CN112543420A

CN112543420A - Task processing method and device and server

Info

Publication number: CN112543420A
Application number: CN202011212440.5A
Authority: CN
Inventors: 童海; 徐为恺; 杨杨; 江旻
Original assignee: WeBank Co Ltd
Current assignee: WeBank Co Ltd
Priority date: 2020-11-03
Filing date: 2020-11-03
Publication date: 2021-03-23
Anticipated expiration: 2040-11-03
Also published as: CN112543420B

Abstract

The invention discloses a task processing method, a task processing device and a server. The task processing method comprises the following steps: based on the first parameter of each first node device in at least one first node device, issuing a first task to each second node device in at least one second node device; determining aggregated data corresponding to the first task based on first data reported by each second node device of the at least one second node device; the first node device represents a node device which meets a first set constraint condition of the first task in the mobile intelligent group awareness network; the first parameter represents the quality of data acquired by the node equipment; the second node equipment represents the first node equipment of which the first parameter meets the set data quality condition; and the aggregated data corresponding to the first task is obtained by aggregating the first data meeting the second set constraint condition of the first task.

Description

Task processing method and device and server

Technical Field

The invention relates to the technical field of financial technology (Fintech), in particular to a task processing method, a device and a server.

Background

With the development of computer technology, more and more technologies are applied in the financial field, and the traditional financial industry is gradually changing to financial technology, however, the financial technology also puts higher demands on the technologies due to the requirements of security and real-time performance of the financial industry. In the field of financial science and technology, a Mobile Crowd Sensing (Mobile Crowd Sensing) system takes Mobile equipment carried by a common user as a Sensing unit and forms a Crowd Sensing network through network communication, so that Sensing task distribution and Sensing data collection are realized, and a large-scale Sensing task is completed.

In the related art, due to the influence of various factors, the quality of perception data collected by mobile devices corresponding to task participants is uneven, so that the perception data obtained by aggregating the perception data collected by all the mobile devices is inaccurate.

Disclosure of Invention

In view of this, embodiments of the present invention are intended to provide a task processing method, a task processing device, and a server, so as to solve the technical problem in the related art that perceptual data obtained by fusing a mobile crowd sensing system is inaccurate.

In order to achieve the purpose, the technical scheme of the invention is realized as follows:

the embodiment of the invention provides a task processing method, which comprises the following steps:

based on the first parameter of each first node device in at least one first node device, issuing a first task to each second node device in at least one second node device;

determining aggregated data corresponding to the first task based on first data reported by each second node device of the at least one second node device; wherein the content of the first and second substances,

the first node device represents a node device which meets a first set constraint condition of the first task in the mobile intelligent group awareness network;

the first parameter represents the quality of data acquired by the node equipment;

the second node equipment represents the first node equipment of which the first parameter meets the set data quality condition;

and the aggregated data corresponding to the first task is obtained by aggregating the first data meeting the second set constraint condition of the first task.

In the above scheme, the method further comprises:

and determining a first parameter of each node device in the mobile intelligent group sensing network.

In the above scheme, the method further comprises:

updating a first parameter of each of the at least one second node device based on the score corresponding to the first task; wherein the content of the first and second substances,

the score corresponding to the first task is obtained after the aggregated data corresponding to the first task is determined.

In the foregoing solution, the determining a first parameter of each node device in the mobile wisdom group aware network includes:

determining an index value of each node device on each set evaluation index in at least one set evaluation index;

and updating the first parameter of each node device in the mobile intelligent group perception network based on the corresponding relation between the set first parameter and the index value.

In the above solution, the set evaluation index includes at least one of:

location information of the node device;

the density of terminal equipment corresponding to a coverage area corresponding to the node equipment;

task completion rate of the node device.

In the foregoing solution, when the first parameter of each of the at least one second node device is updated based on the score corresponding to the first task, the method includes:

determining an offset value corresponding to second node equipment based on first data reported by the second node equipment, the aggregation data corresponding to the first task and the score corresponding to the first task;

and updating the first parameter of the second node device based on the deviation value corresponding to the second node device.

In the foregoing solution, the updating the first parameter of the second node device based on the deviation value corresponding to the second node device includes:

determining a first parameter calculation mode corresponding to the second node equipment based on the deviation value corresponding to the second node equipment;

and updating the first parameter of the second node equipment based on the first parameter calculation mode corresponding to the second node equipment.

In the foregoing solution, when determining, based on the deviation value corresponding to the second node device, a first parameter calculation method for updating the second node device corresponding to the second node device, the method further includes one of:

determining a first parameter calculation mode corresponding to the second node equipment based on the median and the deviation value corresponding to the second node equipment;

determining a first parameter calculation mode corresponding to the second node equipment based on the set adjustment parameter, the median and the deviation value corresponding to the second node equipment; wherein the content of the first and second substances,

and determining the median based on the deviation values corresponding to all the second node devices.

In the foregoing solution, the first parameter calculation manner includes one of the following:

calculating a new first parameter based on the current first parameter, the deviation value and a set first correction coefficient;

the first parameter remains unchanged;

and calculating a new first parameter based on the current first parameter, the deviation value, the median and the set second correction coefficient.

In the foregoing solution, the node device includes one of:

a server for mobile edge computing;

a terminal device for performing a first task.

An embodiment of the present invention provides a task processing device, including:

the task allocation unit is used for issuing a first task to each second node device in at least one second node device based on the first parameter of each first node device in at least one first node device;

an aggregation unit, configured to determine, based on first data reported by each second node device of the at least one second node device, aggregated data corresponding to the first task; wherein the content of the first and second substances,

An embodiment of the present invention further provides a server, including: a processor and a memory for storing a computer program capable of running on the processor,

wherein the processor is configured to execute the steps of any one of the above task processing methods when the processor runs the computer program.

An embodiment of the present invention further provides a storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of any one of the task processing methods described above.

