Method and Device for Determining Risk Value of Operating System Task

Abstract

A method, apparatus, device, and storage medium for determining the risk value of a job system task provided by this application include: obtaining the parameters of each node in the job system; determining the delay risk level of each node according to the parameters; determining the delay risk level of the job system according to the delay risk level of each node, and adjusting the values of the start job time and the overdue threshold value of the nodes whose delay risk level exceeds the preset delay risk level. By adopting this technical solution, it is possible to evaluate the delay risk level of a single node, and further evaluate the overall delay risk situation of the job system. Furthermore, it is possible to adjust the parameters of the nodes in the job system according to the overall delay risk situation, so as to achieve the purpose of reducing the delay rate of the actual jobs of the nodes.

Description

Technical Field

[0001] The present application relates to the technical field of business system operations, and in particular, to a method, apparatus, device, and storage medium for determining the risk value of job system tasks. Background Art

[0002] Currently, information exchange is often required in the background of business systems related to finance. To ensure the smooth implementation of business operations, each node in the job chain is usually incorporated into a unified monitoring and alerting platform for monitoring, so as to trigger an alert when the job is delayed.

[0003] However, the successful execution of the job chain is determined by numerous parameters, which include not only static parameters such as the setting of the delay threshold, the start time point of the job chain task, and the maximum allowable execution duration of the task, but also the relationship of the tasks, such as the series and parallel connections between task nodes in the job chain and the sequence of tasks.

[0004] Therefore, there is an urgent need for a method for determining the risk value of job system tasks, which can evaluate the delay risk level of a single node, and then evaluate the overall delay risk situation of the job system, and then can adjust the parameters of the nodes in the job system according to the overall delay risk situation, so as to achieve the purpose of reducing the delay rate of the actual jobs of the nodes. Summary of the Invention

[0005] The present application provides a method, apparatus, device, and storage medium for determining the risk value of job system tasks, which can evaluate the delay risk level of a single node, and then evaluate the overall delay risk situation of the job system, and then can adjust the parameters of the nodes in the job system according to the overall delay risk situation, so as to achieve the purpose of reducing the delay rate of the actual jobs of the nodes.

[0006] In a first aspect, the present application provides a method for adjusting parameters of job system task nodes, the method comprising:

[0007] Obtain the parameters of each node in the job system; wherein, the parameters include: the value of the start job time, the value of the execution duration, and the value of the overdue threshold; wherein, the job system includes multiple nodes; wherein, there is a connection relationship between different nodes; the connection relationship includes series and parallel.

[0008] Determine the delay risk level of each node according to the parameters.

[0009] Determine the delay risk level of the job system according to the delay risk level of each node, and adjust the value of the start job time and the value of the overdue threshold of the nodes whose delay risk level exceeds the preset delay risk level.

[0010] In one example, according to the parameters, determining the delay risk level of each node includes:

[0011] Calculating the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node according to the parameters of the initial node and the start job times and the overdue thresholds of the nodes connected to the initial node;

[0012] Determining the delay risk level of each node according to the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node.

[0013] In one example, calculating the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node according to the parameters of the initial node and the start job times and the overdue thresholds of the nodes connected to the initial node includes:

[0014] Calculating the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node according to the relationship between the first sum value and the second sum value; wherein, the first sum value is the sum of the start job time, the execution duration, and the overdue threshold of the initial node; the second sum value is the sum of the start job time and the overdue threshold of the node connected to the initial node.

[0015] In one example, sending the data information of the nodes whose delay risk levels exceed the preset delay risk level to the user to prompt the user to modify the start job time and the overdue threshold of the nodes.

[0016] In one example, adjusting the value of the start job time of the nodes whose delay risk levels exceed the preset delay risk level includes:

[0017] Calculating the delay margin of the nodes whose delay risk levels exceed the preset delay risk level, and determining the start job time of the nodes connected to the nodes according to the delay margin.

