CN109120679B - Task allocation method and device - Google Patents
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Abstract
The embodiment of the application provides a task allocation method and a device, wherein the method comprises the following steps: receiving a task detection request sent by a server; sending a detection application request corresponding to the task detection request to the server in a preset state, wherein the detection application request carries hardware resource information; if receiving task information of the task to be detected, which is sent by the server, detecting the task to be detected according to the task information to obtain a detection result; and sending the detection result to the server. By implementing the embodiment of the application, the efficiency of task detection can be improved.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a task allocation method and apparatus.
Background
With the development of society, mobile electronic devices (such as mobile phones and tablet computers) are gradually going deep into the public life, and an apple Operating System (IOS) platform applied to the mobile electronic devices is widely applied accordingly. The mobile application detection task based on the IOS platform is only executed at a server end at present, and if a large number of detection tasks need to be detected, the efficiency of the task detection is low.
Disclosure of Invention
The embodiment of the application provides a task allocation method and device, which can improve the efficiency of task detection.
A first aspect of an embodiment of the present application provides a task allocation method, where the method includes:
receiving a task detection request sent by a server;
sending a detection application request corresponding to the task detection request to the server in a preset state, wherein the detection application request carries hardware resource information;
if task information of the task to be detected sent by the server is received, detecting the task to be detected according to the task information to obtain a detection result, wherein the task to be detected is a task to be detected and identified by the server;
and sending the detection result to the server.
A second aspect of an embodiment of the present application provides a task allocation method, where the method includes:
if the task to be detected is identified, sending a task detection request to a plurality of clients, wherein the clients operate on the macOS platform;
receiving detection application requests sent by the plurality of clients, wherein the detection application requests carry hardware resource information;
determining a target client from the plurality of clients according to the hardware resource information sent by the plurality of clients;
sending task information of the task to be detected to the target client;
and receiving a detection result sent by the target client.
A third aspect of embodiments of the present application provides a task assigning apparatus including a first receiving unit, a judging unit, a second receiving unit, and a transmitting unit, wherein,
the first receiving unit is used for receiving a task detection request sent by a server;
the judging unit is used for sending a detection application request corresponding to the task detection request to the server in a preset state, wherein the detection application request carries hardware resource information;
the second receiving unit is configured to, if receiving task information of the task to be detected sent by the server, detect the task to be detected according to the task information to obtain a detection result, where the task to be detected is a task to be detected and identified by the server;
the sending unit is used for sending the detection result to the server.
A fourth aspect of the embodiments of the present application provides a terminal, where the terminal includes a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, where the memory is used to store a computer program, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method according to the first aspect and the second aspect of the embodiments of the present application.
A fifth aspect of embodiments of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, and wherein the computer program causes a computer to perform some or all of the steps as described in the first and second aspects of embodiments of the present application.
A sixth aspect of embodiments of the present application provides a computer program product, wherein the computer program product comprises a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps as described in the first and second aspects of embodiments of the present application. The computer program product may be a software installation package.
The embodiment of the application has at least the following beneficial effects:
according to the embodiment of the application, if the to-be-detected tasks exist in the server, task detection requests are sent to a plurality of clients, and the clients operate on a macOS platform; a client receives a task detection request sent by a server; if the client judges that the client is in the preset state, sending a detection application request to the server, wherein the detection application request carries hardware resource information; the server receives detection application requests sent by the plurality of clients, wherein the detection application requests carry hardware resource information; the server determines a target client from the plurality of clients according to the hardware resource information sent by the plurality of clients; the server sends the task information of the task to be detected to the target client; if the client receives the task information of the task to be detected, which is sent by the server, the task to be detected is detected according to the task information to obtain a detection result; the client sends the detection result to the server; the server receives the detection result sent by the target client, so that compared with the existing scheme, if the server has the task to be detected, the task to be detected is only executed on the server, the task to be detected can be distributed to the client to be executed according to the resource information of the client, and the client returns the execution result after the execution is finished, so that the detection efficiency during task detection can be improved to a certain extent.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a task allocation system according to an embodiment of the present application;
FIG. 2 is a flowchart of a task allocation method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a task allocation method according to an embodiment of the present application;
FIG. 4 is an interaction diagram of a task allocation method according to an embodiment of the present application;
FIG. 5 provides another task allocation method according to an embodiment of the present application;
FIG. 6 provides another task allocation method according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a terminal according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a server according to an embodiment of the present application;
FIG. 9 is a schematic structural diagram of a task allocation apparatus according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of a task allocation apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The electronic device according to the embodiments of the present application may include various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem, and various forms of User Equipment (UE), Mobile Stations (MS), terminal equipment (terminal device), and so on. For convenience of description, the above-mentioned apparatuses are collectively referred to as electronic devices.
