculation-demand task forwarded by the 5G communication module in real time, and controls the tower crane to execute the corresponding low-calculation-demand tower crane task after local calculation; and/or
And the data processing module on each tower crane receives the calculated high-calculation-demand task forwarded by the 5G communication module in real time, and directly executes the corresponding high-calculation-demand tower crane task.
Further, the data processing module receives a local data processing request, splits a third task into a low-computation-demand request and a high-computation-demand request, performs local computation on the low-computation-demand request, and sends the high-computation-demand request to an edge computation server of a corresponding area through a 5G communication module of the tower crane;
and the edge server of the corresponding area performs local calculation on the high-calculation-demand request and then sends the high-calculation-demand request to a cloud server.
Based on the above object, the present application further proposes a low-delay communication system for remote control of an intelligent tower crane, comprising:
the equipment deployment module is used for installing a 5G communication module and a data processing module on each tower crane in the intelligent tower crane cluster, dividing the intelligent tower crane cluster into a plurality of areas, and deploying an edge server in each area to form an edge server cluster;
the edge server registration module is used for binding and registering each edge server with each tower crane in the area where the edge server is located;
the system comprises a first task splitting module, a second task splitting module and a first task splitting module, wherein the first task splitting module is used for identifying and analyzing a received tower crane task set by each edge server after a cloud server sends the tower crane task set to an edge server cluster, acquiring tasks belonging to a plurality of tower cranes corresponding to the edge server, and splitting the first task into different tasks corresponding to single tower cranes;
the second task splitting module is used for splitting the second task aiming at the task of each tower crane, splitting the second task into a low-computation-demand task and a high-computation-demand task by the edge server, sending the low-computation-demand task to the 5G communication module corresponding to the single tower crane, and sending the high-computation-demand task to the 5G communication module corresponding to the single tower crane after carrying out local computation;
and the task execution module is used for receiving the low-calculation-demand task and the calculated high-calculation-demand task forwarded by the 5G communication module in real time by the data processing module on each tower crane and analyzing the tasks so as to execute the corresponding tower crane task.
Overall, the advantages of the present application and the experience brought to the user are:
according to the method, the edge computing platform is built between the plurality of tower cranes and the cloud server, the task with high operation amount is locally computed on the edge server, the computing pressure of the cloud server is reduced, the delay time of tower crane control is greatly reduced, and the operation efficiency and the robustness of the system are improved.
Drawings
In the drawings, the same reference numerals refer to the same or similar parts or elements throughout the several views unless otherwise specified. The figures are not necessarily drawn to scale. It is appreciated that these drawings depict only some embodiments according to the disclosure and are not therefore to be considered limiting of its scope.
Fig. 1 shows a schematic diagram of the system architecture principle of the present application.
Fig. 2 shows a flow chart of a low-latency communication method for intelligent tower crane remote control according to an embodiment of the present application.
Fig. 3 shows a block diagram of a low-latency communication system for intelligent tower crane remote control according to an embodiment of the present application.
FIG. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 5 shows a schematic diagram of a storage medium according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 shows a schematic diagram of the system architecture principle of the present application. In the embodiment of the application, as shown in the left part of fig. 1, a construction site is provided with a 5G communication module and a data processing module on each tower crane. The data of each tower crane are collected in real time and sent to the edge server through the 5G communication module. And the edge server receives the tower crane signal and sends the tower crane signal to the cloud server, and the tower crane signal is displayed through the display device. Of course, the cloud server also calculates and forwards the tower crane work tasks through the edge server. By decomposing tasks with high calculation demands and processing the tasks locally at the edge server, the calculation work pressure of the cloud server is greatly reduced, and the control delay of the tower crane can be greatly reduced.
In the embodiment of the invention, the cloud server can be a server with communication capability, and can also be terminal equipment with calculation capability and signal receiving and transmitting capability such as a smart phone, a smart watch and the like.
Fig. 2 shows a flow chart of a low-latency communication method for intelligent tower crane remote control according to an embodiment of the present application. As shown in fig. 2, the low-delay communication method for intelligent tower crane remote control includes:
step 101: and installing a 5G communication module and a data processing module on each tower crane in the intelligent tower crane cluster, dividing the intelligent tower crane cluster into a plurality of areas, and disposing an edge server in each area to form an edge server cluster.
In the embodiment of the invention, the tower crane comprises a luffing trolley, and the luffing trolley is used for controlling the lifting height and the transverse position of the lifting hook.
