CN114979411B - Distributed image processing method, device, equipment and system - Google Patents
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Abstract
The embodiment of the application provides a distributed image processing method, device, equipment and system, wherein the method comprises the following steps: receiving an image processing request sent by a client, and if the task type corresponding to the image processing request is determined to be a real-time task according to the image processing information of the image to be processed included in the image processing request, determining a target task distribution device from a plurality of distributed task distribution devices according to a preset first scheduling rule; the image processing request is sent to the target task distribution equipment, so that the target task distribution equipment determines target image processing equipment from the distributed multiple image processing equipment according to a first preset mode, performs image processing on the image to be processed through the target image processing equipment, and sends image processing result information to the client. Therefore, the method not only can meet the image processing requirement of large concurrency, but also can reduce the waste of equipment resources and maintain the stability of the system.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to a distributed image processing method, device, equipment, and system.
Background
With the advent of the large data age, various data processing services have also been developed, and image data processing services are typically one. The current image processing services such as image comparison and image recognition are generally services provided based on an API (Application Programming Interface ) interface, that is, a client calls the API interface, so that the corresponding image processing service can be directly obtained from a server. However, some image processing services have a high demand on the computational power of the server, and therefore, when the image processing services with high computational power are provided through the API interface, one GPU (Graphics Processing Unit, graphics processor) is required to carry one image processing request. A large number of GPU servers are deployed, which in turn results in a great waste of idle server resources. Therefore, if an image processing service is provided only by way of an API interface, it is difficult to satisfy the current large-concurrency image processing demand.
Disclosure of Invention
The embodiment of the invention aims to provide a distributed image processing method, device, equipment and system, so as to solve the problem that the existing image processing service providing mode is difficult to meet the large concurrent image processing requirement.
In order to solve the above technical problems, embodiments of the present application are implemented as follows:
in a first aspect, an embodiment of the present application provides a distributed image processing method, including:
receiving an image processing request sent by a client, wherein the image processing request comprises image processing information of an image to be processed;
determining a task type corresponding to the image processing request according to the image processing information;
if the task type is a real-time task, determining target task distribution equipment from a plurality of distributed task distribution equipment according to a preset first scheduling rule;
the image processing request is sent to the target task distribution device, so that the target task distribution device determines target image processing devices from a plurality of distributed image processing devices according to a first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client.
In a second aspect, an embodiment of the present application provides a distributed image processing apparatus, including:
the receiving module is used for receiving an image processing request sent by the client; the image processing request comprises image processing information of an image to be processed;
The determining module is used for determining the task type corresponding to the image processing request according to the image processing information;
the first scheduling module is used for determining target task distribution equipment from the distributed multiple task distribution equipment according to a preset first scheduling rule if the task type is a real-time task;
the sending module is used for sending the image processing request to the target task distribution equipment so that the target task distribution equipment can determine target image processing equipment from a plurality of distributed image processing equipment according to a preset mode, and the target image processing equipment can process the image to be processed and send image processing result information to the client.
In a third aspect, an embodiment of the present application provides a distributed image processing system, including a client, a distributed plurality of task scheduling devices, a distributed plurality of task distributing devices, and a distributed plurality of image processing devices;
the client is used for responding to the image processing operation of the user and determining the image processing information of the image to be processed; determining target task scheduling equipment from the distributed multiple task scheduling equipment according to a second preset mode, and sending an image processing request to the target task scheduling equipment according to the image processing information;
The task scheduling device is used for determining a task type corresponding to the image processing request according to the image processing information when the image processing request sent by the client is received; if the task type is a real-time task, determining a target task distribution device from the distributed multiple task distribution devices according to a preset first scheduling rule; transmitting the image processing request to the target task distribution device;
the task distribution device is used for determining a target image processing device from the distributed multiple image processing devices according to a first preset mode when the image processing request sent by the task scheduling device is received, and sending the image processing request to the target image processing device;
the image processing device is used for carrying out image processing on the image to be processed according to the image processing request when the image processing request sent by the task distribution device is received, and sending image processing result information to the client.
In a fourth aspect, an embodiment of the present application provides a distributed image processing apparatus, including a processor, a memory, and a computer program stored on the memory and executable on the processor, the computer program implementing the steps of the distributed image processing method according to the first aspect when executed by the processor.
In a fifth aspect, embodiments of the present application provide a computer readable storage medium having a computer program stored thereon, which when executed by a processor, implements the steps of the distributed image processing method according to the first aspect.