First, a task allocation system of the task allocation method according to the embodiment of the present application will be briefly described below. Referring to fig. 1, fig. 1 is a schematic diagram of a task allocation system according to an embodiment of the present disclosure. As shown in fig. 1, the task allocation system includes a server 101 and clients 102, wherein the clients 102 run on a macOS platform, the macOS is a set of operating systems running on an apple Macintosh series computer, the server 101 detects whether there is a task to be detected in real time, and when detecting the task to be detected, sends a task detection request to the clients 102; after receiving the task detection request, if the client 102 is in the preset state, sending a detection application request to the server 101, wherein the detection application request carries hardware resource information of the client 102; after receiving detection application requests sent by a plurality of clients 102, the server 101 extracts hardware resource information corresponding to each client from the detection application requests; the client 101 determines a target client from the plurality of clients 102 according to the hardware resource information; the client 102 sends task information of the task to be detected to a target client; the target client receives the task information, detects the task to be detected according to the task information to obtain a detection result, and sends the detection result to the server 101; the server 101 receives the detection result. Through the task distribution system, the tasks to be detected by the server side can be distributed to the client sides of the server side, and the tasks to be detected are detected at the client sides, so that the efficiency of task detection can be improved to a certain extent.
Referring to fig. 2, fig. 2 is a flowchart illustrating a task allocation method according to an embodiment of the present disclosure. As shown in fig. 2, the task allocation method includes steps 201 and 204 as follows:
201. and receiving a task detection request sent by the server.
Optionally, the task detection request may carry a task name of the task to be detected and a memory value required when the task to be detected is executed, and certainly, the task detection request may also carry other information related to the task to be detected, which is only illustrated here and is not limited specifically.
202. And sending a detection application request corresponding to the task detection request to the server in a preset state, wherein the detection application request carries hardware resource information.
Optionally, one possible method for sending a detection application request corresponding to the task detection request to the server in a preset state includes steps a1-a4, which are specifically as follows:
a1, acquiring the number of the tasks being detected and the number of the tasks being downloaded;
the number of the tasks being detected is the number of the detection tasks currently being executed by the client, and the number of the tasks being downloaded is the number of the tasks currently being downloaded by the client.
A2, if the number of the tasks being detected is in a first preset range and the number of the tasks being downloaded is in a second preset range, acquiring hardware resource information;
optionally, the first preset range may be, for example, a range smaller than 5 pieces, specifically, 2 pieces, 3 pieces, and the like, and the second preset range may be, for example, a range smaller than 2 pieces, specifically, 0 piece or 1 piece.
Optionally, the hardware resource information may include hardware resource idle information, a Central Processing Unit (CPU) temperature, a CPU usage rate, a Graphics Processing Unit (GPU) usage rate, and the like, that is, a hardware resource that can be used in the current system hardware resource of the client.
A3, generating a detection application request according to the hardware resource information;
the hardware resource is used as the load content of the detection application request, and is filled into the load field of the detection application request, and the source Address, the destination Address, the source Internet Protocol Address (IP Address), the destination IP Address and the like of the detection application request are filled.
A4, sending the detection application request to the server.
Optionally, if it is determined that the detection request is in the preset state, another possible method for sending the detection request includes steps B1-B4, which are specifically as follows:
b1, acquiring the memory value occupied by the task under detection, and acquiring the numerical value of the task under download;
the memory value occupied by the task being detected may be: the sum of the memory occupied by all downloading tasks at the client.
B2, if the memory value is smaller than a preset memory value and the numerical value of the task being downloaded is smaller than a preset threshold value, acquiring hardware resource information;
optionally, the preset memory value may be, for example, a value between 50% and 80%, specifically, 55%, 56%, and the like, and the preset threshold value may be 2, that is, the numerical value of the task being downloaded is less than 2.
