CN114741164A - EDF-VD-based flexible hybrid critical scheduling method - Google Patents

EDF-VD-based flexible hybrid critical scheduling method Download PDF

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CN114741164A
CN114741164A CN202210058462.3A CN202210058462A CN114741164A CN 114741164 A CN114741164 A CN 114741164A CN 202210058462 A CN202210058462 A CN 202210058462A CN 114741164 A CN114741164 A CN 114741164A
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黄凯
沙天薏
蒋小文
郑丹丹
熊东亮
刘智力
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Zhejiang University ZJU
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Abstract

The invention belongs to the technical field of embedded processor systems, and discloses a flexible mixed critical scheduling method based on EDF-VD, which comprises the following steps: step 1: establishing an FMCI task model: the service level of the low-critical task is dynamically adjusted by prolonging the period of the low-critical task; step 2: the FMCI-EDF-VD scheduling method is provided: and in the system task scheduling and running process, the service level of the low-critical task is dynamically adjusted on line according to the over-support condition of the high-critical task. Compared with the existing FMC, the Flexible Mixed Critical Improvement (FMCI) model can guarantee the completion of high-critical tasks, meanwhile, more low-critical tasks are scheduled, and the method has the advantages of supporting the execution of the low-critical tasks.

Description

EDF-VD-based flexible hybrid critical scheduling method
Technical Field
The invention belongs to the technical field of embedded processor systems, and particularly relates to a flexible mixed critical scheduling method based on EDF-VD.
Background
With the increasing requirements of embedded systems on space and overhead, it has become a development trend of modern embedded systems to integrate functional subsystems with different critical levels and meeting different authentication requirements on the same shared computing platform, and such systems are called hybrid critical systems (MCS). At present, the hybrid critical system is especially common in the real-time embedded fields of electric power, automobiles, avionics, aerospace and the like. For example, a control system in a power plant, which is used to handle tasks in power edge computing and other scenarios, modularly integrates business components that require different real-time requirements and other components to reduce the ever-increasing computational operating overhead and computational complexity usage. Since different components have different requirements for system security assurance, for example, 5 different critical levels are defined in D0178B standard in the field of avionics, a task with a higher critical level represents that the system is affected more seriously if the deadline is missed, i.e., the requirement for security and reliability is higher, so that for a component with a higher requirement for security and reliability, a hybrid critical system is assigned a higher critical level, and a higher security assurance level is provided.
In order to avoid affecting the safe operation of the system during operation, it is therefore necessary to give the high-critical tasks enough computational resources to meet their time constraints. However, the problem of "priority reversal" can arise if the individual application components on the shared computing platform are managed using conventional scheduling methods. In view of the above problems, an intuitive improvement is to directly use the critical level of tasks as the priority, and the task with a high critical level is always higher in priority than the task with a low critical level. However, this approach may cause the low critical task to fail to respond late or to be abandoned when the system is busy, thereby affecting the overall quality of service and functionality of the system. How to efficiently schedule such system tasks becomes an academic research hotspot focused on by many scholars.
The Flexible Mixed Critical (FMC) model is an advanced one used for task scheduling of the existing mixed critical system, and after a high critical task is over-supported, whether a low critical task needs to balance the resources of the whole system by reducing the execution time of the low critical task is compensation demand calculation in a mode of allocating idle resources of the system in equal proportion under the condition that all the high critical tasks are over-supported is considered. This approach is very conservative. In fact, it is highly unlikely that all of the high-critical tasks will be overburdened at the same time, and when not all of the high-critical tasks will be overburdened, more free resources can be allocated by the system to any of the overburdened high-critical tasks for compensation. In addition, the FMC does not consider a mechanism for recovering and compensating the low-critical task by the free resources, that is, when the low-critical task whose execution time is reduced by the high-critical task is over-supported, if there are redundant resources in the subsequent time before the deadline, the resources are not recovered and compensated back to the low-critical task which is over-compensated for the high-critical task. Therefore, the method may have a large amount of invalid compensation of the low-critical task, and the performance of the low-critical task is greatly reduced.
Disclosure of Invention
The invention aims to provide a flexible mixed critical scheduling method based on EDF-VD (erbium doped fiber-virtual distribution) to solve the technical problem.
In order to solve the technical problems, the specific technical scheme of the flexible mixed critical scheduling method based on the EDF-VD is as follows:
an EDF-VD-based flexible hybrid critical scheduling method comprises the following steps:
step 1: establishing an FMCI task model: dynamically adjusting the service level of the low-critical task by prolonging the period of the low-critical task;