Step 102: binding and registering each edge server with each tower crane in the area where the edge server is located, including:
determining the tower crane which establishes a binding relation with the edge server in advance; sending a tower crane state information acquisition request to a 5G communication module of the tower crane; receiving tower crane state information returned by the tower crane based on the tower crane state information acquisition request, wherein the tower crane state information comprises: whether the gear is the P gear, whether the tower crane is flameout or not, and whether the control room door is closed or not;
the method comprises the steps that an edge server sends a registration request to a 5G communication module of a tower crane, wherein the registration request comprises a tower crane identifier and a registration type, corresponding subscription information is obtained, and the tower crane corresponding to the tower crane identifier is registered according to the subscription information.
For example, several nearest towers within a preset range from the periphery of a certain edge server are bound. Specifically, after the edge server is started, a registration request is sent to the 5G base station, where the registration request includes a tower crane identifier, a registration type (initial registration), where the tower crane identifier includes a SUPI (Subscription Permanent Identifier, user permanent identifier) or a 5G-GUTI (Globally Unique Temporary UE Identity, globally unique temporary UE identifier), the registration type is used to indicate that the terminal is a tower crane terminal, and may further include a TAI (Tracking Area identity, tracking area identifier) accessed last time, a security parameter, UE 5GC capability, PDU session state, PDU session to be activated, a subsequent request, a MICO ((Mobile Originated connection only) mode preference, and other parameters, the 5G base station selects a suitable AMF (Access and Mobility Management Function ) according to the registration request of the tower crane terminal, and forwards the registration request to the AMF, where the AMF receives the registration request and then selects a suitable UDM (Unified Data Management, unified data management function) to obtain subscription information of the tower crane terminal, where the subscription information of the tower crane terminal indicates that the terminal type is the tower crane terminal is the last time, the AMF receives the subscription information of the tower crane terminal sent by the UDM, generates context information after receiving the subscription information of the tower crane terminal, the AMF sends a PDU session to the edge server, and the AMF is successfully establishes a session to the edge server, and the server is successfully establishes a session with the edge server, and the service is connected to the server is successfully established.
Step 103: the cloud server sends a tower crane task set to an edge server cluster, each edge server identifies and analyzes the received tower crane task set, acquires tasks belonging to a plurality of tower cranes corresponding to the edge server, performs first task splitting, and first splits the tasks into different tasks corresponding to single tower cranes, wherein the method comprises the following steps:
the cloud server sends a tower crane task set to the edge server cluster;
each edge server identifies and analyzes the received tower crane task set, extracts a plurality of initial feature vectors of the tower crane task set, and acquires task categories belonging to a plurality of tower cranes corresponding to the edge server according to the plurality of initial feature vectors;
carrying out first task splitting into tasks corresponding to different single tower cranes, wherein the splitting comprises the following steps: splitting subtasks according to the dependency relationship among all subtasks in a complete task by using a method represented by a DAG scheduling graph according to the task categories of the plurality of tower cranes; and processing the subtasks with low front-back coupling degree by using an edge server in a splitting and parallelizing mode, and processing the subtasks with high front-back coupling degree in a serializing mode.
For example, in this embodiment, for tasks corresponding to different single towers, subtasks are split according to the DAG representation mode, tasks with weaker coupling before and after are split and parallelized, subtasks with stronger coupling before and after are scheduled according to the serialization mode, the specific coupling strength is determined by the dependency relationship between subtask data, and if wide dependency exists between data, the task coupling is considered to be strong.
In the embodiment, under the support of computing power equipment such as an edge resource device CPU or TPU, the task can be classified by using an unsupervised clustering method of K-Means. The provision of n edge servers ES together manages m edge device nodes edei to provide edge computing resources for subtasks { T1, T2 … … Ti } divided by the original task T, where RSnTi represents allocation of subtasks Ti to the edge servers ESm, so that scheduling is performed by the nearest edge server, and a service combination path of t= { T1, T2 … … Ti } is denoted as crs= { RSnTi }. After decomposing the task, the subtasks Ti are deployed to the corresponding resource nodes or VNs in a parallelization mode as much as possible, so that the resource requirements of different subtasks are met, and the upper use limit of the memory, the CPU or other computing resources of some tasks is limited.