B3, generating a detection application request according to the hardware resource information;
b4, sending the detection application request to the server.
In this example, whether the application detection task is satisfied is judged from the perspective of the memory, the current operation parameters of the client can be reflected more accurately, whether the client has enough memory to operate the detection task can be determined, the initial screening can be performed, the workload of the server is reduced, the operation load of the server is reduced, and the detection efficiency can be improved to a certain extent
203. And if receiving task information of the task to be detected sent by the server, detecting the task to be detected according to the task information to obtain a detection result, wherein the task to be detected is the task to be detected identified by the server.
The task information of the task to be detected may include: task name, task execution conditions, task execution steps, task links, and the like. For example, for feature extraction of an application, the task information may include: the method comprises the steps of task name, task link and task execution, wherein the task link is used for instructing a client to download an application program from a specified address, and then detection of the application program is executed according to the task execution step. The task executing step can also be obtained through a task link, namely when the client downloads the detection task through the task link, the task executing step is obtained through a downloading mode, of course, the task executing step can also be pre-stored by the client, namely the task executing step corresponding to the task name is stored, when the server generates the task information, only the task name needs to be indicated, the client can execute the task executing step corresponding to the task name according to the task name, so that the feature extraction of the application program is completed, the features of the application program are obtained, and if the task executing step corresponding to the task name cannot be matched, the client sends a task executing step request packet, and the task executing step for obtaining the task is obtained from the server.
204. And sending the detection result to the server.
Referring to fig. 3, fig. 3 is a schematic flowchart illustrating a task allocation method according to an embodiment of the present disclosure. As shown in fig. 3, the task allocation method includes steps 301 and 305 as follows:
301. if the task to be detected is identified, sending a task detection request to a plurality of clients, wherein the clients operate on the macOS platform;
the task to be detected may be, for example, a task of performing shelling processing on the mobile application, or a detection task of performing feature extraction on the mobile application, or a task of analyzing the user information, which is only an example and is not limited specifically here.
Optionally, the server sends the task to be detected to all clients to which the task belongs through a heartbeat packet, the heartbeat packet is a self-defined command field that regularly informs the state of the other party between the client and the server, and is sent according to a certain time interval, and the heartbeat packet field in the application includes: heartbeat instructions, detection machine identity Information (ID), device ID, time stamp, data signature. Wherein, the heartbeat instruction is used for identifying that the equipment is in a survival state; the ID of the detector is the ID of the equipment executing the detection task; the equipment ID is the identity information of the client; the time stamp is used for uniquely identifying the time of a certain moment; the data signature is used for identity authentication, the identity authentication can be bidirectional authentication between a server and a client, and can also be unidirectional authentication between the server or the client, the identity authentication can be specifically divided according to security levels, the security levels comprise a first security level and a second security level, the first security level is higher than the second security level, when the security level is the first security level, bidirectional authentication can be adopted, and when the security level is the second security level, unidirectional authentication can be adopted. Of course, the heartbeat packet field may also add or delete a data type therein, and the added data type may be added according to actual needs, for example, it may be: task information of the detection task, task link of the detection task, hardware resource information or remaining detection time, etc., which are only schematic distances and are not limited specifically herein.
302. Receiving detection application requests sent by the plurality of clients, wherein the detection application requests carry hardware resource information;
optionally, the hardware resources may include hardware resource idle information, a Central Processing Unit (CPU) temperature, a CPU usage rate, a Graphics Processing Unit (GPU) usage rate, and the like, that is, the hardware resources that can be used in the current system hardware resources of the client.
303. Determining a target client from the plurality of clients according to the hardware resource information sent by the plurality of clients;
optionally, the method for determining a target client from a plurality of clients may include steps C1-C2, which are as follows:
c1, extracting hardware idle resources in the plurality of clients;
optionally, the hardware idle resource of each of the plurality of clients is extracted from the detection application request.
And C2, taking the client with the highest hardware idle resource in the plurality of clients as a target client.