[0018] In a second aspect, the present application provides a processing device for data information to be traded, and the device includes:

[0019] An acquisition unit, configured to acquire the parameters of each node in the job system; wherein, the parameters include: the value of the start job time, the value of the execution duration, and the value of the overdue threshold; wherein, there are multiple nodes in the job system; wherein, there is a connection relationship between different nodes; the connection relationship includes series and parallel;

[0020] A determination unit, configured to determine the delay risk level of each node according to the parameters;

[0021] An adjustment unit, configured to determine the delay risk level of the job system according to the delay risk level of each node, and adjust the values of the starting job time and the overdue threshold of the nodes whose delay risk level exceeds the preset delay risk level.

[0022] A calculation module, configured to calculate the delay risk level of the initial node and the delay risk level of the nodes connected to the initial node according to the parameters of the initial node and the starting job time and the overdue threshold of the nodes connected to the initial node;

[0023] A determination module, configured to determine the delay risk level of each node according to the delay risk level of the initial node and the delay risk level of the nodes connected to the initial node.

[0024] In one example, the calculation module includes:

[0025] A calculation sub-module, configured to calculate the delay risk level of the initial node and the delay risk level of the nodes connected to the initial node according to the relationship between the first sum value and the second sum value; wherein, the first sum value is the sum of the starting job time, the execution duration, and the overdue threshold of the initial node; the second sum value is the sum of the starting job time and the overdue threshold of the nodes connected to the initial node.

[0026] In one example, the apparatus further includes:

[0027] A sending unit, configured to send the data information of the nodes whose delay risk level exceeds the preset delay risk level to the user, so as to prompt the user to modify the starting job time and the overdue threshold of the nodes.

[0028] In one example, the adjustment unit includes:

[0029] An adjustment module, configured to calculate the delay margin of the nodes whose delay risk level exceeds the preset delay risk level, and determine the starting job time of the nodes connected to the nodes according to the delay margin.

[0030] In a third aspect, the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0031] The memory stores computer execution instructions;

[0032] The processor executes the computer execution instructions stored in the memory to implement the method as described in the first aspect.

[0033] Fourthly, the present application provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method described in the first aspect when executed by a processor.

[0034] Fifthly, the present application provides a computer program product including a computer program, which implements the method described in the first aspect when executed by a processor.

[0035] A method, apparatus, device, and storage medium for determining the risk value of an operating system task provided by the present application include: obtaining parameters of each node in the operating system; where the parameters include: the value of the starting job time, the value of the execution duration, and the value of the overdue threshold; where there are multiple nodes in the operating system; where there is a connection relationship between different nodes; the connection relationship includes series and parallel; determining the delay risk level of each node according to the parameters; determining the delay risk level of the operating system according to the delay risk level of each node, and adjusting the value of the starting job time and the value of the overdue threshold of the nodes whose delay risk level exceeds the preset delay risk level. By adopting the technical solution, the delay risk level of a single node can be evaluated, and then the overall delay risk situation of the operating system can be evaluated, and then the parameters of the nodes in the operating system can be adjusted according to the overall delay risk situation to achieve the purpose of reducing the delay rate of the actual operation of the nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings here are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0037] Figure 1 is a schematic flowchart of a method for determining the risk value of an operating system task according to Embodiment 1 of the present application;

[0038] Figure 2 is a schematic flowchart of a method for adjusting the parameters of an operating system task node according to Embodiment 2 of the present application;

[0039] Figure 3 is a schematic structural diagram of a device for adjusting the parameters of an operating system task node according to Embodiment 3 of the present application;

[0040] Figure 4 is a schematic structural diagram of a device for adjusting the parameters of an operating system task node according to Embodiment 4 of the present application;

[0041] Figure 5 is a block diagram of an electronic device shown according to an exemplary embodiment.

[0042] Through the above-mentioned drawings, specific embodiments of the present application have been shown, and more detailed descriptions will be provided hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed Embodiments

[0043] Here, exemplary embodiments will be described in detail, and examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0044] A method for determining the risk value of a job system task provided by the present application aims to solve the above technical problems in the prior art.

[0045] The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail below with specific embodiments. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the drawings.

[0046] Figure 1 is a schematic flowchart of a method for determining the risk value of a job system task according to Embodiment 1 of the present application. The method in Embodiment 1 includes the following steps:

[0047] S101. Obtain the parameters of each node in the job system; wherein, the parameters include: the value of the starting job time, the value of the execution duration, and the value of the overdue threshold; wherein, the job system includes multiple nodes; wherein, there is a connection relationship between different nodes; the connection relationship includes series and parallel.