Step 104: for each task of the tower crane, the edge server performs second task splitting to split the task into a task with low computing requirement and a task with high computing requirement, sends the task with low computing requirement to a 5G communication module corresponding to a single tower crane, and sends the task with high computing requirement to the 5G communication module corresponding to the single tower crane after performing local computing, including:
aiming at the task of each tower crane, the edge server performs second task splitting into a low-calculation-demand task and a high-calculation-demand task, and the method comprises the following steps: acquiring a preset first encryption matrix, determining a target line number according to the total number of tasks with low calculation requirements and the total line number of the first encryption matrix, splitting the first encryption matrix according to the line number, and splitting each target line number into a sub-matrix so as to correspond to the tasks with low calculation requirements; acquiring a preset second encryption matrix, determining a target column number according to the total number of tasks with high computing demands and the total column number of the second encryption matrix, splitting the second encryption matrix according to columns, and splitting each target column number into a sub-matrix so as to correspond to the tasks with high computing demands;
and sending the task with low calculation requirement to a 5G communication module corresponding to the single tower crane, and sending the task with high calculation requirement to the 5G communication module corresponding to the single tower crane after carrying out local calculation.
For example, the sub-matrix of the first encryption matrix and the sub-matrix of the second encryption matrix are combined, and the combined result is sent to the corresponding edge server as a sub-calculation task; receiving a sub-calculation result returned by the edge server;
verifying the sub-calculation results of each edge server; if the verification passes, synthesizing an encryption calculation result according to the sub-calculation results returned by all the edge servers;
generating an inverse matrix of each basic transformation matrix in the first basic transformation matrix set and the second basic transformation matrix set to obtain a first inverse matrix set and a second inverse matrix set; and decrypting the encryption calculation result by using the first inverse matrix set and the second inverse matrix set to obtain a multiplication result of the first input matrix and the input matrix.
In the context of outsourcing matrix multiplication tasks, the input matrix typically contains some sensitive information, such as tower crane control password data, etc. Thus, when delegating computational tasks to edge servers, the privacy of the input matrices a and B and the output R needs to be protected. In order to blindly input matrices, the present embodiment encrypts matrices a and B using a base transformation matrix.
The basic transformation is the basic operation of the matrix, and comprises the following operation modes:
mode one, rearranging two rows (columns);
multiplying the non-zero number by all row (column) elements of the matrix in mode two;
mode three, add two rows (columns) of the matrix multiplied by the same non-zero number.
By performing these arithmetic operations, the values of the elements in the input matrix will be replaced. Moreover, the complexity of the basis transformation is O (n 2), which is far lower than the complexity of directly performing matrix multiplication on two input matrices. Based on the above, in this embodiment, the input matrix is transformed to implement encryption, so as to implement the outer package of the matrix multiplication operation.
Step 105: the data processing module on each tower crane receives and analyzes the low-calculation-requirement task and the calculated high-calculation-requirement task forwarded by the 5G communication module in real time so as to execute the corresponding tower crane task, and the data processing module comprises:
the data processing module on each tower crane receives the low-calculation-demand task forwarded by the 5G communication module in real time, and controls the tower crane to execute the corresponding low-calculation-demand tower crane task after local calculation; and/or
And the data processing module on each tower crane receives the calculated high-calculation-demand task forwarded by the 5G communication module in real time, and directly executes the corresponding high-calculation-demand tower crane task.
According to the method, the edge computing platform is built between the plurality of tower cranes and the cloud server, the task with high operation amount is locally computed on the edge server, the computing pressure of the cloud server is reduced, the delay time of tower crane control is greatly reduced, and the operation efficiency and the robustness of the system are improved.
An embodiment of the application provides a low-delay communication system for remote control of an intelligent tower crane, where the system is configured to perform the low-delay communication method for remote control of an intelligent tower crane according to the foregoing embodiment, as shown in fig. 3, and the system includes:
the device deployment module 501 is configured to install a 5G communication module and a data processing module on each tower crane in an intelligent tower crane cluster, divide the intelligent tower crane cluster into a plurality of areas, and deploy an edge server in each area to form an edge server cluster;
the edge server registration module 502 is configured to bind and register each edge server with each tower crane in the area where the edge server is located;
the first task splitting module 503 is configured to identify and parse the received tower crane task set by each edge server after the cloud server sends the tower crane task set to the edge server cluster, obtain tasks belonging to multiple tower cranes corresponding to the edge server, and split the first task into tasks corresponding to different single tower cranes;
the second task splitting module 504 is configured to split the second task into a low-computation-demand task and a high-computation-demand task according to the task of each tower crane, send the low-computation-demand task to the 5G communication module corresponding to the single tower crane, and send the high-computation-demand task to the 5G communication module corresponding to the single tower crane after performing local computation;
the task execution module 505 is configured to receive, in real time, the low-computation-demand task and the high-computation-demand task forwarded by the 5G communication module and analyze the low-computation-demand task and the high-computation-demand task, so as to execute the corresponding tower crane task.
