CN108833510B - Message processing method and device - Google Patents
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Abstract
The embodiment of the application discloses a message processing method and device. One embodiment of the method comprises: responding to a to-be-processed message which is monitored in a local area network and is published by a theme subscribed by an objective function, and receiving the to-be-processed message, wherein the to-be-processed message comprises to-be-analyzed data acquired by data acquisition equipment in the Internet of things; analyzing and calculating the data to be analyzed in the message to be processed through the running instance of the target function to obtain a calculation result; generating a message to be issued containing a calculation result, configuring a theme for the message to be issued and issuing the message to be issued; and sending the message to be published to the device subscribing the subject of the message to be published. The implementation mode improves the efficiency and the safety of data analysis and calculation in the Internet of things.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to the technical field of Internet of things, and particularly relates to a message processing method and device.
Background
The internet of things is a network which is formed by combining various information sensing devices, collects various required information such as any object or process needing monitoring, connection and interaction in real time and the internet to realize connection of objects, objects and people and connection of all objects and the network.
In various types of applications of the internet of things, data collected by equipment needs to be processed in a targeted manner according to business requirements. At present, a local device is generally adopted to upload data to a cloud with strong computing power in the processing of large-scale mass data, and a processing function of the cloud is triggered to perform analysis and calculation on the data.
Disclosure of Invention
The embodiment of the application provides a message processing method and device.
In a first aspect, an embodiment of the present application provides a message processing method, including: responding to a to-be-processed message which is monitored in a local area network and is published by a theme subscribed by an objective function, and receiving the to-be-processed message, wherein the to-be-processed message comprises to-be-analyzed data acquired by data acquisition equipment in the Internet of things; analyzing and calculating the data to be analyzed in the message to be processed through the running instance of the target function to obtain a calculation result; generating a message to be issued containing a calculation result, configuring a theme for the message to be issued and issuing the message to be issued; and sending the message to be published to the device subscribing the subject of the message to be published.
In some embodiments, the above method further comprises: reading configuration information of the target function; wherein the configuration information includes: subject routing rule information, scripts or programs that perform functions, types of functions.
In some embodiments, the analyzing and calculating the data to be analyzed in the message to be processed through the running instance of the objective function to obtain the calculation result includes: and in the deployed running environment corresponding to the type of the target function, running the running instance of the target function by taking the data to be analyzed as the parameters to be executed of the target function to obtain a calculation result.
In some embodiments, the configuration information of the objective function further includes resource configuration information of a running instance of the function; in the above-mentioned operating environment corresponding to the type of the target function that has been deployed, operating the operation instance of the target function with the data to be analyzed as the parameter to be executed of the target function to obtain the calculation result, the method includes: and in the deployed running environment corresponding to the type of the target function, taking the data to be analyzed as the parameters to be executed of the target function, calling the available resources indicated by the resource configuration information of the running instance to run the running instance of the target function, and obtaining a calculation result.
In some embodiments, the running instance of the objective function is run in the deployed running environment corresponding to the type of the objective function by using the data to be analyzed as the parameter to be executed of the objective function, and the calculation result is obtained, where the running instance of the objective function includes: starting a local message processing engine to transmit data to be analyzed to a running instance of the target function in a deployed running environment corresponding to the type of the target function; preprocessing data to be analyzed by using the running instance of the target function, transmitting the preprocessed information to an execution script of the target function or a binary program of the target function for calculation, obtaining result data and transmitting the result data back to the running instance of the target function; and converting the result data into a data format supported by the message processing engine through the operation example of the objective function to obtain a calculation result.
In some embodiments, the generating a to-be-published message including a calculation result includes: transmitting the calculation result as the effective load of the message to a local message processing engine through the operation example of the objective function; detecting whether the effective load of a message returned by the running example of the target function is empty or not through a local message processing engine; and if the local message processing engine detects that the effective load of the message returned by the running instance of the target function is not empty, taking the message returned by the running instance of the target function as the message to be issued.
In a second aspect, an embodiment of the present application provides a message processing apparatus, including: the receiving unit is configured to respond to a to-be-processed message which is monitored in a local area network and published by a topic subscribed by an objective function, and receive the to-be-processed message, wherein the to-be-processed message comprises to-be-analyzed data acquired by data acquisition equipment in the Internet of things; the computing unit is configured to analyze and compute the data to be analyzed in the message to be processed through the running example of the target function to obtain a computing result; the publishing unit is configured to generate a message to be published containing the calculation result, configure a theme for the message to be published and publish the message to be published; and the sending unit is configured to send the message to be published to the equipment subscribing to the subject of the message to be published.
In some embodiments, the above apparatus further comprises: a reading unit configured to read configuration information of an objective function; wherein the configuration information includes: subject routing rule information, scripts or programs that perform functions, types of functions.