[0048] In one example, the job system can be constructed using the Neo4j graph database engine. Among them, the Neo4j graph database is a high-performance NOSQL graph database engine with advantages such as being embedded, high-performance, and lightweight. Among them, the Neo4j graph database can include multiple nodes. The job system includes multiple nodes, and different nodes have a connection relationship.

[0049] The elements of each node include: node ID, task name, whether it is a sub-task, the value of the overdue threshold, the delay risk level, the definition of the warning response strategy, the consecutive successful execution frequency, and other relevant information, as well as the information of the previous and subsequent nodes. In this embodiment, there are two types of nodes: one is a rigid node, and the other is an elastic node; among them, a rigid node is a node that cannot tolerate overdue execution or whose overdue execution will cause business failure, and an elastic node is the opposite node.

[0050] S102. Determine the delay risk level of each node according to the parameters.

[0051] In this embodiment, the delay risk level can be set by itself. For example, the delay risk level can be divided into 6 levels. Among them, the above levels can be divided into the lowest risk level of 1, the second lowest risk level of 2, and arranged in sequence to the risk level of 6.

[0052] S103. Determine the delay risk level of the job system according to the delay risk level of each node, and adjust the values of the start job time and the overdue threshold of the nodes whose delay risk level exceeds the preset delay risk level.

[0053] In this embodiment, the value obtained by multiplying the delay risk level of each node by the node depth of the node and then summing them up can obtain the delay risk level of the job system. For example, if the delay risk level of each node is Ri and the node depth of the node is Di, then the delay risk level of the job system is R, and R = ∑R i ·D i , i = 1, 2, 3..., n.

[0054] If there is a node whose delay risk level exceeds the preset delay risk level, the parameters of the node can be adjusted. For example, the value of the overdue threshold of the node can be adjusted. Specifically, the value of the overdue threshold can be increased. However, if the value of the start job time of the node is still in a delayed state after adjusting the value of the overdue threshold of the node, the value of the start job time of the node is adjusted. Specifically, a prediction suggestion can be provided by the three-standard-deviation method. The staff adjusts the node with this delay risk level according to the prompt of the node delay risk level. Specifically, the adjustment is as follows:

[0055] The start job time of the node records the situation of historical nodes in chronological order. The sample Ti records that the start job time of the node starts at 0:00. The sampling does not include abnormal values exceeding the overdue threshold. Because it is to adjust the start job time, the abnormal situation is controlled by the overdue threshold. The average value of the execution duration is Ta. Then, according to the standard deviation formula:

[0056]

[0057] For \(i = 1, 2, \ldots, n\), where \(n\) corresponds to the minute moment when the historical node is successfully executed, the range of the optional starting job moment parameter provided for the user is: \(T_a - 3\sigma \lt \xi \lt T_a + 3\sigma\). After each successful invocation, update the range of the starting job moment parameter, and obtain the delay risk level of the job system and the delay risk level of the current node in real time. Among them, record the value of the execution duration of the job system in the log to form a mean sample under the mean strategy.

[0058] Furthermore, configure the parameter adjustment strategy for each node, and the specific strategy has a complex design scheme. For example, the parameter range strategy for the starting job moment can be:

[0059] 1. Fix \(T = T_a+\) optional multiple standard deviation \(\sigma\), and the multiple ranges from -3 to +3;

[0060] 2. Set \(T = T_a\);

[0061] 3. Set \(T_a+\) set a fixed value, which floats according to \(T_a\). Among them, \(T_a\) is the value of the execution duration of the node.

[0062] A method, device, equipment and storage medium for determining the risk value of a job system task provided by the present application include: obtaining the parameters of each node in the job system; among them, the parameters include: the value of the starting job moment, the value of the execution duration, and the value of the overdue threshold; among them, the job system includes multiple nodes; among them, there is a connection relationship between different nodes; the connection relationship includes series and parallel; determining the delay risk level of each node according to the parameters; determining the delay risk level of the job system according to the delay risk level of each node, and adjusting the value of the starting job moment and the value of the overdue threshold of the node whose delay risk level exceeds the preset delay risk level. By adopting the technical solution, it is possible to evaluate the delay risk level of a single node, and further evaluate the overall delay risk situation of the job system, and then be able to adjust the parameters of the nodes in the job system according to the overall delay risk situation to achieve the purpose of reducing the delay rate of the actual operation of the nodes.