When an image processing request sent by a client is received, if a corresponding task type is determined to be a real-time task according to image processing information of an image to be processed included in the image processing request, determining a target task distribution device from a plurality of distributed task distribution devices according to a preset first scheduling rule; and sending the image processing request to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to the first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client. Therefore, the distributed devices are reasonably scheduled to realize image processing, so that the image processing requirement of large concurrency can be met, the waste of device resources can be reduced, and the stability of the system is maintained. In addition, the corresponding processing is carried out according to the task type corresponding to the image processing request, so that the hierarchical processing of the request is realized, and the user experience can be improved under the condition of large concurrency of the image processing request, thereby maintaining and even improving the service volume.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a first method for processing a distributed image according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a second method for processing a distributed image according to an embodiment of the present application;
fig. 3 is a third flowchart of a distributed image processing method according to an embodiment of the present application;
fig. 4 is a schematic block diagram of a distributed image processing apparatus according to an embodiment of the present application;
FIG. 5 is a schematic diagram illustrating the components of a distributed image processing system according to an embodiment of the present application
Fig. 6 is a schematic structural diagram of a distributed image processing apparatus according to an embodiment of the present application.
Detailed Description
In order to make the technical solution of the present invention better understood by those skilled in the art, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, shall fall within the scope of the invention.
Fig. 1 is a schematic flow chart of a first method for processing a distributed image according to an embodiment of the present invention, where the method in fig. 1 can be executed by distributed task scheduling devices disposed in different areas; the task scheduling device can be a terminal device such as a mobile phone, a tablet computer, a desktop computer, a portable notebook computer and the like, and can also be a server. As shown in fig. 1, the method at least comprises the following steps:
step S102, receiving an image processing request sent by a client; wherein the image processing request includes image processing information of an image to be processed;
specifically, a client related to image processing may be installed in a terminal device of a user, where the client may be an independent Application (APP), an applet embedded in another Application, a web Application, or the like. When a user needs to perform image processing, the client can be operated; correspondingly, the client side responds to image processing operation of a user and determines image processing information of an image to be processed; and determining target task scheduling equipment from the distributed multiple task scheduling equipment according to a second preset mode, and sending an image processing request to the target task scheduling equipment according to the image processing information. When the distributed task scheduling device is determined to be the target task scheduling device by the client, receiving an image processing request sent by the client and carrying out subsequent processing.
The image processing information comprises image processing type information, image attribute information of an image to be processed, an IP address of a client and the like. The image processing type information characterizes operations to be executed on the image to be processed, such as downloading, uploading, feature extraction, image recognition and the like; the image attribute information may include image identification information of an image to be processed, an image size, and the like. The second preset mode can be set by itself according to needs in practical application, for example, can be a route automatic distribution mode, or can be that a client obtains an IP address of each task scheduling device, determines a distance from each task scheduling device according to the obtained IP address, compares each determined distance to obtain a minimum distance, and determines a task scheduling device corresponding to the minimum distance as a target task scheduling device.
Step S104, determining a task type corresponding to the image processing request according to the image processing information;
in order to improve user experience under the condition of meeting the requirement of image processing with large concurrency, in the embodiment of the application, task classification is performed on each image processing request, and corresponding processing is performed according to task types. The task types may include a real-time task and a delayed task, where the real-time task characterizes the image processing request that needs to be processed immediately, and the delayed task characterizes the image processing request that may be processed for a period of time.
Step S106, if the task type is a real-time task, determining target task distribution equipment from a plurality of distributed task distribution equipment according to a preset first scheduling rule;
the distributed image processing system corresponding to the distributed image processing method provided by the embodiment of the application not only comprises a plurality of distributed task scheduling devices with a task scheduling function, but also comprises a plurality of distributed task distributing devices and a plurality of distributed image processing devices. The task distribution device has a task distribution function and can perform distribution processing on an image processing request of which the task type is a real-time task so as to distribute the image processing request to the determined target image processing device. The image processing device is used for providing an image processing service, and can perform corresponding processing on an image to be processed according to the acquired image processing request, such as downloading processing, feature comparison processing and the like. It should be noted that each device may integrate at least one function, for example, a certain device has not only a task scheduling function but also a task distributing function, that is, the device is both a task scheduling device and a task distributing device, so that waste of bandwidth resources caused by transfer of image resources in an image processing process can be reduced, and real-time processing speed can be ensured. In practical application, the integration of the functions can be realized by adopting the container technology means such as a virtual machine, a dock mirror image and the like.
Step S108, the image processing request is sent to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to a first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client.
Specifically, when the target task distribution device receives the image processing request, the target image processing device is determined from the distributed multiple image processing devices according to the first preset mode, and the image processing request is sent to the target image processing device. The target image processing device performs image processing on the image to be processed according to the received image processing request, and sends image processing result information to the corresponding client according to the information such as the IP address or the client identifier of the client in the image processing request. The first preset mode may be set automatically according to needs in practical application, for example, may be an automatic routing distribution mode, or may be that the target task distribution device obtains IP addresses of the image processing devices connected to the target task distribution device, determines distances between the target task distribution device and the image processing devices connected to the target task distribution device according to the obtained IP addresses, compares the determined distances to obtain minimum distances, and determines the image processing device corresponding to the minimum distances as the target image processing device.