In some embodiments, the above-mentioned computing unit is further configured to: and in the deployed running environment corresponding to the type of the target function, running the running instance of the target function by taking the data to be analyzed as the parameters to be executed of the target function to obtain a calculation result.
In some embodiments, the configuration information of the objective function further includes resource configuration information of a running instance of the function; the above-mentioned computing unit is further configured to: and in the deployed running environment corresponding to the type of the target function, taking the data to be analyzed as the parameters to be executed of the target function, calling the available resources indicated by the resource configuration information of the running instance to run the running instance of the target function, and obtaining a calculation result.
In some embodiments, the above-mentioned computing unit is further configured to: starting a local message processing engine to transmit data to be analyzed to a running instance of the target function in a deployed running environment corresponding to the type of the target function; preprocessing data to be analyzed by using the running instance of the target function, transmitting the preprocessed information to an execution script of the target function or a binary program of the target function for calculation, obtaining result data and transmitting the result data back to the running instance of the target function; and converting the result data into a data format supported by the message processing engine through the operation example of the objective function to obtain a calculation result.
In some embodiments, the publishing unit is further configured to generate the message to be published including the calculation result as follows: transmitting the calculation result as the effective load of the message to a local message processing engine through the operation example of the objective function; detecting whether the effective load of a message returned by the running example of the target function is empty or not through a local message processing engine; and if the local message processing engine detects that the effective load of the message returned by the running instance of the target function is not empty, taking the message returned by the running instance of the target function as the message to be issued.
In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; a storage device for storing one or more programs which, when executed by one or more processors, cause the one or more processors to implement the message processing method as provided in the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the program, when executed by a processor, implements the message processing method provided in the first aspect.
In a fifth aspect, an embodiment of the present application provides an internet of things system, including: a data acquisition device configured to acquire data; the client device is connected with the data acquisition device and is configured to issue the to-be-processed message containing the data acquired by the data acquisition device according to the theme of the to-be-processed message; an edge computing device comprising one or more processors and a storage device, the storage device having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the message processing method provided by the first aspect.
The message processing method and device in the embodiment of the application receive the message to be processed in response to the message to be processed which is monitored in the local area network and published by the topic subscribed by the objective function, wherein the message to be processed comprises the data to be analyzed which is acquired by the data acquisition equipment in the internet of things, then the data to be analyzed in the message to be processed is analyzed and calculated through the operation example of the objective function to obtain a calculation result, then the message to be published containing the calculation result is generated, the topic is configured for the message to be published and the message to be published is published, and finally the message to be published is sent to the equipment subscribing the topic of the message to be published, so that the data close to the data acquisition equipment is rapidly processed, and the safety of data processing of the internet of things is improved.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present application may be applied;
FIG. 2 is a flow diagram for one embodiment of a message processing method according to the present application;
FIG. 3 is a flow diagram of another embodiment of a message processing method according to the present application;
FIG. 4 is a flow chart illustrating a specific implementation of function computation in a message processing method according to the present application;
FIG. 5 is a schematic diagram of a message processing apparatus according to the present application;
FIG. 6 is a schematic block diagram of a computer system suitable for use in implementing an electronic device of an embodiment of the present application;
FIG. 7 is a schematic diagram of an architecture of an Internet of things system suitable for use in implementing embodiments of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 illustrates an exemplary system architecture 100 to which the message processing method or message processing apparatus of the present application may be applied. Here, the system architecture 100 may be an internet of things based system architecture.
As shown in fig. 1, the system architecture 100 may include devices 101, 102, 103. The devices 101, 102, 103 may be communicatively connected via a network, for example, the devices 101, 102, 103 may be located in the same local area network, and the devices 101, 102, 103 may be connected via a wired or wireless link or a fiber cable.
The device 101 may be a data acquisition device, for example, an acquisition device for acquiring various physical information representing an environment where the device is located, such as temperature, humidity, speed, and time in a scene of the internet of things, and the data acquisition device may acquire data in the form of images, text, and voice.
The device 102 may be a client device, and the client device may be connected to a data collection device. The user end equipment acquires the data acquired by the data acquisition equipment and provides an interface for data analysis and processing for the user of the Internet of things. The client device may further be in communication connection with an edge computing device (e.g., device 103) and/or a cloud server (e.g., server 104), and when receiving a data analysis processing request from a user, the client device may send data collected by the data collection device to the edge computing device or the cloud server for processing. The customer premise equipment can also receive the processing result of the edge computing equipment or the cloud server on the data. Device 102 may have installed thereon a client for communicating with device 103, through which a user may initiate a data processing request.