Optionally, in an actual situation, it may happen that the server does not receive any detection application request, and another method for determining a target client from a plurality of clients may include steps D1-D4, which are as follows:
d1, if the detection application requests sent by the plurality of clients are not received, acquiring the remaining detection time length of each task in at least one detecting task of each client and the remaining download time length of each task in at least one downloading task of the client;
the detection duration of each task can be estimated in advance because the detection durations of different tasks are possibly different, and then the remaining detection duration is determined according to the percentage of the detection completion currently. The remaining download duration of the currently downloading task may be calculated to obtain an average download speed according to the time spent in downloading the downloaded part, and the remaining download duration may be estimated according to the speed, or may be determined according to the data amount of the remaining download part and the current real-time download speed, that is, the data amount of the remaining download part is divided by the current real-time download speed to obtain the remaining download duration.
D2, obtaining at least one reference client according to the remaining detection time length of each task in at least one detecting task of each client in the plurality of clients and the remaining download time length of each task in at least one downloading task of the client, wherein the target remaining detection time length of each client in the at least one reference client is less than the preset remaining detection time length and the target remaining download time length of the client is less than the preset remaining download time length; the target residual detection time length of the client is the minimum value of the residual detection time length of at least one task which is detected by the client, and the target download time length of the client is the minimum value of the download time length of at least one task which is downloaded by the client;
d3, obtaining the network quality parameter of each reference client in the at least one reference client;
the network quality parameters may include a real-time download speed, a real-time upload speed, an average download speed, an average upload speed, a packet loss rate, and the like.
D4, determining a target client according to the network quality parameters of each reference client, wherein the target client is the reference client with the optimal network quality parameters in the at least one reference client.
The reference client with the optimal network quality may be: if the reference client with the highest average download speed and the lowest packet loss rate does not exist, the reference client with the optimal network quality may also be: and the reference client with the lowest packet loss rate.
When the server does not receive a detection application request sent by the client, the residual detection time length of each task in at least one detecting task of each client in the plurality of clients and the residual downloading time length of each task in at least one downloading task of the client are obtained, a reference client is determined according to the information, and then a target client is determined according to the network quality of the reference client, so that the tasks can be distributed to the client which can reach the task application condition at first when the client does not have the task application condition, the waiting time of the task to be detected can be reduced, and the task detection efficiency is improved.
Optionally, in an actual situation, it may happen that the server does not receive any detection application request, and another method for determining a target client from a plurality of clients may include steps E1-E4, which are as follows:
e1, if the detection application requests sent by the plurality of clients are not received, extracting the task attributes of the tasks to be detected;
optionally, the task attribute may be an identifier for identifying whether the task to be detected can be split into a plurality of subtasks, and if the task to be detected can be split into a plurality of subtasks, specific rules for splitting the task are recorded in the task attribute, for example, a split point and a split number of the task are described.
E2, splitting the task to be detected into a first subtask and a second subtask according to the task attribute;
optionally, if the number of splits recorded in the task attribute is 2, splitting the task to be detected into a first subtask and a second subtask, and if the recorded number of splits is other numbers, splitting the task to be detected into the subtasks with the corresponding number.
E3, determining a first execution client of the first subtask and a second execution client of the second subtask from the plurality of clients according to the hardware resource information sent by the plurality of clients;
optionally, the method for determining the first executing client of the first subtask and then determining the first executing client and the second executing client from the plurality of clients when determining the executing client of the second subtask may refer to a specific implementation manner of steps D1-D4, which is not limited herein.
E4, sending the task information of the first subtask to the first execution client, and sending the task information of the second subtask to the second execution client.
When the detection application request is not received, the task to be detected is split into a plurality of subtasks which are respectively distributed to a plurality of clients to be executed, so that the task detection speed can be increased, and the phenomenon that the detection pressure of the clients is reduced due to the fact that a detection memory required by the detection task is large can be avoided.
304. Sending task information of the task to be detected to the target client;
the server adds a task information field of the detection task in a field of the heartbeat packet, and sends the detection task to the client through the heartbeat packet, and certainly, the server can also send the detection task to the client needing to be assigned through generating a specific task distribution instruction.
Optionally, in consideration of security, the task information may be encrypted, where an encryption algorithm of the encryption process may adopt a symmetric encryption algorithm, an asymmetric encryption algorithm, and the like, the symmetric encryption algorithm may be, for example, DES, AES128, and the like, and the asymmetric encryption algorithm may be, for example, an RSA encryption algorithm, and the like.