In the embodiment of the present invention, the server issues the first task to each second node device in the at least one second node device based on the first parameter of each first node device in the at least one first node device, and determines the aggregated data corresponding to the first task based on the first data reported by each second node device in the at least one second node device. The first node device represents a node device which meets a first set constraint condition of a first task in the mobile intelligent group perception network. The server issues the first task to the second node device, so that the first data with the quality meeting the setting requirement reported by the second node device can be obtained, and the accuracy of aggregated data corresponding to the first task obtained based on the aggregation of the obtained first data is improved.

Drawings

FIG. 1 is a schematic diagram of a mobile crowd sensing system provided in the related art;

fig. 2 is a schematic diagram of an architecture of a mobile crowd sensing system according to an embodiment of the present invention;

fig. 3 is a schematic flow chart illustrating an implementation of a task processing method according to an embodiment of the present invention;

fig. 4 is a schematic flow chart illustrating an implementation process of determining, by a cloud server, a second node device in the task processing method according to the embodiment of the present invention;

fig. 5 is a schematic flow chart illustrating an implementation of a task processing method according to another embodiment of the present invention;

fig. 6 is a schematic flow chart illustrating an implementation of updating a first parameter in a task processing method according to an embodiment of the present invention;

fig. 7 is a schematic flow chart illustrating an implementation of updating a first parameter in a task processing method according to an embodiment of the present invention;

fig. 8 is a graph of a first parameter when the second node device continuously reports trusted data according to the embodiment of the present invention;

fig. 9 is a graph of a first parameter when the second node device continuously reports untrusted data according to the embodiment of the present invention;

fig. 10 is a schematic flow chart illustrating an implementation of updating a first parameter in a task processing method according to an embodiment of the present invention;

FIG. 11 is a schematic structural diagram of a task processing device according to an embodiment of the present invention;

fig. 12 is a schematic diagram of a hardware component structure of a server according to an embodiment of the present invention.

Detailed Description

Before the embodiments of the present invention are described, the operation principle of the mobile crowd sensing system in the related art is described.

Referring to fig. 1, fig. 1 illustrates an architecture diagram of a mobile crowd sensing system provided in the related art. As shown in fig. 1, the mobile crowd sensing system in the related art includes: the system comprises a first terminal device 11 corresponding to at least one task publisher, a cloud server 12 and a second terminal device 13 corresponding to at least one task participant. The working principle of the mobile crowd sensing system is as follows:

the first terminal device 11 is communicated with the cloud server and issues a sensing task to the cloud server 12;

the cloud server 12 broadcasts the sensing task to the second terminal device 13 when receiving the sensing task issued by the first terminal device 11;

the second terminal device 13, under the condition of receiving the sensing tasks broadcast by the cloud server, executes the sensing tasks selected by the task participants from the received sensing tasks, and reports the sensing data corresponding to the sensing tasks to the server 12;

the cloud server 12 determines, based on constraint conditions (constraint conditions such as task start time, completion time, and location information) corresponding to the sensing tasks, sensing data meeting the constraint conditions corresponding to the sensing tasks from among the sensing data corresponding to the sensing tasks reported by all the second terminal devices 13, and aggregates the determined sensing data to obtain an aggregation result, when receiving the sensing data corresponding to the sensing tasks reported by the second terminal devices 13; the aggregating process of the determined sensing data may be calculating an average of all the determined sensing data.

The cloud server 12 sends the aggregation result data corresponding to the sensing task to the first terminal device 11 when determining the aggregation result corresponding to the sensing task.

In the related art, due to the influence of various factors, for example, different device configuration parameters of the second terminal device, the quality of the sensing data reported to the cloud server by the second terminal device is different, and thus, the aggregation result obtained by the cloud server based on the sensing data reported by the second terminal device is inaccurate.

In order to solve the above technical problem, an embodiment of the present invention provides a Mobile crowd sensing system, where a node device for Mobile Edge Computing (MEC) is added to the Mobile crowd sensing system provided in fig. 1. In the mobile crowd sensing system of the present invention, the server may issue the first task to each of the at least one second node device based on the first parameter of each of the at least one first node device, and determine the aggregated data corresponding to the first task based on the first data reported by each of the at least one second node device. The first node device represents a node device which meets a first set constraint condition of a first task in the mobile intelligent group perception network. When the server is a cloud server, the first node equipment and the second node equipment are both node equipment for mobile edge computing; when the server is a node device for mobile edge computing, the first node device and the second node device are both terminal devices used by task participants.

The server issues the sensing task to the second node device, so that the sensing data with the quality meeting the set requirement reported by the second node device can be obtained, and the accuracy of aggregated data corresponding to the sensing task obtained based on the aggregation of the obtained sensing data is improved.

The technical solution of the present invention is further described in detail with reference to the drawings and the specific embodiments of the specification.

Referring to fig. 2, fig. 2 is a schematic diagram illustrating a mobile crowd sensing system architecture provided by an embodiment of the present invention. The mobile crowd-sourcing awareness system as shown in fig. 2 comprises at least one terminal device 21 for issuing a first task, a cloud server 22, at least one node device 23 for mobile edge computing, and at least one terminal device 24 for performing the first task. The node equipment for the mobile edge calculation is a server; the first task characterizes the aware task. The first task may be a task related to intelligent transportation, public safety, social recommendation, environmental monitoring, urban public management, and the like. The terminal equipment can be a mobile phone, a tablet computer, wearable equipment and the like.

The working principle of the mobile crowd sensing system is as follows:

and the terminal device 21 is communicated with the cloud server 22 and issues the first task to the cloud server.

The cloud server 22 determines an MEC node device subset based on a first parameter of each first node device 23 of the at least one first node device 23 when receiving the first task issued by the terminal device 21; and issuing the first task to each second node device 23 of the at least one second node device 23 based on the MEC node device subset. Wherein, the MEC node device subset includes the related information of at least one second node device 23; the first node device 23 is a node device 23 which satisfies a first set constraint condition of a first task in the mobile wisdom group awareness network; the second node apparatus 23 is the first node apparatus 23 whose first parameter satisfies the set data quality condition.