In some scenarios of the present application, the system architecture described above may further include a server 104 communicatively coupled to at least one of the devices 101, 102, 103 via a wide area network. At least one of the devices 101, 102, 103 may be connected to the server 104 by means of a wired, wireless link, or optical cable, etc.
The server 104 may be a cloud server in the internet of things. The cloud server can provide cloud computing services for the customer premise equipment. The cloud server can deploy a data computing function, and when data requested to be processed by the user side is received, the data is analyzed and computed to obtain a computing result.
It should be noted that the message processing method provided in the embodiment of the present application may be executed by the edge computing device 103, and accordingly, the message processing apparatus may be disposed in the edge computing device 103.
It should be understood that the number of devices, networks, servers in fig. 1 is merely illustrative. There may be any number of devices, networks, servers, as desired for an implementation. In a particular scenario, there may be any number of data collection devices, customer premises equipment, edge computing devices, networks, cloud servers.
With continued reference to FIG. 2, a flow 200 of one embodiment of a message processing method according to the present application is shown. The message processing method comprises the following steps:
In this embodiment, an execution subject (for example, the edge computing device 103 shown in fig. 1) of the message processing method may monitor whether a message of a topic subscribed by an objective function deployed on the execution subject exists in a local area network where the execution subject is located, and if so, the execution subject may receive the message published by the topic subscribed by the objective function as a message to be processed.
Here, the to-be-processed message may include data to be analyzed acquired by a data acquisition device in the internet of things. The objective function may be a function for implementing a specific analysis and calculation function on the data to be analyzed, where the specific analysis and calculation function may be selected according to the user's requirement, for example, if the user wishes to perform a statistical analysis on the data, the objective function is a statistical analysis function. The execution script of the object function or the binary program for executing the function of the object function may be written or compiled by a user in advance and stored in the execution body, and the execution environment of the object function may be deployed in the execution body in advance.
The data to be analyzed may be sensor data acquired by sensors such as a temperature acquisition device, a humidity acquisition device, a pressure sensor, a light sensor, a camera, a voice signal receiver, and the like, or may be data acquired by hardware devices including these sensors and a data processing apparatus, for example, image data obtained by preprocessing an image acquired by a camera by an electronic device having the camera and an image processing chip.
After the user submits the data to be analyzed through the user end device, the user end device can pack the data to be analyzed to generate a message to be processed. And then, the message to be processed can be published in the Internet of things, and a preset theme can be configured for the message to be processed when the message to be processed is published. The execution main body may monitor whether a topic of the objective function subscription deployed thereon is published, and may receive a message to be processed of the topic from the user end device if it is monitored that the topic of the objective function subscription is published.
In some optional implementations of this embodiment, the execution subject may store a topic right list accessible by the execution subject in a connected manner. The topic authority list comprises the corresponding relation between the function and the subscribed topic, and after the published topic is monitored, the function subscribed to the topic can be found in the list as the target function.
The execution main body can start the running instance of the target function of the local message processing engine, the local message processing engine can transmit the data to be analyzed to the running instance of the target function, and the data to be analyzed is analyzed and calculated through the running instance of the target function. Here, the local message processing engine may be a main program that performs a message processing method. Specifically, the local message processing engine may transfer the data to be analyzed to the execution script or the binary program of the target function when the running instance of the target function runs, perform corresponding calculation and processing on the execution script or the binary program of the target function, and return a message to the running instance of the target function as a calculation result after the execution script or the binary program finishes calculation.
After the execution script or the binary program of the function completes the calculation, the calculation result may be transmitted back to the local message processing engine, and the local message processing engine may perform data packing on the calculation result to generate a message to be issued including the calculation result. Specifically, the message to be issued may be generated after the calculation result is encapsulated according to the data transmission protocol between the execution main body and the device issuing the message to be processed. And then, configuring a predefined theme for the message to be published, and publishing the generated message in the internet of things according to a preset theme routing rule in the executive body, so that the device subscribing the theme can receive the message to be published.
The execution subject and the device subscribing the subject of the message to be published can perform data transmission through a subscription-publishing mode. The device subscribing to the topic of the message to be published may be a client device publishing the message to be published, or may be another edge device in the same local area network as the execution subject in the internet of things, such as another client device or another edge computing device. The devices may monitor whether the subscribed topic is published, and if the subscribed topic is monitored, may receive the published message, so that the to-be-published message including the calculation result may be received, that is, in the local area network of the execution main body, each device that has subscribed to the to-be-published message may obtain a result of performing analysis calculation on the to-be-analyzed data sent by the device that publishes the to-be-processed message.
In an actual scenario, a user can publish data to be analyzed through a client installed in a user end device through the user end device, and if an edge computing device is deployed in the same local area network, and a relevant configuration of an objective function is applied to the edge computing device, and an operating environment of the objective function is deployed, a message published by the client can be received through a topic subscribed by the objective function. After the edge computing device completes the computation, a message containing the computation result may be published, and the customer premise equipment may subscribe to the message, thereby obtaining the analysis computation result of the submitted data to be analyzed.