305. And receiving a detection result sent by the target client.
Referring to fig. 4, fig. 4 is an interaction diagram of a task allocation method according to an embodiment of the present application. As shown in fig. 4, the task allocation method includes:
401. when the server detects a task to be detected, task detection requests are sent to a plurality of clients;
402. when the client judges that the client is in a preset state, a detection application request is sent to the server, and the detection application request carries hardware resource information;
403. the server determines a target client according to the hardware resource information;
404. sending task information of a task to be detected to a target client;
405. the client detects the task to be detected according to the task information of the task to be detected to obtain a detection result;
406. and the client sends the detection result to the server.
According to the embodiment, the server distributes the task to be detected to the client side for execution, and the client side returns the execution result after the execution is completed, so that the detection efficiency during task detection can be improved to a certain extent.
Referring to fig. 5, fig. 5 is a block diagram illustrating another task allocation method according to an embodiment of the present disclosure. As shown in fig. 5, the task allocation method includes the following steps:
501. receiving a task detection request sent by a server;
502. acquiring the number of the tasks being detected and the number of the tasks being downloaded;
503. if the number of the tasks being detected is in a first preset range and the number of the tasks being downloaded is in a second preset range, acquiring hardware resource information;
504. generating a detection application request according to the hardware resource information;
505. sending the detection application request to the server;
506. if receiving task information of the task to be detected, which is sent by the server, detecting the task to be detected according to the task information to obtain a detection result;
507. and sending the detection result to the server.
Through the embodiment, if the number of the tasks being detected is in a first preset range and the number of the tasks being downloaded is in a second preset range, the detection application request is generated according to the hardware resource information and is sent to the service, so that the client can judge whether to apply for the task to be detected according to the hardware resource information of the client, and the intelligence and the practicability of the task distribution system can be improved to a certain extent.
Referring to fig. 6, fig. 6 is a block diagram illustrating another task allocation method according to an embodiment of the present disclosure. As shown in fig. 6, the task allocation method includes the following steps:
601. if the task to be detected exists, sending a task detection request to a plurality of clients, wherein the clients operate on the macOS platform;
602. if the detection application requests sent by the plurality of clients are not received, acquiring the remaining detection time length of each task in at least one detecting task of each client and the remaining downloading time length of each task in at least one downloading task of the client;
603. acquiring at least one reference client according to the residual detection time length of each task in at least one detecting task of each client in the plurality of clients and the residual downloading time length of each task in at least one downloading task of the client;
the target residual detection duration of each client in the at least one reference client is less than the preset residual detection duration, and the target residual downloading duration of the client is less than the preset residual downloading duration; the target residual detection time length of the client is the minimum value of the residual detection time length of at least one task which is detected by the client, and the target download time length of the client is the minimum value of the download time length of at least one task which is downloaded by the client;
604. obtaining a network quality parameter of each reference client in the at least one reference client;
605. determining a target client according to the network quality parameters of each reference client, wherein the target client is a reference client with the optimal network quality parameters in the at least one reference client;
606. sending task information of the task to be detected to the target client;
607. and receiving a detection result sent by the target client.
Through the embodiment, the task can be distributed to the client which can firstly reach the task application condition when the client does not have the task application condition, so that the waiting time of the task to be detected can be reduced, and the task detection efficiency is improved.
In accordance with the foregoing embodiments, please refer to fig. 7, fig. 7 is a schematic structural diagram of a terminal according to an embodiment of the present application, and as shown in fig. 7, the terminal includes a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, where the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the program includes instructions for executing the following steps;
receiving a task detection request sent by a server;
sending a detection application request corresponding to the task detection request to the server in a preset state, wherein the detection application request carries hardware resource information;
if task information of the task to be detected sent by the server is received, detecting the task to be detected according to the task information to obtain a detection result, wherein the task to be detected is a task to be detected and identified by the server;
and sending the detection result to the server.
In a possible example, in the case that the server is in the preset state, the server sends a detection application request to the server, where the detection application request carries hardware resource information, and the instruction in the program is specifically configured to perform the following operations: acquiring the number of the tasks being detected and the number of the tasks being downloaded; if the number of the tasks being detected is in a first preset range and the number of the tasks being downloaded is in a second preset range, acquiring hardware resource information; generating a detection application request according to the hardware resource information; and sending the detection application request to the server.