[0063] Figure 2 It is a schematic flowchart of a method for adjusting the parameters of a job system task node according to Embodiment 2 of the present application. The method in Embodiment 2 includes the following steps:

[0064] S201. Obtain the parameters of each node in the job system; among them, the parameters include: the value of the starting job moment, the value of the execution duration, and the value of the overdue threshold; among them, the job system includes multiple nodes; among them, there is a connection relationship between different nodes; the connection relationship includes series and parallel.

[0065] Exemplarily, this step can refer to step S101, which will not be elaborated here.

[0066] S202. Calculate the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node according to the parameters of the initial node, the start job times and overdue thresholds of the nodes connected to the initial node.

[0067] Exemplarily, the initial node is the first node. For example, the start job time of the initial node can be Sa, the start job time of the first node connected to this initial node can be Sb, the start job time of the second node connected to the first node can be Sc, and the start job time of the third node connected to the second node can be Sd. Further, the overdue threshold of the initial node can be La, the overdue threshold of the first node connected to this initial node can be Lb, the overdue threshold of the second node connected to the first node can be Lc, and the overdue threshold of the third node connected to the second node can be Ld. The value of the execution duration of the initial node can be Ta, the value of the execution duration of the first node connected to this initial node can be Tb, the value of the execution duration of the second node connected to the first node can be Tc, and the value of the execution duration of the third node connected to the second node can be Td.

[0068] Among them, the initial node can be A, the first node connected to the initial node can be B, the second node can be C, and the third node can be D. Among them, each node has different levels of delay risk levels. Specifically, the delay risk levels can be divided into delay risk level 1, delay risk level 2, delay risk level 3, delay risk level 4, delay risk level 5, and delay risk level 6. Among them, the weights of different delay risk levels are different, and the specific information of the delay risk levels is also recorded on the nodes.

[0069] In this embodiment, the delay risk level of the initial node A and the delay risk level of the first node B connected to the initial node A are obtained according to the start job time Sa of the initial node A and the overdue threshold La of the initial node.

[0070] S203. Determine the delay risk level of each node according to the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node.

[0071] Exemplarily, calculating the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node according to the parameters of the initial node, the start job times and overdue thresholds of the nodes connected to the initial node includes:

[0072] Calculate the delay risk level of the initial node and the delay risk levels of the nodes connected to the initial node according to the relationship between the first sum value and the second sum value; where the first sum value is the sum of the start operation time, execution duration, and overdue threshold of the initial node; the second sum value is the sum of the start operation time and overdue threshold of the node connected to the initial node.

[0073] Exemplarily, the delay risk level of the initial node is calculated as: Sa + Ta + La < Sb, that is, the initial node A starts late and the end time of normal execution is earlier than that of the subsequent node, and the risk is the delay risk level 1;

[0074] Further, Sa + Ta < Sb, that is, the initial node A starts normally and the end time of normal execution is earlier than that of the subsequent node, and the risk is the delay risk level 2; where Sa + Ta is the first sum value; Sb is the second sum value;

[0075] Further, Sa + Ta > Sb and Sa + Ta + La < Sb + Lb. Although the normal execution of the initial node A will affect the start of the first node B on schedule, it is within the allowable delay range of the first node B, and the risk is the delay risk level 3; where Sa + Ta + La is the first sum value; Sb + Lb is the second sum value;

[0076] Further, Sa + Ta > Sb and Sa + Ta < Sb + Lb and Sa + Ta + La > Sb + Lb. The normal execution of the initial node A will affect the start of the first node B on schedule. If the delay of the initial node A is not considered, if the upper limit of the delay of the initial node A is reached, the first node B will fail to start, and the risk is the delay risk level 4; where Sa + Ta is the first sum value; Sb + Lb is the second sum value;

[0077] Further, Sa + Ta + La > Sb + Lb and Sa + Ta < Sb + Lb. In some specific cases, the first node B may still be able to start even with a delay after the previous delay, and the risk is the delay risk level 5; where Sa + Ta + La is the first sum value; Sb + Lb is the second sum value;

[0078] Further, Sa + Ta > Sb + Lb, which is bound to fail, and the initial node A is at the delay risk level 6; where Sa + Ta + La is the first sum value; Sb + Lb is the second sum value.