In the message processing method of the embodiment of the application, firstly, a message to be processed which is issued by monitoring a topic subscribed by an objective function in a local area network is responded, and the message to be processed is received, wherein the message to be processed comprises data to be analyzed and acquired by data acquisition equipment in the internet of things; then, analyzing and calculating the data to be analyzed in the message to be processed through the running instance of the target function to obtain a calculation result; then generating a message to be issued containing a calculation result, configuring a theme for the message to be issued and issuing the message to be issued; and finally, the message to be published is sent to the equipment subscribing the subject of the message to be published, so that the data analysis and processing at the near data acquisition equipment end are realized. Because data do not need to be uploaded to the cloud in the data processing process, the safety problems of data leakage or data loss and the like are avoided, meanwhile, the data processing speed does not depend on network performance, and the data processing efficiency is improved.
With continued reference to fig. 3, shown is a flow diagram of another embodiment of a message processing method in accordance with the present application. As shown in fig. 3, a flow 300 of the message processing method of the present embodiment includes the following steps:
In this embodiment, the execution subject of the message processing method may read the stored configuration information of the objective function in advance. The configuration information of the objective function may be pre-configured by the user according to the requirement and stored in the execution body. The configuration information of the objective function may be information for describing a relevant configuration of the objective function. Here, the configuration information of the objective function may include, but is not limited to: subject routing rule information, function calculation configuration information and log processing information of the target function. The topic routing rule information may be used to represent messaging rules for the objective function, including topics to which the objective function subscribes. The function calculation configuration information may include, but is not limited to: function name, type of function, function executor. The function type may represent a programming language type of a program implementing the function, such as Python, node. js, Java, C #, or the like, the function executor may be a script or a program executing the function, the function executor corresponds to the function type, such as the function type is Python, and the function executor may be a Python script implementing the function. The log processing information may be information indicating a processing manner of the function execution log.
The function calculation configuration information may further include execution environment configuration information corresponding to the type of the function. The execution subject can install and deploy the operating environment of the target function according to the read operating environment configuration information.
The information to be processed comprises data to be analyzed acquired by data acquisition equipment in the Internet of things. In this embodiment, if it is detected that a topic subscribed by an objective function is published in a local area network in which an execution subject of the message processing method is located, a message to be processed in the topic may be received. The message to be processed may be issued by a user end device in the same local area network as the execution main body, and include data to be analyzed acquired by the data acquisition device.
After reading the configuration information of the target function, the execution subject may install a runtime environment corresponding to the type of the deployed target function. In this way, the data to be analyzed in the received message to be processed can be used as the calculation object of the objective function, and the data to be analyzed can be input into the objective function for calculation. During calculation, the operation instance of the objective function can be started specifically, and the data to be analyzed is transmitted to the operation instance for calculation to obtain a calculation result.
In some optional implementation manners of this embodiment, the function calculation configuration information may further include resource configuration information of a running instance of the function. The resource configuration information of the running instance of the function is used to characterize the available resources configured for the running instance of the function, and may include, but is not limited to: the number of configuration of the running instance that can be supported, the running instance message handling time limit, the memory and/or CPU resource configuration of the running instance.
After reading the resource configuration information used for indicating the available resources of the running instances in the configuration information of the objective function, a corresponding number of running instances can be started for the objective function according to the resource configuration information. For example, if the configuration number of the supportable runtime instances in the resource configuration information is 3, which indicates that the objective function is allowed to open up at most 3 runtime instances, then at most 3 runtime instances may be opened up for the objective function. When the number of messages needing to be processed is increased, whether the current objective function has an idle running instance or not can be judged, if no idle running instance exists and the number of the currently started running instances reaches the upper limit of 3, the running instances can be immediately reused after being processed; if there are no free running instances and the currently open running instance does not reach the upper limit of 3, a new running instance may be started to process the added message.
Further optionally, if the resource configuration information does not indicate configuration data of the supportable runtime instances, after reading the configuration information, the runtime instances may be configured as an objective function according to a default number of runtime instances to start the runtime instances. For example, each function may default to at least one running instance to ensure that messages are processed in a timely manner when they are sent. Or each function can be set by default not to create an operation instance, that is, the minimum value of the default function allowable operation instance book is 0, the minimum resource required when the function is started can be further ensured after the configuration information is read, and the operation instance is created only when a message needing to be processed is transmitted.