It should be noted that the image processing request may or may not include the image to be processed. For example, when the image processing request is for requesting an upload, image recognition, or the like of an image to be processed, the image processing request may include the image to be processed provided by the user; when the image processing request is for requesting downloading, viewing, etc., the image processing request may not include an image to be processed, which is stored in a designated storage area, such as a cloud, etc. Correspondingly, when the image processing request does not include the image to be processed, the target image processing device acquires the corresponding image to be processed from the designated storage area according to the image identification information of the image to be processed included in the image processing request, and correspondingly processes the acquired image to be processed according to the operation type information in the image processing request.
In one or more embodiments of the present application, when an image processing request sent by a client is received, if it is determined that a corresponding task type is a real-time task according to image processing information of an image to be processed included in the image processing request, determining a target task distribution device from a plurality of distributed task distribution devices according to a preset first scheduling rule; and sending the image processing request to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to the first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client. Therefore, the distributed devices are reasonably scheduled to realize image processing, so that the image processing requirement of large concurrency can be met, the waste of device resources can be reduced, and the stability of the system is maintained. In addition, the corresponding processing is carried out according to the task type corresponding to the image processing request, so that the hierarchical processing of the request is realized, and the user experience can be improved under the condition of large concurrency of the image processing request, thereby maintaining and even improving the service volume.
Because the distributed multiple task distribution devices are distributed in different areas, such as different cities, different places of the same city, and the like, in order to improve the processing efficiency of the image processing request with the task type being a real-time task, in one or more embodiments of the present application, the target task distribution device is determined based on the transmission bandwidth of the task distribution device and the transmission delay between the task scheduling device and the task distribution device. Specifically, as shown in fig. 2, step S106 may include the following steps S106-2 to S106-6:
step S106-2, if the task type is a real-time task, acquiring a transmission bandwidth and a transmission delay corresponding to each task distribution device in the distributed multiple task distribution devices;
specifically, the task scheduling device sends information acquisition requests to the connected task distribution devices respectively, and records the sending time of the information acquisition requests. And after receiving the information acquisition request, the task distribution equipment transmits response data to the task scheduling equipment according to the current transmission bandwidth of the task distribution equipment. The task scheduling device receives the response data sent by the task distribution device, records the receiving time, determines the transmission delay between the task scheduling device and the corresponding task distribution device according to the recorded sending time and the recorded receiving time, and acquires the transmission bandwidth of the corresponding task distribution device from the received response data.
Step S106-4, determining a second weight corresponding to each task distribution device according to the acquired transmission bandwidth and transmission delay;
optionally, in one or more embodiments of the present application, the second weight is determined based on a preset correspondence. Specifically, step S106-4 may include: determining a third sub-weight corresponding to each acquired transmission bandwidth based on a corresponding relation between the preset transmission bandwidth and the third sub-weight; determining a fourth sub-weight corresponding to each acquired transmission delay based on a corresponding relation between the preset transmission delay and the fourth sub-weight; and determining a second weight corresponding to each task distribution device according to the determined third sub-weight and fourth sub-weight.
The corresponding relation between the transmission bandwidth and the third sub-weight, and the corresponding relation between the transmission delay and the fourth sub-weight can be set according to the needs in practical application. As an example, the third sub-weight is denoted as Wb and the fourth sub-weight is denoted as Wt; when the transmission bandwidth is less than 100M, the corresponding third sub-weight wb=0.8; when the transmission bandwidth is between 100M and 500M (including 100M and 500M), the corresponding third sub-weight wb=1; when the transmission bandwidth is greater than 500M, the corresponding third sub-weight wb=1.2. When the transmission delay is less than 10ms, the corresponding fourth sub-weight wt=1; when the transmission delay is between 10ms and 100ms (including 10ms and 100 ms), the corresponding fourth sub-weight wt=0.9; when the transmission delay is greater than 100ms, the corresponding fourth sub-weight wt=0.7. The second weight is denoted as W2, and may be w2=wb+wt, that is, the third sub-weight and the second sub-weight are added, and the result of the adding process is determined as the second weight; it may also be w2=a+wb+c+ws, where a and c are coefficients, and specific values thereof may be set by themselves in practical applications.
In one or more embodiments of the present application, the second weight may also be determined according to a preset calculation manner. Specifically, step S106-4 may include: and calculating a second weight corresponding to each task distribution device based on the transmission bandwidth and the transmission delay corresponding to each task distribution device according to a preset calculation mode. The calculation manner may be set by itself according to needs in practical applications, for example, the second weight is denoted as W2, w2=d represents transmission bandwidth+f represents transmission delay, where 0< d <1,0< f <1, and so on.
Step S106-6 of determining a target task distribution device for performing distribution processing on the image processing request from the plurality of task distribution devices according to the second weight.