[0079] S204. Determine the delay risk level of the job system according to the delay risk level of each node, and adjust the values of the start operation time and overdue threshold of the nodes whose delay risk levels exceed the preset delay risk level.

[0080] In this embodiment, adjusting the value of the starting operation time of a node whose delay risk level exceeds the preset delay risk level includes: calculating the delay margin of a node whose delay risk level exceeds the preset delay risk level, and determining the starting operation time of the node connected to the node according to the delay margin.

[0081] In this embodiment, starting from the initial node with depth - first search, when the risk of the current node is higher than level 4 of the delay risk level, the delay margin is Δ = Sa + Ta + La - (Sb + Lb). Further, that is, when calculating the relationship between the first node B and its subsequent nodes, the delay margin of the first node B is Lb = Lb + delay margin Δ.

[0082] S205: Send the data information of the node whose delay risk level exceeds the preset delay risk level to the user to prompt the user to modify the starting operation time and the overdue threshold of the node.

[0083] In this embodiment, real - time testing is performed after operations such as modifying the overdue threshold of the node and starting the starting operation time. Further, if the calculated node delay risk level or the node delay risk level increases, the user is prompted to make modifications through methods such as pages, text messages, and WeChat; because the efficiency of calculating the delay risk level based on the gallery model is very high, the obtained intermediate results are updated to the risk identification of the job chain node after the user confirms the disposal according to the evaluation results.

[0084] A method for adjusting parameters of task nodes in a job system provided by this application includes obtaining parameters of each node in the job system; where the parameters include: the value of the starting operation time, the value of the execution duration, and the value of the overdue threshold; where there are multiple nodes in the job system; where different nodes have connection relationships; the connection relationships include series and parallel. According to the parameters of the initial node and the starting operation time and overdue threshold of the nodes connected to the initial node, calculate the delay risk level of the initial node and the delay risk level of the nodes connected to the initial node. According to the delay risk level of the initial node and the delay risk level of the nodes connected to the initial node, determine the delay risk level of each node. According to the delay risk level of each node, determine the delay risk level of the job system, and adjust the value of the starting operation time and the value of the overdue threshold of the nodes whose delay risk level exceeds the preset delay risk level. By adopting this technical solution, the purpose of preventing invalid configurations can be achieved, the occurrence of system delays can be avoided, and the overtime risk of the overall job system can be reduced.

[0085] Figure 3 It is a schematic structural diagram of a device for adjusting parameters of task nodes in a job system according to Embodiment 3 of this application. The device 30 in Embodiment 3 includes the following:

[0086] An acquisition unit 301, configured to acquire parameters of each node in the job system; wherein the parameters include: the value of the starting job time, the value of the execution duration, and the value of the overdue threshold; wherein the job system includes multiple nodes; wherein there are connection relationships between different nodes; the connection relationships include series and parallel.

[0087] A determination unit 302, configured to determine the delay risk level of each node according to the parameters.

[0088] An adjustment unit 303, configured to determine the delay risk level of the job system according to the delay risk level of each node, and adjust the value of the starting job time and the value of the overdue threshold of the node whose delay risk level exceeds the preset delay risk level.

[0089] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the above-described device can refer to the corresponding process in the foregoing method embodiment, and will not be elaborated herein.

[0090] Figure 4 FIG. 13 is a schematic structural diagram of a parameter adjustment device for task nodes of a job system according to Embodiment 4 of the present application. The device 40 in Embodiment 4 includes the following:

[0091] An acquisition unit 401, configured to acquire parameters of each node in the job system; wherein the parameters include: the value of the starting job time, the value of the execution duration, and the value of the overdue threshold; wherein the job system includes multiple nodes; wherein there are connection relationships between different nodes; the connection relationships include series and parallel;

[0092] A determination unit 402, configured to determine the delay risk level of each node according to the parameters;

[0093] An adjustment unit 403, configured to determine the delay risk level of the job system according to the delay risk level of each node, and adjust the value of the starting job time and the value of the overdue threshold of the node whose delay risk level exceeds the preset delay risk level.