The second node device 23, upon receiving the first task issued by the cloud server 22, issues the first task to each second terminal device 24 in the at least one second terminal device 24 based on the first parameter of each first terminal device 24 in the at least one first terminal device 24 for executing the first task. The second node device 23 may issue the first task to the second terminal device 24 by sending a broadcast message; the first terminal device 24 is a terminal device 24 which meets a first set constraint condition of a first task in the mobile wisdom group awareness network; the second terminal device 24 is the first terminal device 24 whose first parameter satisfies the set data quality condition.

The second terminal device 24, in a case of receiving the first task issued by the second node device 23, executes the first task, and reports first data corresponding to the first task acquired in real time to the second node device 23; wherein the first data is perception data.

The second node device 23, upon receiving the first data corresponding to the first task reported by all the second terminal devices 24, determines, based on all the received first data, first aggregated data corresponding to the first task, and reports the first aggregated data corresponding to the first task to the cloud server 22. Based on all the received first data, the method for determining the first aggregated data corresponding to the first task may be: determining first data meeting a second set constraint condition of the first task from all the received first data, performing aggregation processing on the first data meeting the second set constraint condition of the first task according to a set data aggregation mode to obtain first aggregated data corresponding to the first task, and reporting the first aggregated data corresponding to the first task to the cloud server 22; the set data aggregation mode can represent the average value of the calculated sensing data and can also represent the weighted average value of the calculated sensing data.

The cloud server 22, when receiving the first aggregated data reported by all the second node devices 23, determines, based on all the first aggregated data, second aggregated data corresponding to the first task, and sends, to the terminal device 21, the second aggregated data corresponding to the first task. The cloud server 22 may determine, from all the received first aggregated data, first aggregated data that meets a second set constraint condition of the first task, and aggregate, according to a set data aggregation manner, the first aggregated data that meets the second set constraint condition of the first task, to obtain second aggregated data corresponding to the first task.

The terminal device 21 is configured to send a score corresponding to the first task to the cloud server when receiving the second aggregated data corresponding to the first task sent by the cloud server 22; the score of the first task may be input by the task publisher, or may be determined by the terminal device 21 based on the expected data of the first task and the second aggregated data, where the expected data of the first task is input by the task publisher.

The cloud server 22, which updates the first parameter of each second node device 23 based on the score corresponding to the first task and issues the score corresponding to the first task to each second node device 23 when receiving the score corresponding to the first task sent by the terminal device 21;

the second node device 23, upon receiving the score corresponding to the first task sent by the cloud server 22, updates the first parameter of each of the second terminal devices 24 for executing the first task based on the score corresponding to the first task.

After the operation principle of the mobile crowd sensing system is briefly introduced above, the cloud server 22 or the node device 23 for mobile edge computing is taken as an execution subject, and the implementation process of the task processing method according to the embodiment of the present invention is described in detail below.

Referring to fig. 3, fig. 3 is a schematic diagram illustrating an implementation flow of a task processing method according to an embodiment of the present invention. An execution subject of the task processing method provided by the embodiment of the present invention is a server, and the server is a cloud server 22 in fig. 2 or a node device 23 for mobile edge computing in fig. 2. Here, when the execution subject is the cloud server 22 in fig. 2, the first node device and the second node device in the following embodiments are both the node devices 23 for mobile edge computing. When the execution subject is the node device 23 for the mobile edge calculation, the first node device and the second node device in the following embodiments are both the terminal devices 24 for executing the first task.

As shown in fig. 3, the task processing method includes:

s301: and issuing a first task to each second node device in at least one second node device based on the first parameter of each first node device in at least one first node device. Wherein the content of the first and second substances,

and the second node equipment represents the first node equipment of which the first parameter meets the set data quality condition.

Here, the server, upon receiving the first task, determines, from the node devices in the mobile wisdom group awareness network, at least one node device that satisfies the first set constraint of the first task, based on the first set constraint in the attribute information of the first task and based on the related information of all the node devices in the mobile wisdom group awareness network, and obtains the at least one first node device. Wherein the content of the first and second substances,

the server stores relevant information of all node devices accessed into the mobile intelligent group sensing network in advance, wherein the relevant information comprises device identification, geographical location information, first parameters and the like, and can also comprise a coverage area. In practical applications, the first parameter may be a reputation. The larger the value of the first parameter is, the better the quality of the data collected by the corresponding node device is represented, that is, the higher the reliability of the data is.

The attribute information of the first task includes a task starting time, a task ending time, a place for executing the task, a minimum number of people participating in the task, and the like, and also includes a budget and an expected result corresponding to the first task. The budget characterizes resources that are expected to be allocated to all participants performing the first task. The resource, which may be a virtual resource, in return for executing the first task. The expected result corresponding to the first task may be used to determine a score for the first task. The score for the first task characterizes satisfaction with the aggregated data for the first task.

The first set of constraints may characterize where the task is performed. When the attribute information of the first task does not include a task execution place, all node devices in the mobile wisdom group awareness network are determined to be the node devices meeting the first set constraint condition of the first task.

The method includes that when at least one first node device is determined, the server determines at least one first node device with a first parameter meeting a set data quality condition based on a first parameter of each first node device in the determined at least one first node device, and obtains at least one second node device; and under the condition that at least one second node device is determined, issuing a first task to each second node device in the at least one second node device. Wherein the set data quality condition may indicate that the value of the first parameter is greater than or equal to a set threshold; the method also can be characterized in that a first number of first node devices are selected according to the sequence from large to small of the value of the first parameter, and the first number is determined based on the minimum number of persons participating in the first task. Here, when the first node device is a node device for moving edge calculation, the second number of all the terminal devices for executing the first task corresponding to the first number of the second node devices is greater than or equal to the minimum number of participating persons corresponding to the first task.