Specifically, comparing the obtained second weights to obtain the maximum second weight; and determining the task distribution device corresponding to the largest second weight as a target task distribution device for performing distribution processing on the image processing request.
Therefore, the target task distribution equipment is determined from the distributed multiple task distribution equipment based on the transmission bandwidth and the transmission delay corresponding to each task distribution equipment, so that the transmission time of the image processing requests among the equipment can be effectively reduced, the target task distribution equipment can be ensured to have enough physical resources to distribute and process the image processing requests, the effective scheduling of the task distribution equipment is realized, the waste of equipment resources is avoided, the processing efficiency of the image processing requests is improved, and the real-time image processing requirements are met.
The real-time requirements of image processing tend to be different in view of the different image processing types and different sizes of images. Taking the image processing type as an example for illustration, for example, when the user wants to upload the image in the mobile phone to the network disk for storage, that is, the image processing type is uploading, the user may not pay attention to when the uploading is completed, that is, the real-time requirement is low; and for example, when the user handles the business, the user performs image comparison to realize identity authentication, namely the image processing type is image comparison, and the user hopes to obtain the image comparison result as soon as possible, so that the business handling is completed as soon as possible, namely the real-time performance needs to be higher. Based on this, as shown in fig. 3, step S104 may include the following steps S104-2 to S104-4, and correspondingly, step S106 may include the following step S106-8, and the method may further include the following steps S110 to S112:
step S104-2, determining a first weight corresponding to the image processing request according to the image processing type information and the image attribute information included in the image processing information;
specifically, based on a corresponding relation between preset image processing type information and first sub-weights, determining the first sub-weights corresponding to the image processing type information included in the image processing information; determining a second sub-weight corresponding to the image attribute information included in the image processing information according to a preset determination mode of the second sub-weight; and determining the first weight corresponding to the image processing request according to the determined first sub weight and the determined second sub weight.
The first sub-weight corresponding to the image processing type, the second sub-weight corresponding to the image attribute information and the determination mode of the first weight can be set according to the needs in practical application. As an example, the first sub-weight corresponding to the image processing type of image search, image comparison, etc. is 1, and may be denoted as wr=1, and the first sub-weight corresponding to the image processing type of uploading, downloading, viewing, etc. is 0.5, and may be denoted as wr=0.5. The second sub-weight may be determined in a manner of ws=1.2-0.1 x, where x is the size of the image to be processed, and the unit is Mb or the like. The first weight is denoted as W1, and may be w1=wr+ws, that is, the first sub-weight and the second sub-weight are added, and the result of the adding process is determined as the first weight; it may also be w1=mwr+n Ws, where m and n are coefficients, and specific values thereof may be set by themselves, and the like.
Step S104-4, determining whether the first weight is smaller than a first preset weight, if yes, determining that the task type corresponding to the image processing request is a delay task, and executing step S110; if not, determining that the task type corresponding to the image processing request is a real-time task, and executing step S106-2.
The first preset weight may be set as required in practical application, for example, 1.6.
Step S106-8, determining target task distribution equipment from a plurality of distributed task distribution equipment according to a preset first scheduling rule;
the process of determining the target task distribution device according to the first scheduling rule may refer to the foregoing related description, and the repetition is not repeated here.
Step S110, determining a target message queue from a plurality of distributed message queues according to a preset second scheduling rule;
the second scheduling rule can be set automatically according to the needs in practical application, for example, a route automatic distribution mode can be adopted; the distance between the message queue and each message queue can be determined according to the preset address information of each message queue, the determined distances are compared to obtain the minimum distance, and the message queue corresponding to the minimum distance is determined as a target message queue.
Step S112, the image processing request is saved to the target message queue, so that the image processing device corresponding to the target message queue performs image processing on the image to be processed according to the image processing request in the target message queue, and sends the image processing result information to the client.
In this embodiment of the present application, each message queue may correspond to a plurality of image processing apparatuses, and each image processing apparatus may access a corresponding message queue at intervals of a preset first time interval, or access a corresponding message queue when reaching a preset time point, and process an image processing request in the accessed message queue. Wherein, the preset first time interval or the preset time point of each image processing device can be the same or different.
Further, in order to avoid that the same image processing request is repeatedly processed, in one or more embodiments of the present application, when the image processing device obtains the image processing request to be processed from the corresponding message queue, the status identifier of the corresponding image processing request is set to the first identifier that indicates that the image processing request is locked through the message queue management module, and when the image processing device obtains the processing completion information from the image processing device, the status identifier is set to the second identifier that indicates that the image processing request is processed, or the corresponding image processing request is removed from the message queue.