In a further implementation, step 303 may be performed as follows: and in the deployed running environment corresponding to the type of the target function, taking the data to be analyzed as the parameters to be executed of the target function, calling the available resources indicated by the resource configuration information of the running instance to run the running instance of the target function, and obtaining a calculation result. Here, the resource configuration information may further include memory configuration information of the function run instance, and CPU configuration information, that is, memory resource configuration information and CPU resource configuration information available for each run instance.
Specifically, the memory resource configuration information of the function running instance may include a maximum soft limit and a maximum limit of the memory. When the system memory is insufficient, the memory occupied by the running instance exceeding the maximum soft limit can be preferentially recycled, so that the memory occupied by the running instance is close to the maximum soft limit. The maximum limit may be the maximum memory available to the system, and when the system memory is insufficient, the run instance whose occupied memory exceeds the maximum limit may be reset.
The CPU resource configuration information of the function runtime instance may indicate an upper limit of the CPU resources available to the runtime instance, including the length of the available CPU time period and the number of CPUs that can be used within the length of the available CPU time period.
In order to implement the configuration number of the supportable runtime instances of the above functions, the message processing time limit of the runtime instances, and the configuration of the memory and/or CPU resources of the runtime instances, it is necessary that the operating system of the execution main body is a Linux system, and supports Cgroup (control groups). The Cgroup is a mechanism provided by the Linux kernel that can limit, record, and isolate the physical resources (e.g., CPU, memory, input/output interface, etc.) used by a process group.
Resources can be configured for the running instance of the objective function according to the resource configuration information, that is, the resources used during the execution, analysis and calculation of the data to be analyzed by the running instance of the objective function are controlled, so that the utilization efficiency of the resources of the execution main body is improved.
Optionally, the resource configuration information may further include timeout time information of the running instance, a maximum number of processes that can be created by the running instance, and the like. Therefore, the running instance can be cleaned when the running instance exceeds the configured time, so that the effective utilization of resources is ensured, and the excessive consumption of resources caused by the excessive process creation of the running instance is avoided.
Please refer to fig. 4, which shows a flowchart of a specific implementation manner of analyzing and calculating data to be analyzed in a message to be processed and generating a message to be issued in the message processing method according to the present application, that is, a flowchart of an optional implementation manner of step 303 and step 304 in the flowchart 300 of the message processing method. Wherein steps 401 to 403 are a flow of an alternative implementation of step 303.
As shown in fig. 4, in some optional implementations of this embodiment, a process 400 of performing analysis calculation on data to be analyzed in a message to be processed to generate a message to be published including a calculation result may include:
step 401, in the deployed running environment corresponding to the type of the objective function, starting a local message processing engine to transmit data to be analyzed to a running instance of the objective function.
The execution main body may start a local message processing engine, and the specific implementation of the local message processing engine may be a main program of the objective function. The message processing engine may send a message to a running instance of the objective function, where the message may include data to be analyzed that is parsed from the message to be processed.
And 402, preprocessing the data to be analyzed by using the running instance of the target function, transmitting the preprocessed information to the execution script of the target function for calculation, obtaining result data and transmitting the result data back to the running instance of the target function.
After receiving the message of the main program, the running instance of the target function may preprocess the message, specifically, may convert the data to be analyzed in the message into a Json class or a dictionary class, and then may send the message to the function executor. The function executor may be an execution script of the target function or a binary program of the target function, and after receiving the message preprocessed by the run instance, the function executor may execute the function using the data to be analyzed as the parameter to be executed by using the execution script or the binary program, and after the execution is completed, may return a message including result data of the execution of the function to the run instance.
Specifically, when the execution script or the binary program of the target function is calculated, the value of the specific field may be obtained from the data to be analyzed of the dictionary class or the Json class, the analysis calculation is executed, and after the calculation is completed, the result data of the Json class or the dictionary class may be returned to the running instance of the target function.
After receiving the new message returned by the index executor, the running instance of the target function may convert the new message into a message format supported by the local message processing engine, and take the message after the format conversion as a calculation result.
Here, the communication between the local message processing engine and the function execution instance may be in a process communication manner. For example, if the operating system of the execution main body is a Linux system or a MacOS system, the inter-process communication method may include, but is not limited to, a socketpair (socket pair) method, and if the operating system of the execution main body is a Windows system, the inter-process communication method may include, but is not limited to, a Namedpipe (named pipe) method.
Returning to fig. 3, the flow 300 of the message processing method further includes:
and step 304, generating a to-be-published message containing the calculation result, configuring a theme for the to-be-published message and publishing the to-be-published message.
After the calculation result is obtained, the execution main body can issue the message to be issued containing the calculation result in the internet of things according to a preset theme.
With continued reference to fig. 4, steps 404 through 406 are implementation flows of an alternative implementation of step 304. After step 403, the above-mentioned flow 400 may further include: ,
The running instance of the objective function can package the calculation result into data, and the calculation result is packaged into a message according to a data format agreed between the local message processing engine, wherein the effective load of the message is the calculation result obtained by the running instance of the objective function. The running instance of the objective function may then transmit the message to the local message processing engine.