In practical applications, the cloud server may determine at least one second node device for mobile edge computing according to the process shown in fig. 4. Wherein the content of the first and second substances,

the cloud server judges whether the node equipment meets a first set constraint condition of the first task based on the attribute information of the first task. When the judgment result indicates that the node equipment meets a first set constraint condition of the first task, adding the corresponding node equipment to a candidate MEC node list, wherein the candidate MEC node list is used for storing relevant information of the first node equipment; and when the judgment result indicates that the node equipment does not meet the first set constraint condition of the first task, adding the corresponding node equipment to the node list of the pending MEC. Here, the cloud server may determine whether the node apparatus satisfies the first set constraint condition of the first task based on the first set constraint condition in the attribute information of the first task and based on the location information and the coverage area of all the node apparatuses for the mobile edge computing. The node device satisfying the first set constraint condition of the first task is the first node device.

The cloud server determines at least one second node device based on the first parameter of each first node device in the candidate MEC node list. Judging whether the total number of the terminal equipment corresponding to the second node equipment reaches the minimum number of the participated persons corresponding to the first task; when the judgment result indicates that the total number of the terminal devices corresponding to the second node devices is smaller than the minimum number of the participators, at least one second node device is continuously determined; when the judgment result represents that the total number of the terminal devices corresponding to the second node device is greater than or equal to the minimum number of the participators, outputting an MEC node list; and the MEC node list comprises the determined related information of all the second node devices.

Here, a third number of second node devices is determined from the candidate MEC node list in order from high to low of the first parameter based on the first parameter of each first node device in the candidate MEC node list and based on the number of terminal devices accessing each first node device. When the total number of the terminal devices corresponding to all the second node devices in the candidate MEC node list is larger than or equal to the minimum number of the participants corresponding to the first task, the second node devices are determined from the candidate MEC node list. And when the total number of the terminal devices corresponding to all the first node devices in the candidate MEC node list is less than the minimum number of people participating, selecting a fourth number of node devices from the undetermined MEC node list according to the sequence of the first parameter from high to low so that the total number of the terminal devices for executing the first task is greater than or equal to the minimum number of people participating. The terminal device corresponding to the second node device is a terminal device accessed to the second node device, the number of the terminal devices corresponding to the second node device may be reported to the cloud server by the second node device, and of course, when the cloud server stores the related information of the terminal devices accessed to the node devices for mobile edge computing, the cloud server may count the number of the terminal devices corresponding to the second node device.

In an embodiment, when the first node device is a terminal device for executing a first task, the server may broadcast a task notification message to the at least one first node device when determining the at least one first node device, so as to notify that a user corresponding to the first node device currently has a first task to be executed, so that the user corresponding to the first node device determines whether to participate in the first task based on attribute information of the first task carried in the task notification message. When a user confirms to participate in a first task through an interactive interface of first node equipment, triggering the first node equipment to send confirmation information for representing participation in the first task to a server, and when the server receives the confirmation information sent by the first node equipment, determining at least one first node equipment with a first parameter meeting a set data quality condition based on the first parameter of each first node equipment in the at least one first node equipment sending the confirmation information to obtain at least one second node equipment; and under the condition that at least one second node device is determined, issuing a first task to each second node device in the at least one second node device.

S302: and determining the aggregated data corresponding to the first task based on the first data reported by each of the at least one second node device. And the aggregated data corresponding to the first task is obtained by aggregating the first data meeting the second set constraint condition of the first task.

The server obtains first data corresponding to the first task reported by each second node device, determines first data meeting a second set constraint condition of the first task from all the received first data, and aggregates the first data meeting the second set constraint condition of the first task according to a set data aggregation mode to obtain aggregated data corresponding to the first task. Wherein the content of the first and second substances,

and the second set constraint condition is used for the server to screen out effective first data. And the second set constraint condition represents a task execution time period and a task execution site corresponding to the first task, and the task execution time period is determined by the task starting time and the task ending time in the attribute information of the first task.

The set data aggregation mode may be characterized by calculating an average value of the first data, or may be characterized by calculating a weighted average value of the first data.

It should be noted that, when the server is the node device 23 used in the mobile edge computing in fig. 2, the second node device is the terminal device 24 used to execute the first task, the second node device executes the first task, collects first data corresponding to the first task, and reports the first data corresponding to the first task to the node device 23 used in the mobile edge computing. The node device 23 for mobile edge computing determines, when receiving first data reported by all second node devices, first data that satisfies a second set constraint condition of the first task, and performs aggregation processing on the first data that satisfies the second set constraint condition of the first task according to a set data aggregation manner, to obtain first aggregated data corresponding to the first task.

When the server is the cloud server 22 in fig. 2, the second node device is a node device 23 for mobile edge computing, and the first data reported to the server by the second node device is first aggregated data corresponding to the first task. Since the first aggregated data meets the first data aggregation of the second set constraint condition of the first task, the first aggregated data meets the second set constraint condition of the first task, and the cloud server 22 aggregates all the first aggregated data according to the set data aggregation manner under the condition that the first aggregated data reported by all the second node devices is received, so as to obtain the second aggregated data corresponding to the first task.

And the cloud server sends the second aggregated data corresponding to the first task to the terminal equipment issuing the first task under the condition that the second aggregated data corresponding to the first task is determined.

In the solution provided in the embodiment of the present invention, the server issues the first task to each second node device in the at least one second node device based on the first parameter of each first node device in the at least one first node device, and determines the aggregated data corresponding to the first task based on the first data reported by each second node device in the at least one second node device. The first node device represents a node device which meets a first set constraint condition of a first task in the mobile intelligent group perception network. The server issues the first task to the second node device, so that the first data with the quality meeting the setting requirement reported by the second node device can be obtained, and the accuracy of aggregated data corresponding to the first task obtained based on the aggregation of the obtained first data is improved.

As another embodiment of the present invention, the task processing method further includes:

a first parameter is determined for each node device in the mobile wisdom-aware network.

Here, the server may set a first parameter of a node device that first accesses the mobile wisdom group aware network to an initial value. The value of the first parameter is any value between 0 and 1. For example, the initial value may be 0.5.