The low-delay communication system for remote control of the intelligent tower crane provided by the embodiment of the application and the low-delay communication method for remote control of the intelligent tower crane provided by the embodiment of the application have the same beneficial effects as the method adopted, operated or realized by the stored application program due to the same inventive concept.
The embodiment of the application also provides electronic equipment corresponding to the low-delay communication method for intelligent tower crane remote control provided by the embodiment, so as to execute the low-delay communication method for intelligent tower crane remote control. The embodiments of the present application are not limited.
Referring to fig. 4, a schematic diagram of an electronic device according to some embodiments of the present application is shown. As shown in fig. 4, the electronic device 2 includes: a processor 200, a memory 201, a bus 202 and a communication interface 203, the processor 200, the communication interface 203 and the memory 201 being connected by the bus 202; the memory 201 stores a computer program that can be run on the processor 200, and when the processor 200 runs the computer program, the low-delay communication method for remote control of the intelligent tower crane provided in any of the foregoing embodiments of the present application is executed.
The memory 201 may include a high-speed random access memory (RAM: random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 203 (which may be wired or wireless), the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.
The processor 200 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 200 or by instructions in the form of software. The processor 200 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but may also be a Digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 201, and the processor 200 reads the information in the memory 201, and in combination with its hardware, performs the steps of the above method.
The electronic equipment provided by the embodiment of the application and the low-delay communication method for intelligent tower crane remote control provided by the embodiment of the application have the same beneficial effects as the method adopted, operated or realized by the electronic equipment and the method for intelligent tower crane remote control due to the same inventive concept.
The present embodiment further provides a computer readable storage medium corresponding to the low-latency communication method for remote control of an intelligent tower crane provided in the foregoing embodiment, referring to fig. 5, the computer readable storage medium is shown as an optical disc 30, on which a computer program (i.e. a program product) is stored, where the computer program, when executed by a processor, performs the low-latency communication method for remote control of an intelligent tower crane provided in any of the foregoing embodiments.
It should be noted that examples of the computer readable storage medium may also include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory, or other optical or magnetic storage medium, which will not be described in detail herein.
The computer readable storage medium provided by the above embodiment of the present application and the low-delay communication method for remote control of an intelligent tower crane provided by the embodiment of the present application are the same inventive concept, and have the same advantages as the method adopted, operated or implemented by the application program stored therein.
It should be noted that:
the algorithms and displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, the present application is not directed to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the present application as described herein, and the above description of specific languages is provided for disclosure of preferred embodiments of the present application.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the present application may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the application, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the application and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed application requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this application.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the present application and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
Various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functions of some or all of the components in a virtual machine creation system according to embodiments of the present application may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present application may also be embodied as a device or system program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present application may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of various changes or substitutions within the technical scope of the present application, and these should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (7)
1. A low-latency communication method for intelligent tower crane remote control, comprising:
each tower crane in the intelligent tower crane cluster is provided with a 5G communication module and a data processing module, the intelligent tower crane cluster is divided into a plurality of areas, and an edge server is deployed in each area to form an edge server cluster;
binding and registering each edge server with each tower crane in the area where the edge server is located, including: determining the tower crane which establishes a binding relation with the edge server in advance; sending a tower crane state information acquisition request to a 5G communication module of the tower crane; receiving tower crane state information returned by the tower crane based on the tower crane state information acquisition request, wherein the tower crane state information comprises: whether the gear is the P gear, whether the tower crane is flameout or not, and whether the vehicle door is closed or not; the method comprises the steps that an edge server sends a registration request to a 5G communication module of a tower crane, wherein the registration request comprises a tower crane identifier and a registration type, corresponding subscription information is obtained, and the tower crane corresponding to the tower crane identifier is registered according to the subscription information;