The local message processing engine may receive a message returned by the running instance and determine whether a payload of the message returned by the running instance is empty.
In step 406, if the local message processing engine detects that the payload of the message returned by the running instance of the target function is not empty, the message returned by the running instance of the target function is taken as the message to be issued.
If the local message processing engine detects that the effective load of the message returned by the running instance is not empty, the received message containing the calculation result can be used as the message to be issued, and then a theme can be configured for the message to be issued and issued.
Optionally, when the local message processing engine detects that the payload of the message returned by the running instance is empty, the message returned by the running instance may not be issued. This can prevent the user from issuing a message that does not contain the calculation result desired by the user when the function calculation fails or other errors occur.
As can be seen from fig. 4, the process 400 of analyzing and calculating the data to be analyzed in the message to be processed to generate the message to be issued containing the calculation result implements function calculation on the edge computing device through message transmission between the local message processing engine, the running instance of the objective function, and the execution script or binary program of the objective function.
Returning to fig. 3, after step 304, the flow 300 of the message processing method further includes:
The execution subject and the device subscribing the subject of the message to be published can perform data transmission through a subscription-publishing mode. The device subscribing to the subject of the message to be published may be another device in the same lan as the execution subject in the internet of things, such as a client device or another edge computing device. When monitoring the subscribed topics, the devices can receive messages in the published topics, and therefore calculation results can be obtained.
Step 302 and step 305 in the above embodiment are respectively identical to step 201 and step 204 in the above embodiment, and are not described again here.
As can be seen from fig. 3, the message processing method of this embodiment provides an available operating environment for implementing the function of the objective function by reading the configuration information of the objective function. The user can configure the target function according to the requirement, so that the range of applicable platforms (including systems such as Linux, Windows and Darwin, and CPUs such as arm, x86, mips and powerpc) for local function calculation is expanded. In addition, the minimum memory space required for starting the function running function is small, and the performance requirement on the local edge computing device is lowered.
With further reference to fig. 5, as an implementation of the methods shown in the above-mentioned figures, the present application provides an embodiment of a message processing apparatus, which corresponds to the method embodiments shown in fig. 2 and fig. 3, and which can be applied to various electronic devices.
As shown in fig. 5, the message processing apparatus 500 of the present embodiment includes: a receiving unit 501, a calculating unit 502, a distributing unit 503, and a transmitting unit 504. The receiving unit 501 may be configured to receive a to-be-processed message in response to monitoring the to-be-processed message published by a topic subscribed in an objective function in a local area network, where the to-be-processed message includes to-be-analyzed data acquired by a data acquisition device in the internet of things; the calculating unit 502 may be configured to perform analysis calculation on the data to be analyzed in the message to be processed through the running instance of the objective function, so as to obtain a calculation result; the publishing unit 503 may be configured to generate a message to be published including the calculation result, configure a topic for the message to be published, and publish the message to be published; the sending unit 504 may be configured to send the message to be published to devices subscribing to the subject matter of the message to be published.
In some examples, the apparatus 500 may further include: a reading unit configured to read configuration information of an objective function; wherein the configuration information includes: subject routing rule information, scripts or programs that perform functions, types of functions.
In some optional implementations of the above example, the computing unit 502 may be further configured to: and in the deployed running environment corresponding to the type of the target function, running the running instance of the target function by taking the data to be analyzed as the parameters to be executed of the target function to obtain a calculation result.
In some optional implementations of the foregoing example, the configuration information of the objective function may further include resource configuration information of a running example of the function; the above-mentioned computing unit 502 may be further configured to: and in the deployed running environment corresponding to the type of the target function, taking the data to be analyzed as the parameters to be executed of the target function, calling the available resources indicated by the resource configuration information of the running instance to run the running instance of the target function, and obtaining a calculation result.
In some optional implementations of the above example, the computing unit 502 may be further configured to: starting a local message processing engine to transmit data to be analyzed to a running instance of the target function in a deployed running environment corresponding to the type of the target function; preprocessing data to be analyzed by using the running instance of the target function, transmitting the preprocessed information to an execution script of the target function or a binary program of the target function for calculation, obtaining result data and transmitting the result data back to the running instance of the target function; and converting the result data into a data format supported by the message processing engine through the operation example of the objective function to obtain a calculation result.
In some optional implementations of the foregoing example, the publishing unit 503 may be further configured to generate the to-be-published message including the calculation result as follows: transmitting the calculation result as the effective load of the message to a local message processing engine through the operation example of the objective function; detecting whether the effective load of a message returned by the running example of the target function is empty or not through a local message processing engine; and if the local message processing engine detects that the effective load of the message returned by the running instance of the target function is not empty, taking the message returned by the running instance of the target function as the message to be issued.