The server can also update the first parameter of each node device based on the related information of the node device and the set first parameter configuration mode. The related information of the node device includes location information, task completion rate, and the like. The task completion rate characterizes the ratio between the number of completed tasks and the total number of participating historical tasks. The first set parameter configuration mode represents that the set first parameter corresponding to the urban central area is larger than the set first parameter corresponding to the suburban area; it is also characterized that the higher the task completion rate, the larger the value of the corresponding set first parameter.

It should be noted that, in order to improve the information security, when the node device first applies for accessing the mobile intelligent group awareness network, the server performs identity authentication on the node device, and when the identity authentication passes, the node device is allowed to access the mobile intelligent group awareness network; and when the authentication fails, the node equipment is not allowed to access the mobile intelligent group awareness network. The method for the server to authenticate the node device may be as follows: sending a first verification code to the node equipment, comparing whether the first verification code is the same as a second verification code when the second verification code sent by the node equipment is received, and representing that the identity verification passes when the first verification code is the same as the second verification code; and when the first verification code and the second verification code are different, the identity verification is failed.

In an embodiment, the determining the first parameter of each node device in the mobile wisdom group aware network includes:

Here, the set first parameter may correspond to an index value of one set evaluation index, or may correspond to an index value of at least two set evaluation indexes. That is to say, when at least two setting indexes correspond to the node device, one corresponding first parameter is determined by the index values of all the setting indexes corresponding to the node device.

When determining the index values corresponding to all the evaluation indexes corresponding to the node equipment, the server determines a new first parameter corresponding to the node equipment based on the corresponding relation between the set first parameter and the index values corresponding to all the evaluation indexes, and updates the first parameter of the node equipment to the new first parameter.

In one embodiment, the set evaluation index includes at least one of:

location information of the node device;

task completion rate of the node device.

When the density of the terminal device corresponding to the first coverage area is greater than the density of the terminal device corresponding to the second coverage area, the set first parameter corresponding to the first coverage area is greater than the set first parameter corresponding to the second coverage area.

In practical applications, when the node device is a terminal device for executing the first task, the set evaluation index may be at least one of an active area corresponding to the node device and a task completion rate of the node device.

When the node device is a node device for mobile edge calculation, the set evaluation index includes at least one of the following:

location information of the node device;

task completion rate of the node device.

According to the scheme, the first parameter of the node equipment is determined based on the set evaluation index, the first parameter can be determined more accurately, and the first node equipment of which the quality of the acquired data meets the set requirement can be determined accurately based on the first parameter.

As another embodiment of the present invention, fig. 5 is a schematic flow chart illustrating an implementation of a task processing method according to another embodiment of the present invention. On the basis of the embodiment corresponding to fig. 3, the present embodiment further includes:

s303: updating the first parameter of each of the at least one second node device based on the score corresponding to the first task. And obtaining the score corresponding to the first task after determining the aggregated data corresponding to the first task.

Here, the cloud server transmits the second aggregated data corresponding to the first task to the terminal device that issued the first task, when determining the second aggregated data corresponding to the first task.

The cloud server obtains the score corresponding to the first task, and sends the score corresponding to the first task to the second node equipment for mobile edge computing. The numerical interval corresponding to the score corresponding to the first task is 0 to 1.

And under the condition that the score corresponding to the first task is obtained, the cloud server updates the first parameter of the second node equipment for the mobile edge computing to the score corresponding to the first task.

And under the condition that the second node equipment for the mobile edge calculation acquires the score corresponding to the first task, updating the first parameter of the terminal equipment for executing the first task to the score corresponding to the first task.

The score corresponding to the first task may be sent to the cloud server when the terminal device issuing the first task acquires the score input by the task issuer.

When the attribute information of the first task includes the expected result corresponding to the first task, since the terminal device and the cloud server that issue the first task both store the attribute information of the first task, the score of the first task may also be determined by the terminal device or the cloud server that issues the first task based on the expected result corresponding to the first task and the second aggregation data corresponding to the first task. Here, an error value may be calculated based on the expected result corresponding to the first task and the second aggregated data corresponding to the first task, and a score corresponding to the calculated error value may be determined based on a correspondence between the set error value and the set score, so as to obtain the score corresponding to the first task.

It should be noted that the server may allocate resources for each terminal device based on the first parameter corresponding to the terminal device executing the first task and based on the budget corresponding to the first task. And the sum of the resources allocated to all the terminal devices is equal to the resource represented by the budget corresponding to the first task.

According to the scheme, the first parameter of each second node device in the at least one second node device is updated based on the score corresponding to the first task, and the first parameter of the node device can be dynamically updated, so that the accuracy of the first parameter is improved.

In the embodiment corresponding to fig. 5, a method for updating the first parameter of the second node device based on the score corresponding to the first task is described, and another implementation method for updating the first parameter based on the score corresponding to the first task is described below. Referring to fig. 6, fig. 6 is a schematic diagram illustrating an implementation flow of updating a first parameter in a task processing method according to an embodiment of the present invention. As shown in fig. 6, when the first parameter of each of the at least one second node device is updated based on the score corresponding to the first task, the method includes:

s601: and determining an offset value corresponding to the second node equipment based on the first data reported by the second node equipment, the aggregation data corresponding to the first task and the score corresponding to the first task.

Here, the server calculates a product between the aggregated data corresponding to the first task and the score corresponding to the first task, calculates a difference between the first data reported by the second node device and the product, and calculates an offset value corresponding to the second node device based on the difference.

In practical applications, the deviation value corresponding to the second node device may be calculated based on the following formula:

when the server is a node device for mobile edge computing, the second node device is a second terminal device for executing the first task. At this time, the server determines an offset value corresponding to the second terminal device based on the first data reported by the second terminal device for executing the first task, the first fusion data corresponding to the first task, and the score corresponding to the first task. d_iRepresenting a deviation value corresponding to the ith second terminal device; s_iCharacterizing first data reported by the ith second terminal device; s_cCharacterizing first fusion data corresponding to a first task determined by a server; g characterizes the score corresponding to the first task, 0<g<1; n represents the total number of the second terminal equipment accessed to the server; r is_iAnd characterizing a first parameter corresponding to the ith second terminal device.