[0094] The determination unit 402 includes:

[0095] A calculation module 4021, configured to calculate the delay risk level of the initial node and the delay risk level of the node connected to the initial node according to the parameters of the initial node and the starting job time and overdue threshold of the node connected to the initial node;

[0096] A determination module 4022, configured to determine the delay risk level of each node according to the delay risk level of the initial node and the delay risk level of the node connected to the initial node.

[0097] In one example, the computing module 4021 includes:

[0098] A computing sub-module 40211, configured to calculate the delay risk level of the initial node and the delay risk level of the node connected to the initial node according to the relationship between the first sum value and the second sum value; wherein, the first sum value is the sum of the start job time, the execution duration, and the overdue threshold of the initial node; the second sum value is the sum of the start job time and the overdue threshold of the node connected to the initial node.

[0099] In one example, the apparatus further includes:

[0100] A sending unit 404, configured to send the data information of the node whose delay risk level exceeds the preset delay risk level to the user, so as to prompt the user to modify the start job time and the overdue threshold of the node.

[0101] In one example, the adjustment unit 403 includes:

[0102] An adjustment module 4031, configured to calculate the delay margin of the node whose delay risk level exceeds the preset delay risk level, and determine the start job time of the node connected to the node according to the delay margin.

[0103] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described apparatus can refer to the corresponding process in the foregoing method embodiment, and will not be described herein again.

[0104] Figure 5 It is a block diagram of an electronic device shown according to an exemplary embodiment. The device can be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0105] The apparatus 500 may include one or more of the following components: a processing component 502, a memory 504, a power component 506, a multimedia component 508, an audio component 510, an input / output (I / O) interface 512, a sensor component 514, and a communication component 516.

[0106] The processing component 502 generally controls the overall operation of the apparatus 500, such as operations associated with display, telephone call, data communication, camera operation, and recording operation. The processing component 502 may include one or more processors 520 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 502 may include one or more modules to facilitate the interaction between the processing component 502 and other components. For example, the processing component 502 may include a multimedia module to facilitate the interaction between the multimedia component 508 and the processing component 502.

[0107] The memory 504 is configured to store various types of data to support the operation of the device 500. Examples of such data include instructions for any application or method operating on the device 500, contact data, phone book data, messages, pictures, videos, and the like. The memory 504 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk.

[0108] The power component 506 provides power to various components of the device 500. The power component 506 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 500.

[0109] The multimedia component 508 includes a screen that provides an output interface between the device 500 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can not only sense the boundaries of the touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operations. In some embodiments, the multimedia component 508 includes a front camera and / or a rear camera. When the device 500 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have a focal length and optical zoom capabilities.

[0110] The audio component 510 is configured to output and / or input audio signals. For example, the audio component 510 includes a microphone (MIC) that is configured to receive external audio signals when the device 500 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 504 or transmitted via the communication component 516. In some embodiments, the audio component 510 further includes a speaker for outputting audio signals.

[0111] The I / O interface 512 provides an interface between the processing component 502 and a peripheral interface module, which can be a keyboard, a click wheel, buttons, etc. These buttons can include, but are not limited to: a home button, a volume button, a power-on button, and a lock button.

[0112] The sensor assembly 514 includes one or more sensors for providing an assessment of the status of the device 500 in various aspects. For example, the sensor assembly 514 can detect the on / off state of the device 500, the relative positioning of components, such as the display and keypad of the device 500. The sensor assembly 514 can also detect a change in the position of the device 500 or a component of the device 500, the presence or absence of user contact with the device 500, the orientation or acceleration / deceleration of the device 500, and the temperature change of the device 500. The sensor assembly 514 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 514 can also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 514 can further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0113] The communication component 516 is configured to facilitate communication between the device 500 and other devices in a wired or wireless manner. The device 500 can access a wireless network based on communication standards, such as WiFi, 2G, or 3G, or a combination thereof. In an exemplary embodiment, the communication component 516 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 516 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0114] In an exemplary embodiment, the device 500 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above method.

[0115] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 504 including instructions, and the above instructions can be executed by a processor 520 of the device 500 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0116] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute the method for adjusting parameters of the job system node of the above electronic device.