Further, in order to enhance user experience, in one or more embodiments of the present application, a processing priority may be set for an image processing request with a task type that is a delayed task, and the image processing requests are sequentially processed in order of priority from top to bottom. Specifically, the image processing information may further include user information of the user, and step S112 may include: determining priority information of the image processing request according to user information included in the image processing request, correspondingly storing the determined priority information in the target message queue in the image processing request, so that image processing equipment corresponding to the target message queue sequentially performs image processing on corresponding images to be processed according to the corresponding image processing request based on the priority information in the target message queue, and sending image processing result information to a client.
The specific content of the user information can be set according to the needs in practical application, for example, the user information can be information representing that the user is a common user, a common member user, a super member user and the like, the priority of an image processing request sent by the common member user is higher than that of an image processing request sent by the common user, and the priority of the image processing request sent by the common member user is lower than that of the image processing request sent by the super member user. The user information may also be gradation information or the like determined by evaluation according to the image processing situation of the user.
Further, considering that in practical application, for an image processing request with a task type being a delay task, a user may repeatedly send the image processing request, for example, the user submits the image processing request with an image operation type being uploading in Beijing in the first week, the user goes on business to Shenzhen in the third week and finds that the image to be processed is not yet uploaded, and therefore the user submits the image processing request again in Shenzhen. Since the user is characterized to a certain extent that the user wants the image processing request to be processed as soon as possible when the user repeatedly submits the same image processing request a plurality of times. Based on this, in one or more embodiments of the present application, the method may further include:
If the message queue management module determines that the image processing request meets the preset priority adjustment condition, adjusting the priority information of the corresponding image processing request so that the image processing equipment performs image processing on the corresponding image to be processed according to the adjusted priority information.
Specifically, as in the foregoing example, the user may repeatedly send the image processing request through the client at a different location, and the target message queue determined based on the preset second scheduling rule may be different each time the task scheduling module receives the repeated image processing request, and thus, the repeated image processing requests may be saved to different target message queues. Based on the image processing requests in each message queue are compared at intervals of a preset second time interval through the message queue management module, and if the repeated image processing requests are determined to exist, the number of the repeated image processing requests is counted; if the counted number is not less than the preset number, determining that the repeated image processing requests meet the priority adjustment condition, and adjusting priority information corresponding to the image processing requests stored first according to the sequence of the storage time so as to increase the priority, thereby the image processing requests are processed preferentially; and deleting other image processing requests from the repeated image processing requests. Therefore, by applying the message queue and carrying out hierarchical processing on the image processing request with the task type of the delay task, the system pressure under the condition of request quantity burst can be relieved, the utilization rate of computing power resources of the image processing equipment can be improved, the user experience can be improved, and the loss of service can be reduced.
In the distributed image processing method provided by the embodiment of the application, when an image processing request sent by a client is received, if the corresponding task type is determined to be a real-time task according to the image processing information of the image to be processed included in the image processing request, determining a target task distribution device from a plurality of distributed task distribution devices according to a preset first scheduling rule; and sending the image processing request to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to the first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client. Therefore, the distributed devices are reasonably scheduled to realize image processing, so that the image processing requirement of large concurrency can be met, the waste of device resources can be reduced, and the stability of the system is maintained. In addition, the corresponding processing is carried out according to the task type corresponding to the image processing request, so that the hierarchical processing of the request is realized, and the user experience can be improved under the condition of large concurrency of the image processing request, thereby maintaining and even improving the service volume.
The embodiment of the invention also provides a distributed image processing device, which can be applied to task scheduling equipment. Fig. 4 is a schematic block diagram of a distributed image processing apparatus according to an embodiment of the present application, and as shown in fig. 4, the data query apparatus includes:
a receiving module 201, configured to receive an image processing request sent by a client; the image processing request comprises image processing information of an image to be processed;
a determining module 202, configured to determine a task type corresponding to the image processing request according to the image processing information;
the first scheduling module 203 is configured to determine a target task distribution device from a plurality of distributed task distribution devices according to a preset first scheduling rule if the task type is a real-time task;
and the sending module 204 is configured to send the image processing request to the target task distribution device, so that the target task distribution device determines a target image processing device from a plurality of distributed image processing devices according to a preset manner, performs image processing on the image to be processed through the target image processing device, and sends image processing result information to the client.
Optionally, the image processing information includes image processing type information and image attribute information of the image to be processed; accordingly, the determining module 202 is specifically configured to:
determining a first weight corresponding to the image processing request according to the image processing type information and the image attribute information;
determining whether the first weight is smaller than a first preset weight;
if yes, determining that the task type corresponding to the image processing request is a delay processing task;
if not, determining that the task type corresponding to the image processing request is a real-time task.
Optionally, the determining module 202 is further specifically configured to:
determining a first sub-weight corresponding to image processing type information included in the image processing information based on a corresponding relation between preset image processing type information and the first sub-weight;
determining a second sub-weight corresponding to the image attribute information included in the image processing information according to a preset determination mode of the second sub-weight;
and determining a first weight corresponding to the image processing request according to the determined first sub-weight and the determined second sub-weight.