When the server serves as a cloud, the second node device is a second node device for performing mobile edge computing. At this time, the cloudThe server determines an offset value corresponding to the second node device for performing the mobile edge calculation based on the first aggregated data reported by the second node device for performing the mobile edge calculation, the second fused data corresponding to the first task, and the score corresponding to the first task. And determining second fusion data corresponding to the first task by the cloud server. d_iRepresenting a deviation value corresponding to the ith second node equipment for calculating the moving edge; s_iCharacterizing first fusion data reported by the ith node equipment for executing mobile edge calculation; s_cCharacterizing second fusion data corresponding to the first task determined by the cloud server; g represents the score corresponding to the first task, and n represents the total number of the second node devices accessed to the cloud server; r is_iAnd characterizing a first parameter corresponding to the ith second node device.

In addition, d is_iThe smaller the value of (d), the higher the confidence of the data representing the corresponding second node device, and the better the data quality.

In one embodiment, when S is_iFor two-dimensional data or multi-dimensional data, e.g. multi-dimensional vectors, with different S_iMay not be of the same order of magnitude, so that when S is_iFor two-dimensional data or multi-dimensional data, pair S_iCarrying out normalization process, d_iThe expression of (a) is as follows:

wherein S is_ikCharacterizing first data of a kth dimension reported by an ith second node device; [ R ]_k,L_k]And characterizing the value interval of the k-th dimension data, wherein m characterizes the first data as m-dimension data.

It should be noted that, when the first data reported by the second node device is one-dimensional data, the offset value corresponding to the second node device is calculated based on the above formulas (1-1) and (1-2). And when the first data reported by the second node equipment is two-dimensional data or multi-dimensional data, calculating an offset value corresponding to the second node equipment based on the formulas (1-3) and (1-2).

S602: and updating the first parameter of the second node device based on the deviation value corresponding to the second node device.

Here, when the offset value of the second node apparatus is zero, the first parameter of the second node apparatus is kept unchanged. When the offset value of the second node device is not equal to zero, the server may determine an adjustment range corresponding to the second node device based on a set correspondence between the offset value and the adjustment range of the first parameter; and updating the first parameter of the second node equipment based on the current first parameter of the second node equipment and the determined adjustment amplitude.

According to the scheme, the deviation value corresponding to the second node equipment can be accurately determined based on the first data reported by the second node equipment, the aggregated data corresponding to the first task and the score corresponding to the first task, the accuracy of the deviation value is improved, the first parameter of the second node equipment is updated based on the deviation value corresponding to the second node equipment, and the accuracy of the first parameter can be improved.

In an embodiment, fig. 7 is a schematic flow chart illustrating an implementation process of updating a first parameter in a task processing method according to an embodiment of the present invention. Referring to fig. 7, the updating the first parameter of the second node device based on the deviation value corresponding to the second node device includes:

s701: and determining a first parameter calculation mode corresponding to the second node equipment based on the deviation value corresponding to the second node equipment.

And the server compares the deviation value corresponding to the second node equipment with zero to obtain a first comparison result, and determines a first parameter calculation mode corresponding to the second node equipment based on the first comparison result. Wherein the content of the first and second substances,

the first parameter calculation method is preset.

And when the first comparison result represents that the deviation value corresponding to the second node equipment is equal to zero, the determined first calculation mode represents that the first parameter is kept unchanged.

And when the first comparison result represents that the deviation value corresponding to the second node equipment is greater than zero, the determined first calculation mode represents that the first parameter is increased.

And when the first comparison result represents that the deviation value corresponding to the second node equipment is less than zero, the determined first calculation mode represents that the first parameter is increased.

The first amplification is smaller than the second amplification. The first amplification is the amplification amplitude of the first parameter when the deviation value corresponding to the second node device is greater than zero. The second amplification is the amplification amplitude of the first parameter when the deviation value corresponding to the second node device is less than zero.

S702: and updating the first parameter of the second node equipment based on the first parameter calculation mode corresponding to the second node equipment.

The server acquires values of all calculation parameters included in the first parameter calculation mode based on the first parameter calculation mode corresponding to the second node device, substitutes the acquired values of all calculation parameters into the first parameter calculation mode, calculates a new first parameter corresponding to the second node device, and updates the first parameter of the second node device to the new first parameter.

According to the scheme, the server calculates the new first parameter corresponding to the second node device based on the first parameter calculation mode, and the accuracy of the first parameter can be further improved.

In an embodiment, in order to more accurately calculate a new first parameter corresponding to the second device, when determining, based on the deviation value corresponding to the second node device, a first parameter calculation method for updating the second node device corresponding to the second node device, the method further includes one of the following steps:

Here, the median is determined by: and the server arranges the deviation values corresponding to all the second node devices in a descending order to obtain a deviation value sequence, and determines the deviation value in the middle of the deviation value sequence as a median. When the total number of the deviation values in the deviation value sequence is an even number, any one of the 2 deviation values in the middle may be determined as a median.

It should be noted that, when the server is a node device for moving edge calculation, the median is determined based on the deviation value corresponding to each of the second terminal devices for executing the first task. When the server is a cloud server, the median is determined based on the deviation value corresponding to the second node device for the mobile edge computing.

In practical application, the server may compare the median with the deviation value corresponding to the second node device to obtain a second comparison result, and determine a first parameter calculation manner corresponding to the second node device based on the second comparison result.

In practical application, in order to identify a malicious attacker and improve the reliability of the first data reported by the second node device, the server may also calculate a first sum between the set adjustment parameter and the median, compare the deviation value corresponding to the second node device with the first sum to obtain a third comparison result, and determine a first parameter calculation mode corresponding to the second node device based on the third comparison result.

In one embodiment, to improve the accuracy of the calculated new first parameter, the first parameter calculation mode includes one of the following:

the first parameter remains unchanged;

In practical application, when the second comparison result represents that the deviation value corresponding to the second node device is smaller than the median, the determined first parameter calculation mode represents that: and calculating a new first parameter based on the current first parameter, the deviation value and the set first correction coefficient.