[0117] The present application also discloses a computer program product, including a computer program which, when executed by a processor, implements the method as described in this embodiment.

[0118] The various embodiments of the systems and technologies described above in the present application can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, where the programmable processor can be a dedicated or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0119] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a dedicated computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or electronic device.

[0120] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0121] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0122] The systems and techniques described here can be implemented in a computing system that includes back-end components (e.g., as a data electronic device), or a computing system that includes middleware components (e.g., an application electronic device), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described here), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected to each other by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0123] A computer system can include a client and an electronic device. The client and the electronic device are generally remote from each other and typically interact through a communication network. The relationship between the client and the electronic device is created by computer programs that run on respective computers and have a client-server relationship with each other. The electronic device can be a cloud electronic device, also known as a cloud computing electronic device or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services ("Virtual Private Server", or simply "VPS"). The electronic device can also be an electronic device of a distributed system, or an electronic device combined with a blockchain. It should be understood that the various forms of processes shown above can be reordered, added, or deleted steps. For example, the steps recited in this application can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved, and no limitations are imposed herein.

[0124] Other embodiments of the present application will be readily apparent to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and examples are only illustrative, and the true scope and spirit of the present application are pointed out by the following claims.

[0125] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A method for adjusting parameters of a task node in an operating system, characterized in that, The method includes: Obtaining the parameters of each node in the job system; wherein, the parameters include: the value of the starting job time, the value of the execution duration, and the value of the overdue threshold; wherein, there are multiple nodes in the job system; wherein, there is a connection relationship between different nodes; the connection relationship includes series and parallel; Calculating the delay risk level of the initial node and the delay risk level of the node connected to the initial node according to the relationship between the first sum value and the second sum value; wherein, the first sum value is the sum of the starting job time, the execution duration, and the overdue threshold of the initial node; the second sum value is the sum of the starting job time and the overdue threshold of the node connected to the initial node; Determining the delay risk level of each node according to the delay risk level of the initial node and the delay risk level of the node connected to the initial node; Determining the delay risk level of the job system according to the delay risk level of each node, and adjusting the value of the starting job time and the value of the overdue threshold of the node whose delay risk level exceeds the preset delay risk level; Adjusting the value of the starting job time of the node whose delay risk level exceeds the preset delay risk level includes: Calculating the delay margin of the node whose delay risk level exceeds the preset delay risk level, and determining the starting job time of the node connected to the node according to the delay margin.

2. The method according to claim 1, wherein The method further includes: Sending the data information of the node whose delay risk level exceeds the preset delay risk level to the user to prompt the user to modify the starting job time and the overdue threshold of the node.

3. A parameter adjustment device for a job system task node, characterized in that, The device includes: An obtaining unit, configured to obtain the parameters of each node in the job system; wherein, the parameters include: the value of the starting job time, the value of the execution duration, and the value of the overdue threshold; wherein, there are multiple nodes in the job system; wherein, there is a connection relationship between different nodes; the connection relationship includes series and parallel; A determining unit, configured to determine the delay risk level of each node according to the parameters; An adjusting unit, configured to determine the delay risk level of the job system according to the delay risk level of each node, and adjust the value of the starting job time and the value of the overdue threshold of the node whose delay risk level exceeds the preset delay risk level; The determining unit includes: A calculating module, configured to calculate the delay risk level of the initial node and the delay risk level of the node connected to the initial node according to the relationship between the first sum value and the second sum value; wherein, the first sum value is the sum of the starting job time, the execution duration, and the overdue threshold of the initial node; the second sum value is the sum of the starting job time and the overdue threshold of the node connected to the initial node; A determining module, configured to determine the delay risk level of each node according to the delay risk level of the initial node and the delay risk level of the node connected to the initial node; The adjustment unit is specifically configured to calculate the delay margin of nodes whose delay risk level exceeds a preset delay risk level, and determine the start operation time of the nodes connected to the nodes according to the delay margin.

4. An electronic device, characterized in that, It includes: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method according to claim 1 or 2.

5. A computer-readable storage medium, characterized in that, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to claim 1 or 2.

6. A computer program product, characterized in that, It includes a computer program, which when executed by a processor, implements the method according to claim 1 or 2.

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