the cloud server sends a tower crane task set to an edge server cluster, each edge server identifies and analyzes the received tower crane task set, acquires tasks belonging to a plurality of tower cranes corresponding to the edge server, performs first task splitting, and first splits the tasks into different tasks corresponding to single tower cranes, wherein the method comprises the following steps: the cloud server sends a tower crane task set to the edge server cluster; each edge server identifies and analyzes the received tower crane task set, extracts a plurality of initial feature vectors of the tower crane task set, and acquires task categories belonging to a plurality of tower cranes corresponding to the edge server according to the plurality of initial feature vectors; carrying out first task splitting into tasks corresponding to different single tower cranes, wherein the splitting comprises the following steps: splitting subtasks according to the dependency relationship among all subtasks in a complete task by using a method represented by a DAG scheduling graph according to the task categories of the plurality of tower cranes; processing the subtasks with low front-back coupling degree by utilizing an edge server in a splitting parallelization mode, and processing the subtasks with high front-back coupling degree in a serialization mode;
for each task of the tower crane, the edge server performs second task splitting to split the task into a task with low computing requirement and a task with high computing requirement, sends the task with low computing requirement to a 5G communication module corresponding to a single tower crane, and sends the task with high computing requirement to the 5G communication module corresponding to the single tower crane after performing local computing, including: aiming at the task of each tower crane, the edge server performs second task splitting into a low-calculation-demand task and a high-calculation-demand task, and the method comprises the following steps: acquiring a preset first encryption matrix, determining a target line number according to the total number of tasks with low calculation requirements and the total line number of the first encryption matrix, splitting the first encryption matrix according to the line number, and splitting each target line number into a sub-matrix so as to correspond to the tasks with low calculation requirements; acquiring a preset second encryption matrix, determining a target column number according to the total number of tasks with high computing demands and the total column number of the second encryption matrix, splitting the second encryption matrix according to columns, and splitting each target column number into a sub-matrix so as to correspond to the tasks with high computing demands; the task with low calculation requirement is sent to a 5G communication module corresponding to a single tower crane, and the task with high calculation requirement is sent to the 5G communication module corresponding to the single tower crane after being subjected to local calculation;
and the data processing module on each tower crane receives and analyzes the low-calculation-demand task and the calculated high-calculation-demand task forwarded by the 5G communication module in real time so as to execute the corresponding tower crane task.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the tower crane comprises an amplitude changing trolley, and the amplitude changing trolley is used for controlling the lifting height and the transverse position of the lifting hook.
3. The method of claim 1 or 2, wherein,
the data processing module on each tower crane receives and analyzes the low-calculation-requirement task and the calculated high-calculation-requirement task forwarded by the 5G communication module in real time so as to execute the corresponding tower crane task, and the data processing module comprises:
the data processing module on each tower crane receives the low-calculation-demand task forwarded by the 5G communication module in real time, and controls the tower crane to execute the corresponding low-calculation-demand tower crane task after local calculation; and/or
And the data processing module on each tower crane receives the calculated high-calculation-demand task forwarded by the 5G communication module in real time, and directly executes the corresponding high-calculation-demand tower crane task.
4. The method of claim 3, wherein the step of,
the data processing module receives a local data processing request, splits a third task into a low calculation demand request and a high calculation demand request, performs local calculation on the low calculation demand request, and sends the high calculation demand request to an edge server of a corresponding area through a 5G communication module of a tower crane of the data processing module;
and the edge server of the corresponding area performs local calculation on the high-calculation-demand request and then sends the high-calculation-demand request to a cloud server.
5. A low latency communication system for intelligent tower crane remote control employing the method of any of claims 1-4, comprising:
the equipment deployment module is used for installing a 5G communication module and a data processing module on each tower crane in the intelligent tower crane cluster, dividing the intelligent tower crane cluster into a plurality of areas, and deploying an edge server in each area to form an edge server cluster;
the edge server registration module is used for binding and registering each edge server with each tower crane in the area where the edge server is located;
the system comprises a first task splitting module, a second task splitting module and a first task splitting module, wherein the first task splitting module is used for identifying and analyzing a received tower crane task set by each edge server after a cloud server sends the tower crane task set to an edge server cluster, acquiring tasks belonging to a plurality of tower cranes corresponding to the edge server, and splitting the first task into different tasks corresponding to single tower cranes;
the second task splitting module is used for splitting the second task aiming at the task of each tower crane, splitting the second task into a low-computation-demand task and a high-computation-demand task by the edge server, sending the low-computation-demand task to the 5G communication module corresponding to the single tower crane, and sending the high-computation-demand task to the 5G communication module corresponding to the single tower crane after carrying out local computation;
and the task execution module is used for receiving the low-calculation-demand task and the calculated high-calculation-demand task forwarded by the 5G communication module in real time by the data processing module on each tower crane and analyzing the tasks so as to execute the corresponding tower crane task.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor runs the computer program to implement the method of any one of claims 1-4.
7. A computer readable storage medium having stored thereon a computer program, wherein the program is executed by a processor to implement the method of any of claims 1-4.
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