When the second comparison result represents that the deviation value corresponding to the second node device is equal to the median, the determined first parameter calculation mode represents that: the first parameter remains unchanged.

When the second comparison result represents that the deviation value corresponding to the second node equipment is greater than the median, the determined first parameter calculation mode represents that: and calculating a new first parameter based on the current first parameter, the deviation value, the median and the set second correction coefficient.

Illustratively, the expression of the first parameter calculation method is as follows:

wherein r is_i ^newRepresenting a new first parameter corresponding to the ith second node device; r is_iCharacterizing a current first parameter corresponding to the ith second node device; d_iRepresenting a deviation value corresponding to the ith second node device; gamma represents a set first correction coefficient and is used for correcting the first parameter; d_avgThe calculated median is characterized.

In practical application, when the third comparison result represents that the deviation value corresponding to the second node device is smaller than the first sum, the determined first parameter calculation mode represents that: and calculating a new first parameter based on the current first parameter, the deviation value and the set first correction coefficient.

When the third comparison result represents that the deviation value corresponding to the second node device is equal to the first sum, the determined first parameter calculation mode represents that: the first parameter remains unchanged.

When the third comparison result represents that the deviation value corresponding to the second node device is greater than the first sum, the determined first parameter calculation mode represents that: and calculating a new first parameter based on the current first parameter, the deviation value, the median and the set second correction coefficient.

wherein eta represents a set second correction coefficient and is used for correcting the first parameter; and the lambda represents a set adjusting parameter for adjusting the median. (d)_avg+ λ) characterizes the first sum.

The set first correction coefficient γ and the set second correction coefficient η are different from each other, and both of them may be set according to actual conditions.

Referring to fig. 8 and fig. 9 together, fig. 8 shows a graph of a first parameter when the second node device continuously reports trusted data according to the embodiment of the present invention; fig. 9 is a graph illustrating a first parameter when the second node device continuously reports the untrusted data according to the embodiment of the present invention. Wherein the content of the first and second substances,

the vertical axis in fig. 8 and 9 characterizes the first parameter. When the deviation value corresponding to the first data is smaller than or equal to the calculated median, representing that the first data reported by the corresponding second node equipment is credible data; and when the deviation value corresponding to the first data is greater than the calculated median, representing that the first data reported by the corresponding second node equipment is untrusted data. Or, when the deviation value corresponding to the first data is less than or equal to (d)_avg+ lambda), representing that the first data reported by the corresponding second node device is credible data; the deviation value corresponding to the first data is greater than (d)_avg+ λ), the first data reported by the corresponding second node device is represented as untrusted data.

Fig. 8 reflects the effect of different gamma on the first parameter as the number of times trusted data is submitted increases. When the second node device submits the trusted data continuously, the first parameter of the second node device gradually converges to 1; and the larger gamma is, the faster the first parameter converges, so that an appropriate gamma value should be dynamically set according to an actual application scene. When gamma is large, the second node equipment can easily obtain high first parameters, possibly causing malicious node equipment to provide certain times of trusted data to quickly accumulate and promote the first parameters, and then providing false data to enable the first parameters to be always larger than or equal to the set threshold corresponding to the first parameters; however, γ cannot be set too small, otherwise, the increasing amplitude of the first parameter of the node device is not obvious, so that the first parameter cannot reach the set threshold corresponding to the first parameter.

Fig. 9 shows that the first parameter converges gradually to 0 as the second node device continuously submits the false untrusted data, and the larger η, the faster the first parameter converges. Similarly, an appropriate value of η should be dynamically set, and when η is large, the second node device may provide first data with large deviation due to occasional network failure or other objective reasons, so that the first parameter of the second node device is reduced too much; but η cannot be too small, otherwise the malicious second node device may intermittently submit false untrusted data such that the first parameter remains within the safe range, i.e. the first parameter is greater than or equal to the set threshold corresponding to the first parameter.

Fig. 10 is a schematic diagram illustrating an implementation flow of updating a first parameter in a task processing method according to an application embodiment of the present invention. Referring to fig. 10, the method of updating the first parameter includes:

s801: and receiving first data corresponding to the first task reported by the second node equipment.

The server receives first data corresponding to the first task reported by the second node device.

When the server is a second node device for mobile edge computing, the second node device reporting the first data corresponds to a terminal device for executing the first task, and the reported first data is data collected by the terminal device when executing the first task.

When the server is a cloud server, the second node device corresponds to a node device for mobile edge computing, and the reported first data is first aggregated data.

S802: and judging whether the identity of the second node equipment is legal or not.

And the server judges whether the identity of the second node equipment is legal or not by carrying out identity authentication on the second node equipment. When the authentication result represents that the authentication of the second node device fails, the identity of the second node device is represented to be illegal, and S803 is executed; and when the identity verification result represents that the identity verification of the second node equipment passes, representing that the identity of the second node equipment is legal, and executing S804.

S803: and discarding the first data reported by the second node equipment.

S804: and storing the first data reported by the second node equipment.

S805: and judging whether the set cutoff condition is met.

The set cutoff condition may represent that the task end time of the first task is reached, and may also represent that the first data reported by all the second node devices has been stored.

When the set cutoff condition is satisfied, executing S806; if the set cutoff condition is not satisfied, the process returns to S801.

S806: and determining the aggregated data corresponding to the first task based on all the stored first data.

The implementation process of S806 is described with reference to S302 in the embodiment corresponding to fig. 3, and is not described herein again.

S807: and judging whether the score corresponding to the first task is obtained or not.

Executing S808 when the judgment result represents that the score corresponding to the first task is not obtained;

and executing S809 when the judgment result represents that the score corresponding to the first task is obtained.

S808: the score corresponding to the first task is set to 1.

Here, after S808 is executed, S809 is executed.

S809: and updating the first parameter of the second equipment corresponding to each saved first data based on the score corresponding to the first task and the aggregated data corresponding to the first task.