In a possible example, in the case that the server is in the preset state, the server sends a detection application request to the server, where the detection application request carries hardware resource information, and the instruction in the program is further specifically configured to perform the following operations: acquiring a memory value occupied by a task under detection and acquiring a numerical value of the task under downloading; if the memory value is smaller than a preset memory value and the numerical value of the task being downloaded is smaller than a preset threshold value, acquiring hardware resource information; generating a detection application request according to the hardware resource information; and sending the detection application request to the server.
In accordance with the foregoing embodiments, please refer to fig. 8, fig. 8 is a schematic structural diagram of a server according to an embodiment of the present application, as shown in fig. 8, including a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, where the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the program includes instructions for executing the following steps;
if the task to be detected is identified, sending a task detection request to a plurality of clients, wherein the clients operate on the macOS platform;
receiving detection application requests sent by the plurality of clients, wherein the detection application requests carry hardware resource information;
determining a target client from the plurality of clients according to the hardware resource information sent by the plurality of clients;
sending task information of the task to be detected to the target client;
and receiving a detection result sent by the target client.
In a possible example, in the aspect that the target client is determined from the multiple clients according to the hardware resource information sent by the multiple clients, the instructions in the program are specifically configured to perform the following operations: extracting hardware idle resources in the plurality of clients; and taking the client with the highest hardware idle resources as a target client.
In one possible example, the instructions in the program are further specifically for performing the following: if the detection application requests sent by the plurality of clients are not received, acquiring the remaining detection time length of each task in at least one detecting task of each client and the remaining downloading time length of each task in at least one downloading task of the client; acquiring at least one reference client according to the residual detection time length of each task in at least one detecting task of each client in the plurality of clients and the residual downloading time length of each task in at least one downloading task of the client, wherein the target residual detection time length of each client in the at least one reference client is less than the preset residual detection time length and the target residual downloading time length of the client is less than the preset residual downloading time length; the target residual detection time length of the client is the minimum value of the residual detection time length of at least one task which is detected by the client, and the target download time length of the client is the minimum value of the download time length of at least one task which is downloaded by the client; obtaining a network quality parameter of each reference client in the at least one reference client; and determining a target client according to the network quality parameters of each reference client, wherein the target client is the reference client with the optimal network quality parameters in the at least one reference client.
In one possible example, the instructions in the program are further specifically for performing the following: if the detection application requests sent by the plurality of clients are not received, extracting task attributes of the tasks to be detected; splitting the task to be detected into a first subtask and a second subtask according to the task attribute; determining a first execution client of the first subtask and a second execution client of the second subtask from the plurality of clients according to hardware resource information sent by the plurality of clients; and sending the task information of the first subtask to the first execution client, and sending the task information of the second subtask to the second execution client.
The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to realize the above functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
In accordance with the above, please refer to fig. 9, and fig. 9 is a schematic structural diagram of a task allocation apparatus according to an embodiment of the present application. The apparatus comprises a first receiving unit 901, a determining unit 902, a second receiving unit 903 and a transmitting unit 904, wherein,
the first receiving unit 901 is configured to receive a task detection request sent by a server;
the determining unit 902 is configured to send, in a preset state, a detection application request corresponding to the task detection request to the server, where the detection application request carries hardware resource information;
the second receiving unit 903 is configured to, if receiving task information of the task to be detected sent by the server, detect the task to be detected according to the task information to obtain a detection result, where the task to be detected is a task to be detected and identified by the server;
the sending unit 904 is configured to send the detection result to the server.
Optionally, if it is determined that the ue is in the preset state, a detection application request is sent to the server, where in the aspect that the detection application request carries hardware resource information, the determining unit 902 is specifically configured to: acquiring the number of the tasks being detected and the number of the tasks being downloaded; if the number of the tasks being detected is in a first preset range and the number of the tasks being downloaded is in a second preset range, acquiring hardware resource information; generating a detection application request according to the hardware resource information; and sending the detection application request to the server.
Optionally, if it is determined that the ue is in the preset state, a detection application request is sent to the server, where in the aspect that the detection application request carries hardware resource information, the determining unit 902 is further specifically configured to: acquiring a memory value occupied by a task under detection and acquiring a numerical value of the task under downloading; if the memory value is smaller than a preset memory value and the numerical value of the task being downloaded is smaller than a preset threshold value, acquiring hardware resource information; generating a detection application request according to the hardware resource information; and sending the detection application request to the server.