Optionally, the first scheduling module 203 is specifically configured to:
Acquiring transmission bandwidth and transmission delay corresponding to each task distribution device in a plurality of distributed task distribution devices;
determining a second weight corresponding to each task distribution device according to the transmission bandwidth and the transmission delay;
and determining a target task distribution device for performing distribution processing on the image processing request from the plurality of task distribution devices according to the second weight.
Optionally, the first scheduling module 203 is further specifically configured to:
determining a third sub-weight corresponding to each acquired transmission bandwidth based on a corresponding relation between the preset transmission bandwidth and the third sub-weight; determining fourth sub-weights corresponding to the acquired transmission delays based on the corresponding relation between the preset transmission delays and the fourth sub-weights; determining a second weight corresponding to each task distribution device according to the third sub-weight and the fourth sub-weight;
or,
and calculating a second weight corresponding to each task distribution device based on the transmission bandwidth and the transmission delay corresponding to each task distribution device according to a preset calculation mode.
Optionally, the apparatus further comprises: a second scheduling module;
The second scheduling module determines a target message queue from a plurality of distributed message queues according to a preset second scheduling rule if the determining module 202 determines that the task type is a delay processing task; the method comprises the steps of,
and storing the image processing request to the target message queue, so that the image processing equipment corresponding to the target message queue performs image processing on the image to be processed according to the image processing request in the target message queue, and sends image processing result information to the client.
When an image processing request sent by a client is received, if the corresponding task type is determined to be a real-time task according to image processing information of an image to be processed included in the image processing request, determining target task distribution equipment from a plurality of distributed task distribution equipment according to a preset first scheduling rule; and sending the image processing request to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to the first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client. Therefore, the distributed devices are reasonably scheduled to realize image processing, so that the image processing requirement of large concurrency can be met, the waste of device resources can be reduced, and the stability of the system is maintained. In addition, the corresponding processing is carried out according to the task type corresponding to the image processing request, so that the hierarchical processing of the request is realized, and the user experience can be improved under the condition of large concurrency of the image processing request, thereby maintaining and even improving the service volume.
The distributed image processing device provided in the embodiment of the present application can implement each process in the embodiment corresponding to the above distributed image processing method, and in order to avoid repetition, the description is omitted here.
It should be noted that, the distributed image processing apparatus provided in the embodiment of the present application and the distributed image processing method provided in the embodiment of the present application are based on the same inventive concept, so that the implementation of the embodiment may refer to the implementation of the foregoing distributed image processing method, and the repetition is not repeated.
The embodiment of the invention also provides a distributed image processing system based on the same technical conception. Fig. 5 is a schematic diagram of a distributed image processing system according to an embodiment of the present application, and as shown in fig. 5, the distributed image processing system includes: a client 301, a distributed plurality of task scheduling devices 302, a distributed plurality of task distribution devices 303, and a distributed plurality of image processing devices 304;
the client 301 is configured to determine image processing information of an image to be processed in response to an image processing operation of a user; determining a target task scheduling device 302 from the distributed multiple task scheduling devices 302 according to a second preset mode, and sending an image processing request to the target task scheduling device 302 according to the image processing information;
The task scheduling device 302 is configured to determine, when receiving the image processing request sent by the client 301, a task type corresponding to the image processing request according to the image processing information; if the task type is a real-time task, determining a target task distribution device 303 from the distributed multiple task distribution devices 303 according to a preset first scheduling rule; transmitting the image processing request to the target task distribution device 303;
the task distribution device 303 is configured to, when receiving the image processing request sent by the task scheduling device 302, determine a target image processing device 304 from the distributed multiple image processing devices 304 according to a first preset manner, and send the image processing request to the target image processing device 304;
the image processing device 304 is configured to, when receiving the image processing request sent by the task distribution device 303, perform image processing on the image to be processed according to the image processing request, and send image processing result information to the client 301.
In the distributed image processing system provided by the embodiment of the application, when receiving an image processing request sent by a client, a task scheduling device determines a target task distribution device from a plurality of distributed task distribution devices according to a preset first scheduling rule if the corresponding task type is determined to be a real-time task according to image processing information of an image to be processed included in the image processing request; and sending the image processing request to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to the first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client. Therefore, the distributed devices are reasonably scheduled to realize image processing, so that the image processing requirement of large concurrency can be met, the waste of device resources can be reduced, and the stability of the system is maintained. In addition, the corresponding processing is carried out according to the task type corresponding to the image processing request, so that the hierarchical processing of the request is realized, and the user experience can be improved under the condition of large concurrency of the image processing request, thereby maintaining and even improving the service volume.
The distributed image processing system provided in the embodiment of the present application can implement each process in the embodiment corresponding to the above distributed image processing method, and in order to avoid repetition, a description is omitted here.