Here, the server calculates a new first parameter based on the formula (1-4) or the formula (1-5) and updates the first parameter of the second device to the new first parameter according to the above-described embodiment.

According to the scheme, the server can accurately calculate the new first parameter based on the first parameter calculation mode, so that the first parameter of the second node device is updated based on the new first parameter, and the accuracy of the first parameter can be improved.

In order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides a task processing device, which is disposed on a server, and as shown in fig. 11, the task processing device includes:

the task allocation unit 11 is configured to issue a first task to each second node device in the at least one second node device based on the first parameter of each first node device in the at least one first node device;

an aggregation unit 12, configured to determine, based on first data reported by each second node device of the at least one second node device, aggregated data corresponding to the first task; wherein the content of the first and second substances,

In one embodiment, the task processing apparatus further includes:

a first determining unit, configured to determine a first parameter of each node device in the mobile wisdom group awareness network.

In an embodiment, the first determining unit is configured to:

In one embodiment, the set evaluation index includes at least one of:

location information of the node device;

task completion rate of the node device.

In one embodiment, the task processing apparatus further includes:

a first updating unit, configured to update a first parameter of each of the at least one second node device based on a score corresponding to the first task; wherein the content of the first and second substances,

In one embodiment, the task processing apparatus further includes:

a second determining unit, configured to determine, based on the first data reported by the second node device, the aggregated data corresponding to the first task, and the score corresponding to the first task, an offset value corresponding to the second node device;

and the second updating unit is used for updating the first parameter of the second node device based on the deviation value corresponding to the second node device.

In an embodiment, the second updating unit is configured to:

In an embodiment, the second updating unit is further configured to perform one of:

In one embodiment, the first parameter calculation method includes one of the following:

the first parameter remains unchanged;

In an embodiment, the node device comprises one of:

a server for mobile edge computing;

a terminal device for performing a first task.

In practical applications, each unit included in the task processing device may be implemented by a processor in the task processing device, or implemented by the processor and the communication interface together. Of course, the processor needs to run the program stored in the memory to realize the functions of the above-described program modules.

It should be noted that: in the task processing provided in the above embodiments, only the division of the program modules is exemplified when processing the tasks, and in practical applications, the processing may be distributed to different program modules according to needs, that is, the internal structure of the task processing device may be divided into different program modules to complete all or part of the processing described above. In addition, the task processing device and the task processing method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments for details, which are not described herein again.

Based on the hardware implementation of the program module, in order to implement the method of the embodiment of the present invention, the embodiment of the present invention further provides a server. Fig. 12 is a schematic diagram of a hardware composition structure of a server according to an embodiment of the present invention, and as shown in fig. 12, the server includes:

a communication interface 1 capable of information interaction with other devices such as a server and the like;

and the processor 2 is connected with the communication interface 1 to realize information interaction with other equipment, and is used for executing the task processing method provided by one or more technical schemes when running a computer program. And the computer program is stored on the memory 3.

Of course, in practice, the various components in the server are coupled together by a bus system 4. It will be appreciated that the bus system 4 is used to enable connection communication between these components. The bus system 4 comprises, in addition to a data bus, a power bus, a control bus and a status signal bus. For clarity of illustration, however, the various buses are labeled as bus system 4 in fig. 12.

The memory 3 in the embodiment of the present invention is used to store various types of data to support the operation of the server. Examples of such data include: any computer program for operating on a server.

It will be appreciated that the memory 3 may be either volatile memory or nonvolatile memory, and may include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced Synchronous Dynamic Random Access Memory), Synchronous linked Dynamic Random Access Memory (DRAM, Synchronous Link Dynamic Random Access Memory), Direct Memory (DRmb Random Access Memory). The memory 3 described in the embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.

The method disclosed by the above embodiment of the present invention can be applied to the processor 2, or implemented by the processor 2. The processor 2 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 2. The processor 2 described above may be a general purpose processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 2 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 3, and the processor 2 reads the program in the memory 3 and in combination with its hardware performs the steps of the aforementioned method.

When the processor 2 executes the program, the process corresponding to the multi-core processor in each method according to the embodiment of the present invention is realized, and for brevity, no further description is given here.

In an exemplary embodiment, the embodiment of the present invention further provides a storage medium, specifically a computer storage medium, which is a computer readable storage medium, for example, including a memory 3 storing a computer program, where the computer program is executable by a processor 2 to perform the steps in the embodiments corresponding to fig. 3 to 7 and 10. The computer readable storage medium may be Memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disk, or CD-ROM.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple 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 coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

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, that is, 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, all the functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may be separately used as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The technical means described in the embodiments of the present invention may be arbitrarily combined without conflict.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims

1. A task processing method, comprising:

2. The method of claim 1, further comprising:

3. The method according to claim 1 or 2, characterized in that the method further comprises:

4. The method of claim 2, wherein determining the first parameter for each node device in the mobile wisdom-aware network comprises:

5. The method according to claim 4, wherein the set evaluation index includes at least one of:

location information of the node device;

task completion rate of the node device.

6. The method according to claim 3, wherein when updating the first parameter of each of the at least one second node device based on the score corresponding to the first task, the method comprises:

7. The method of claim 6, wherein updating the first parameter of the second node device based on the corresponding bias value of the second node device comprises:

8. The method of claim 7, wherein when determining, based on the deviation value corresponding to the second node device, a first parameter calculation manner for updating the second node device corresponding to the second node device, further comprises one of:

9. The method of claim 7 or 8, wherein the first parameter calculation comprises one of:

the first parameter remains unchanged;

10. The method of claim 1, wherein the node device comprises one of:

a server for mobile edge computing;

a terminal device for performing a first task.

11. A task processing apparatus, comprising:

12. A server, comprising: a processor and a memory for storing a computer program capable of running on the processor,

wherein the processor is adapted to perform the steps of the method of any one of claims 1 to 10 when running the computer program.

13. A storage medium having a computer program stored thereon, the computer program, when being executed by a processor, realizing the steps of the method of any one of claims 1 to 10.