In accordance with the above, please refer to fig. 10, fig. 10 is a schematic structural diagram of a task allocation apparatus according to an embodiment of the present application, where the task allocation apparatus includes:
a first sending unit 110, configured to send a task detection request to multiple clients if the task to be detected is identified, where the clients operate on a macOS platform;
a first receiving unit 120, configured to receive detection application requests sent by the multiple clients, where the detection application requests carry hardware resource information;
a determining unit 130, configured to determine a target client from the multiple clients according to the hardware resource information sent by the multiple clients;
a second sending unit 140, configured to send task information of the task to be detected to the target client;
a second receiving unit 150, configured to receive the detection result sent by the target client.
Optionally, in the aspect that the target client is determined from the multiple clients according to the hardware resource information sent by the multiple clients, the determining unit is specifically configured to: extracting hardware idle resources in the plurality of clients; and taking the client with the highest hardware idle resources as a target client.
Optionally, the task allocation device is further configured to: if the detection application requests sent by the plurality of clients are not received, acquiring the remaining detection time length of each task in at least one detecting task of each client and the remaining downloading time length of each task in at least one downloading task of the client; acquiring at least one reference client according to the residual detection time length of each task in at least one detecting task of each client in the plurality of clients and the residual downloading time length of each task in at least one downloading task of the client, wherein the target residual detection time length of each client in the at least one reference client is less than the preset residual detection time length and the target residual downloading time length of the client is less than the preset residual downloading time length; the target residual detection time length of the client is the minimum value of the residual detection time length of at least one task which is detected by the client, and the target download time length of the client is the minimum value of the download time length of at least one task which is downloaded by the client; obtaining a network quality parameter of each reference client in the at least one reference client; and determining a target client according to the network quality parameters of each reference client, wherein the target client is the reference client with the optimal network quality parameters in the at least one reference client.
Optionally, the task allocation device is further configured to: if the detection application requests sent by the plurality of clients are not received, extracting task attributes of the tasks to be detected; splitting the task to be detected into a first subtask and a second subtask according to the task attribute; determining a first execution client of the first subtask and a second execution client of the second subtask from the plurality of clients according to hardware resource information sent by the plurality of clients; and sending the task information of the first subtask to the first execution client, and sending the task information of the second subtask to the second execution client.
Embodiments of the present application also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the task allocation methods as described in the above method embodiments.
Embodiments of the present application also provide a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program causes a computer to execute part or all of the steps of any one of the task allocation methods as described in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may be implemented in the form of a software program module.
The integrated units, if implemented in the form of software program modules and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a read-only memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and the like.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash memory disks, read-only memory, random access memory, magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (9)
1. A task allocation method is applied to a client, and comprises the following steps:
receiving a task detection request sent by a server;
sending a detection application request corresponding to the task detection request to the server in a preset state, wherein the detection application request carries hardware resource information, the hardware resource information is used for the server to determine a target client from a plurality of clients, and the target client is used for receiving task information of a task to be detected sent by the server;
in a non-preset state, if a task remaining detection duration and a remaining downloading duration acquisition request sent by a server are received, sending the remaining detection duration of each task in the tasks being detected and the remaining downloading duration of each task in the tasks being downloaded to the server, so that the server determines at least one reference client from a plurality of clients and acquires a network quality parameter of each reference client, and determines a target client according to the network quality parameter of each reference client, wherein the target remaining detection duration of each client in the at least one reference client is less than the preset remaining detection duration and the target remaining downloading duration of the client is less than the preset remaining downloading duration;
if task information of a task to be detected sent by the server is received, detecting the task to be detected according to the task information to obtain a detection result, wherein the task to be detected is a task to be detected and identified by the server;
and sending the detection result to the server.
2. The method according to claim 1, wherein the sending, in a preset state, a detection application request corresponding to the task detection request to the server, where the detection application request carries hardware resource information, includes:
acquiring the number of the tasks being detected and the number of the tasks being downloaded;
if the number of the tasks being detected is in a first preset range and the number of the tasks being downloaded is in a second preset range, acquiring hardware resource information;
generating a detection application request according to the hardware resource information;
and sending the detection application request to the server.