It should be noted that, the distributed image processing system provided in the embodiment of the present application and the distributed image processing method provided in the embodiment of the present application are based on the same inventive concept, so that the implementation of the embodiment may refer to the implementation of the foregoing distributed image processing method, and the repetition is not repeated.
The embodiment of the present invention also provides a distributed image processing apparatus, which is configured to execute the distributed image processing method according to the above embodiment, based on the same technical concept. Fig. 6 is a schematic structural diagram of a distributed image processing apparatus for implementing various embodiments of the present invention, as shown in fig. 6, where the distributed image processing apparatus may have a relatively large difference due to different configurations or performances, and may include one or more processors 401 and a memory 402, and one or more storage applications or data may be stored in the memory 402. Wherein the memory 402 may be transient storage or persistent storage. The application programs stored in memory 402 may include one or more modules (not shown in the figures), each of which may include a series of computer executable instructions for use in a distributed image processing apparatus. Still further, the processor 401 may be arranged to communicate with the memory 402 and execute a series of computer executable instructions in the memory 402 on the distributed image processing apparatus. The distributed image processing apparatus may also include one or more power supplies 403, one or more wired or wireless network interfaces 404, one or more input output interfaces 405, and one or more keyboards 406.
In a specific embodiment, the distributed image processing apparatus includes a processor, a communication interface, a memory, and a communication bus; the processor, the communication interface and the memory complete communication with each other through a bus; a memory for storing a computer program; the processor is used for executing the program stored in the memory and realizing the following method steps:
receiving an image processing request sent by a client, wherein the image processing request comprises image processing information of an image to be processed;
determining a task type corresponding to the image processing request according to the image processing information;
if the task type is a real-time task, determining target task distribution equipment from a plurality of distributed task distribution equipment according to a preset first scheduling rule;
the image processing request is sent to the target task distribution device, so that the target task distribution device determines target image processing devices from a plurality of distributed image processing devices according to a first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client.
When an image processing request sent by a client is received, if the corresponding task type is determined to be a real-time task according to image processing information of an image to be processed included in the image processing request, determining a target task distribution device from a plurality of distributed task distribution devices according to a preset first scheduling rule; and sending the image processing request to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to the first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client. Therefore, the distributed devices are reasonably scheduled to realize image processing, so that the image processing requirement of large concurrency can be met, the waste of device resources can be reduced, and the stability of the system is maintained. In addition, the corresponding processing is carried out according to the task type corresponding to the image processing request, so that the hierarchical processing of the request is realized, and the user experience can be improved under the condition of large concurrency of the image processing request, thereby maintaining and even improving the service volume.
The distributed image processing device provided in the embodiment of the present application can implement each process in the embodiment corresponding to the above distributed image processing method, and in order to avoid repetition, a description is omitted here.
It should be noted that, the distributed image processing apparatus provided by the embodiment of the present invention and the distributed image processing method provided by the embodiment of the present invention are based on the same inventive concept, so that the implementation of the embodiment may refer to the implementation of the foregoing distributed image processing method, and the repetition is not repeated.
The embodiment of the application also provides a computer readable storage medium, wherein the storage medium stores a computer program, and the computer program realizes the following method steps when being executed by a processor:
receiving an image processing request sent by a client, wherein the image processing request comprises image processing information of an image to be processed;
determining a task type corresponding to the image processing request according to the image processing information;
if the task type is a real-time task, determining target task distribution equipment from a plurality of distributed task distribution equipment according to a preset first scheduling rule;
the image processing request is sent to the target task distribution device, so that the target task distribution device determines target image processing devices from a plurality of distributed image processing devices according to a first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client.
When the computer readable storage medium is executed by a processor, the computer readable storage medium receives an image processing request sent by a client, and if the corresponding task type is determined to be a real-time task according to image processing information of an image to be processed included in the image processing request, a target task distribution device is determined from a plurality of distributed task distribution devices according to a preset first scheduling rule; and sending the image processing request to the target task distribution device, so that the target task distribution device determines target image processing devices from the distributed multiple image processing devices according to the first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client. Therefore, the distributed devices are reasonably scheduled to realize image processing, so that the image processing requirement of large concurrency can be met, the waste of device resources can be reduced, and the stability of the system is maintained. In addition, the corresponding processing is carried out according to the task type corresponding to the image processing request, so that the hierarchical processing of the request is realized, and the user experience can be improved under the condition of large concurrency of the image processing request, thereby maintaining and even improving the service volume.
The computer readable storage medium provided in the embodiments of the present application can implement each process in the embodiments corresponding to the above-mentioned distributed image processing method, and for avoiding repetition, a detailed description is omitted here.