The units recited in the apparatus 500 correspond to the various steps in the method described with reference to fig. 2 and 3. Thus, the operations and features described above for the method are equally applicable to the apparatus 500 and the units included therein, and are not described in detail here.
In the message processing apparatus according to the embodiment of the application, the receiving unit receives the message to be processed in response to the message to be processed, which is published by the topic subscribed by the objective function and monitored in the local area network, the message to be processed includes the data to be analyzed, which is acquired by the data acquisition device in the internet of things, the calculating unit then performs analysis and calculation on the data to be analyzed in the message to be processed through the operation example of the objective function to obtain the calculation result, the publishing unit then generates the message to be published including the calculation result, configures the topic for the message to be published and publishes the message to be published, and finally the sending unit sends the message to be published to the device subscribing the topic of the message to be published.
Referring now to FIG. 6, shown is a block diagram of a computer system 600 suitable for use in implementing the electronic device of an embodiment of the present application. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the method of the present application when executed by the central generation unit (CPU) 601. It should be noted that the computer readable medium of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The embodiment of the application also provides an Internet of things system. As shown in fig. 7, the system of internet of things provided by the embodiment of the present application may include a data collection device 701, a client device 702, and an edge computing device 703. The data collection device 701, the customer premises device 702 and the edge computing device may correspond to the devices 101, 102, 103, respectively, in the system architecture shown in fig. 1. The data acquisition device 701 may be configured to acquire data, and may include various sensor devices; the client device 702 may be connected to the data collection device and configured to publish a pending message containing data collected by the data collection device on the topic of the pending message the client device 702 may have a client installed thereon that controls function computation, through which the client device 702 may interact with the edge computing device 703. The edge computing device 703 may be the device shown in fig. 6, and includes one or more processors and a storage device, where the storage device stores one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the message processing method described in the foregoing embodiment.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes a receiving unit, a calculating unit, a distributing unit, and a transmitting unit. The names of the units do not form a limitation on the units themselves in some cases, and for example, a receiving unit may also be described as "receiving a message to be processed in response to monitoring the message to be processed published in the topic subscribed to by the objective function in the local area network".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be present separately and not assembled into the device. The computer readable medium carries one or more programs which, when executed by the apparatus, cause the apparatus to: responding to a to-be-processed message which is monitored in a local area network and is published by a theme subscribed by an objective function, and receiving the to-be-processed message, wherein the to-be-processed message comprises to-be-analyzed data acquired by data acquisition equipment in the Internet of things; analyzing and calculating the data to be analyzed in the message to be processed through the running instance of the target function to obtain a calculation result; generating a message to be issued containing a calculation result, configuring a theme for the message to be issued and issuing the message to be issued; and sending the message to be published to the device subscribing the subject of the message to be published.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (15)
1. A method of message processing, comprising:
responding to a to-be-processed message which is issued by monitoring a topic subscribed by an objective function in a local area network where an edge computing device is located, receiving the to-be-processed message, wherein the to-be-processed message comprises to-be-analyzed data acquired by a data acquisition device in the Internet of things, and the to-be-processed message is issued through a user end device which is located in the same local area network with the edge computing device;
starting a local message processing engine, and analyzing and calculating the data to be analyzed in the message to be processed through the running example of the objective function to obtain a calculation result;
generating a message to be issued containing the calculation result, configuring a theme for the message to be issued and issuing the message to be issued;
and sending the message to be published to the equipment subscribing the subject of the message to be published.
2. The method of claim 1, wherein the method further comprises:
reading the configuration information of the target function;
wherein the configuration information comprises: subject routing rule information, scripts to perform functions, types of functions.
3. The method of claim 2, wherein the performing, by the running instance of the objective function, an analysis calculation on the data to be analyzed in the message to be processed to obtain a calculation result includes:
and in a deployed operating environment corresponding to the type of the target function, operating the operating instance of the target function by taking the data to be analyzed as the parameters to be executed of the target function, and obtaining the calculation result.
4. The method of claim 3, wherein the configuration information of the objective function further includes resource configuration information of a running instance of a function;
the step of running the running instance of the objective function by using the data to be analyzed as the parameters to be executed of the objective function in the deployed running environment corresponding to the type of the objective function to obtain the calculation result includes:
and in the deployed running environment corresponding to the type of the target function, calling available resources indicated by the resource configuration information of the running instance to run the running instance of the target function by taking the data to be analyzed as a parameter to be executed of the target function, and obtaining the calculation result.