3. The method according to claim 1, wherein the sending, in a preset state, a detection application request corresponding to the task detection request to the server, where the detection application request carries hardware resource information, includes:
acquiring a memory value occupied by a task under detection and acquiring a numerical value of the task under downloading;
if the memory value is smaller than a preset memory value and the numerical value of the task being downloaded is smaller than a preset threshold value, acquiring hardware resource information;
generating a detection application request according to the hardware resource information;
and sending the detection application request to the server.
4. A task allocation method is applied to a server, and the method comprises the following steps:
if the task to be detected is identified, sending a task detection request to a plurality of clients, wherein the clients run on a macOS platform, and the task detection request is used for indicating the clients to send a detection application request corresponding to the task detection request to the server in a preset state;
receiving detection application requests sent by the plurality of clients, wherein the detection application requests carry hardware resource information;
determining a target client from the plurality of clients according to the hardware resource information sent by the plurality of clients;
if the detection application requests sent by the plurality of clients are not received, acquiring the remaining detection time length of each task in at least one detecting task of each client and the remaining downloading time length of each task in at least one downloading task of the client;
acquiring at least one reference client according to the residual detection time length of each task in at least one detecting task of each client in the plurality of clients and the residual downloading time length of each task in at least one downloading task of the client, wherein the target residual detection time length of each client in the at least one reference client is less than the preset residual detection time length and the target residual downloading time length of the client is less than the preset residual downloading time length; the target residual detection time length of the client is the minimum value of the residual detection time length of at least one task which is detected by the client, and the target download time length of the client is the minimum value of the download time length of at least one task which is downloaded by the client;
obtaining a network quality parameter of each reference client in the at least one reference client;
determining a target client according to the network quality parameters of each reference client, wherein the target client is a reference client with the optimal network quality parameters in the at least one reference client;
sending task information of the task to be detected to the target client;
and receiving a detection result sent by the target client.
5. The method of claim 4, wherein the determining a target client from the plurality of clients according to the hardware resource information sent by the plurality of clients comprises:
extracting hardware idle resources in the plurality of clients;
and taking the client with the highest hardware idle resource in the plurality of clients as a target client.
6. The method according to claim 4 or 5, characterized in that the method further comprises:
if the detection application requests sent by the plurality of clients are not received, extracting task attributes of the tasks to be detected;
splitting the task to be detected into a first subtask and a second subtask according to the task attribute;
determining a first execution client of the first subtask and a second execution client of the second subtask from the plurality of clients according to hardware resource information sent by the plurality of clients;
and sending the task information of the first subtask to the first execution client, and sending the task information of the second subtask to the second execution client.
7. A task allocation apparatus applied to a client, the apparatus comprising:
the first receiving unit is used for receiving a task detection request sent by a server;
the system comprises a judging unit, a task detection unit and a task processing unit, wherein the judging unit is used for sending a detection application request corresponding to the task detection request to the server in a preset state, the detection application request carries hardware resource information, the hardware resource information is used for the server to determine a target client from a plurality of clients, and the target client is used for receiving task information of a task to be detected sent by the server;
the judging unit is further configured to, in a non-preset state, send, to the server, the remaining detection time of each of the tasks being detected and the remaining download time of each of the tasks being downloaded if a request for obtaining the remaining detection time and the remaining download time of the task sent by the server is received, so that the server determines at least one reference client from the plurality of clients and obtains a network quality parameter of each reference client, and determines the target client according to the network quality parameter of each reference client, where the target remaining detection time of each client in the at least one reference client is less than the preset remaining detection time and the target remaining download time of the client is less than the preset remaining download time;
the second receiving unit is used for detecting the task to be detected according to the task information if the task information of the task to be detected sent by the server is received, and obtaining a detection result, wherein the task to be detected is a task to be detected and identified by the server;
a sending unit, configured to send the detection result to the server.
8. A terminal, comprising a processor, an input device, an output device, and a memory, the processor, the input device, the output device, and the memory being interconnected, wherein the memory is configured to store a computer program comprising program instructions, the processor being configured to invoke the program instructions to perform the method of any of claims 1-6.
9. A computer-readable storage medium, characterized in that the computer storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method according to any of claims 1-6.
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| PCT/CN2018/108884 WO2020019519A1 (en) | 2018-07-27 | 2018-09-29 | Task allocation method and apparatus |
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| CN201810840985.7A CN109120679B (en) | 2018-07-27 | 2018-07-27 | Task allocation method and device |
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