It should be noted that, the computer readable storage medium provided by the embodiment of the present invention and the distributed image processing method provided by the embodiment of the present invention are based on the same inventive concept, so that the implementation of the embodiment may refer to the implementation of the foregoing distributed image processing method, and the repetition is not repeated.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (10)
1. A distributed image processing method, comprising:
receiving an image processing request sent by a client, wherein the image processing request comprises image processing information of an image to be processed;
determining a task type corresponding to the image processing request according to the image processing information;
if the task type is a real-time task, determining target task distribution equipment from a plurality of distributed task distribution equipment according to a preset first scheduling rule;
The image processing request is sent to the target task distribution device, so that the target task distribution device determines target image processing devices from a plurality of distributed image processing devices according to a first preset mode, performs image processing on the image to be processed through the target image processing devices, and sends image processing result information to the client.
2. The method according to claim 1, wherein the image processing information includes image processing type information and image attribute information of the image to be processed;
the determining the task type corresponding to the image processing request according to the image processing information comprises the following steps:
determining a first weight corresponding to the image processing request according to the image processing type information and the image attribute information;
determining whether the first weight is smaller than a first preset weight;
if yes, determining that the task type corresponding to the image processing request is a delay processing task;
if not, determining that the task type corresponding to the image processing request is a real-time task.
3. The method according to claim 2, wherein determining the first weight corresponding to the image processing request according to the image processing type information and the image attribute information includes:
Determining a first sub-weight corresponding to image processing type information included in the image processing information based on a corresponding relation between preset image processing type information and the first sub-weight;
determining a second sub-weight corresponding to the image attribute information included in the image processing information according to a preset determination mode of the second sub-weight;
and determining a first weight corresponding to the image processing request according to the determined first sub-weight and the determined second sub-weight.
4. The method of claim 1, wherein the determining a target task distribution device from a distributed plurality of task distribution devices according to a preset first task scheduling rule comprises:
acquiring transmission bandwidth and transmission delay corresponding to each task distribution device in a plurality of distributed task distribution devices;
determining a second weight corresponding to each task distribution device according to the transmission bandwidth and the transmission delay;
and determining a target task distribution device for performing distribution processing on the image processing request from the plurality of task distribution devices according to the second weight.
5. The method of claim 4, wherein determining the second weight corresponding to each task distribution device according to the transmission bandwidth and the transmission delay comprises:
Determining a third sub-weight corresponding to each acquired transmission bandwidth based on a corresponding relation between the preset transmission bandwidth and the third sub-weight; determining fourth sub-weights corresponding to the acquired transmission delays based on the corresponding relation between the preset transmission delays and the fourth sub-weights; determining a second weight corresponding to each task distribution device according to the third sub-weight and the fourth sub-weight;
or,
and calculating a second weight corresponding to each task distribution device based on the transmission bandwidth and the transmission delay corresponding to each task distribution device according to a preset calculation mode.
6. The method according to claim 1, wherein the method further comprises:
if the task type is determined to be a delay processing task, determining a target message queue from a plurality of distributed message queues according to a preset second scheduling rule;
and storing the image processing request to the target message queue, so that the image processing equipment corresponding to the target message queue performs image processing on the image to be processed according to the image processing request in the target message queue, and sends image processing result information to the client.
7. A distributed image processing apparatus, comprising:
the receiving module is used for receiving an image processing request sent by the client; the image processing request comprises image processing information of an image to be processed;
the determining module is used for determining the task type corresponding to the image processing request according to the image processing information;
the first scheduling module is used for determining target task distribution equipment from the distributed multiple task distribution equipment according to a preset first scheduling rule if the task type is a real-time task;
the sending module is used for sending the image processing request to the target task distribution equipment so that the target task distribution equipment can determine target image processing equipment from a plurality of distributed image processing equipment according to a preset mode, and the target image processing equipment can process the image to be processed and send image processing result information to the client.
8. A distributed image processing system, comprising: the system comprises a client, a plurality of distributed task scheduling devices, a plurality of distributed task distributing devices and a plurality of distributed image processing devices;
The client is used for responding to the image processing operation of the user and determining the image processing information of the image to be processed; determining target task scheduling equipment from the distributed multiple task scheduling equipment according to a second preset mode, and sending an image processing request to the target task scheduling equipment according to the image processing information;
the task scheduling device is used for determining a task type corresponding to the image processing request according to the image processing information when the image processing request sent by the client is received; if the task type is a real-time task, determining a target task distribution device from the distributed multiple task distribution devices according to a preset first scheduling rule; transmitting the image processing request to the target task distribution device;
the task distribution device is used for determining a target image processing device from the distributed multiple image processing devices according to a first preset mode when the image processing request sent by the task scheduling device is received, and sending the image processing request to the target image processing device;
the image processing device is used for carrying out image processing on the image to be processed according to the image processing request when the image processing request sent by the task distribution device is received, and sending image processing result information to the client.
9. A distributed image processing apparatus comprising a processor, a memory and a computer program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the distributed image processing method according to any one of claims 1 to 6.
10. A computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the steps of the distributed image processing method according to any of claims 1 to 6.
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