5. The method according to claim 3 or 4, wherein the running instance of the objective function is run in the deployed running environment corresponding to the type of the objective function by using the data to be analyzed as a parameter to be executed of the objective function, and the obtaining the calculation result comprises:
starting a local message processing engine to transmit the data to be analyzed to a running instance of the objective function in a deployed running environment corresponding to the type of the objective function;
preprocessing the data to be analyzed by using the running instance of the target function, transmitting the preprocessed information to an execution script of the target function or a binary program of the target function for calculation, obtaining result data and transmitting the result data back to the running instance of the target function;
and converting the result data into a data format supported by the message processing engine through the running example of the objective function to obtain the calculation result.
6. The method of claim 5, wherein the generating a message to be published containing the computation result comprises:
transmitting the calculation result to the local message processing engine as a payload of a message through the running instance of the objective function;
detecting whether the effective load of a message returned by the running example of the target function is empty or not by the local message processing engine;
and if the local message processing engine detects that the payload of the message returned by the running instance of the target function is not empty, taking the message returned by the running instance of the target function as the message to be issued.
7. A message processing apparatus comprising:
the receiving unit is configured to respond to a to-be-processed message which is issued by monitoring a topic subscribed by an objective function in a local area network where an edge computing device is located, receive the to-be-processed message, wherein the to-be-processed message comprises to-be-analyzed data acquired by a data acquisition device in the internet of things, and the to-be-processed message is issued by a user end device which is in the same local area network as the edge computing device;
the calculation unit is configured to start the message processing engine, and analyze and calculate the data to be analyzed in the message to be processed through the running example of the objective function to obtain a calculation result;
the publishing unit is configured to generate a message to be published containing the calculation result, configure a theme for the message to be published and publish the message to be published;
a sending unit configured to send the message to be published to a device subscribing to the subject of the message to be published.
8. The apparatus of claim 7, wherein the apparatus further comprises:
a reading unit configured to read configuration information of the objective function;
wherein the configuration information comprises: subject routing rule information, scripts to perform functions, types of functions.
9. The apparatus of claim 8, wherein the computing unit is further configured to:
and in a deployed operating environment corresponding to the type of the target function, operating the operating instance of the target function by taking the data to be analyzed as the parameters to be executed of the target function, and obtaining the calculation result.
10. The apparatus of claim 9, wherein the configuration information of the objective function further comprises resource configuration information of a running instance of a function;
the computing unit is further configured to:
and in the deployed running environment corresponding to the type of the target function, calling available resources indicated by the resource configuration information of the running instance to run the running instance of the target function by taking the data to be analyzed as a parameter to be executed of the target function, and obtaining the calculation result.
11. The apparatus of claim 9 or 10, wherein the computing unit is further configured to:
starting a local message processing engine to transmit the data to be analyzed to a running instance of the objective function in a deployed running environment corresponding to the type of the objective function;
preprocessing the data to be analyzed by using the running instance of the target function, transmitting the preprocessed information to an execution script of the target function or a binary program of the target function for calculation, obtaining result data and transmitting the result data back to the running instance of the target function;
and converting the result data into a data format supported by the message processing engine through the running example of the objective function to obtain the calculation result.
12. The apparatus of claim 11, wherein the publication unit is further configured to generate the message to be published including the computation result as follows:
transmitting the calculation result to the local message processing engine as a payload of a message through the running instance of the objective function;
detecting whether the effective load of a message returned by the running example of the target function is empty or not by the local message processing engine;
and if the local message processing engine detects that the payload of the message returned by the running instance of the target function is not empty, taking the message returned by the running instance of the target function as the message to be issued.
13. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
14. A computer-readable storage medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, carries out the method according to any one of claims 1-6.
15. An internet of things system, comprising:
a data acquisition device configured to acquire data;
the client device is connected with the data acquisition device and is configured to issue a message to be processed containing the data acquired by the data acquisition device according to the theme of the message to be processed;
an edge computing device comprising one or more processors and storage having one or more programs stored thereon which, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-6.
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| CN110008088A (en) * | 2019-04-10 | 2019-07-12 | 苏州浪潮智能科技有限公司 | A kind of transmission system of sensor information, method, equipment and storage medium |
| CN112583881B (en) * | 2019-09-30 | 2023-11-03 | 北京国双科技有限公司 | Method and system for processing edge data |
| CN111897997A (en) * | 2020-06-15 | 2020-11-06 | 济南浪潮高新科技投资发展有限公司 | Data processing method and system based on ROS operating system |
| CN111897588B (en) * | 2020-06-19 | 2024-04-02 | 深圳奇迹智慧网络有限公司 | Product model configuration method, device, computer equipment and storage medium |
| CN112328231B (en) * | 2020-10-14 | 2024-02-23 | 远江盛邦（北京）网络安全科技股份有限公司 | Quick conversion method between python dictionary and structure |
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