and 2, step: the FMCI-EDF-VD scheduling method is provided: and in the system task scheduling and running process, the service level of the low-critical task is dynamically adjusted on line according to the over-support condition of the high-critical task.
Further, the step 1 comprises the following specific steps:
n Γ ═ τ ═ N ═ τ ═ N1,τ2,...,τnThe situation that the independent periodic tasks are mixed with critical scheduling on a single-core processor platform is that gamma is { tau ═ tau }1,τ2,...,τnIn which any task τ isiIs characterized by being represented as
Figure BDA0003477308070000031
Wherein L isiIndicating the critical level of the task, L in the case of a dual critical systemi＝{LO,HI}，TiRepresenting the period of the task, the deadline being equal to its period;
Figure BDA0003477308070000032
representing tasks τiWorst-case execution time (WCET) in high critical mode,
Figure BDA0003477308070000033
representing tasks τiThe worst execution time (WCET) in the low critical mode is equal to the WCET in the low critical mode and the WCET in the high critical mode of the low critical task, and the high critical task respectively has two different WCETs and meets the requirements
Figure BDA0003477308070000034
Further, the step 1 includes calculating the utilization rate of the task set of the hybrid critical system, and the calculation formula is as follows:
Figure BDA0003477308070000035
Figure BDA0003477308070000036
Figure BDA0003477308070000037
Figure BDA0003477308070000038
when any high-critical task is out of support and needs the low-critical task to compensate, the new system utilization of the low-critical task is updated as follows:
Figure BDA0003477308070000039
k represents the number of tasks for the high critical task to enter the high critical mode,
Figure BDA00034773080700000310
representing a low critical task in case k high critical tasks enter a high critical mode
Figure BDA00034773080700000311
The utilization ratio of (2).
Further, the FMCI is implemented by means of extending the period or frequency of the low critical task, and is calculated as follows:
Figure BDA00034773080700000312
Figure BDA0003477308070000041
ensuring the schedulability of the tasks in the FMCI high critical mode through the formula (6), calculating how much utilization rate the low critical tasks need to consume to compensate the condition that any high critical task is over-supported when
Figure BDA0003477308070000042
That is, the high critical task overbooking condition is not compensated by reducing the utilization rate of the low critical task as a cost, and the high critical task overbooking part can be compensated by the spare resources left by the system; when the temperature is higher than the set temperature
Figure BDA0003477308070000043
In this case, the low-critical task needs to reduce the utilization rate to fill up the expense of the high-critical task over-branch portion, the total compensation needed to be provided by the low-critical task is calculated through the formula (7), and the period of the low-critical task needing to be prolonged can be calculated by combining the formulas (1) and (2).
Further, the FMCI-EDF-VD scheduling method in step 2 comprises offline calculation and online scheduling, before scheduling, a virtual deadline factor x of a high critical task in a low critical mode is calculated first to satisfy formula (10),
Figure BDA0003477308070000044
is the minimum total utilization of the low critical task;
Figure BDA0003477308070000045
Figure BDA0003477308070000046
Figure BDA0003477308070000047
and in the system task scheduling and running process, the service level of the low-critical task is dynamically adjusted on line according to the over-support condition of the high-critical task.
Further, the FMCI-EDF-VD scheduling method comprises the following specific steps:
step 2.1: in the off-line process, according to formulas (8) and (9), firstly, a virtual deadline factor x is calculated to meet the formula (10), and the scheduling capability of FMCI-EDF-VD is ensured;
step 2.2: and (3) an online scheduling process: the initial state of all tasks is a low critical mode, which can also be called a 0-level high critical mode, under the low critical mode, the high critical tasks are scheduled according to the virtual deadline, and the system selects the task with the shortest deadline from a ready task queue for scheduling; once any high-critical task exceeds the execution time of the high-critical task in the low-critical mode, the task state is immediately switched from the low-critical mode to the high-critical mode, other high-critical tasks keep the current mode unchanged, meanwhile, the excess condition is calculated through a formula (6), and the service level of the low-critical task is updated to balance the resource demand; when no task exists in the ready task queue, namely the system detects idleness, the unfinished conditions of all low critical tasks are calculated and updated, and all tasks are reset and switched back to the low critical mode;
step 2.3: PFJ is calculated after scheduling is finished, and represents the proportion of successfully completing the low-critical task before the deadline.
The invention also discloses a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
The invention also discloses a mobile terminal, comprising a mobile terminal body and a controller, wherein the controller comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and the steps of the method according to any one of claims 1-6 are realized when the processor executes the program.
The flexible mixed critical scheduling method based on the EDF-VD has the following advantages: aiming at the defect of a compensation mode in a Flexible Mixed Critical (FMC) model, the method for reducing the service level of the low critical task is improved, and the dynamic reduction of the service level of the low critical task is realized by reducing the execution time of the low critical task to prolong the period of the low critical task from the prior art. Meanwhile, a corresponding FMCI-EDF-VD scheduling method is provided. The FMCI-EDF-VD scheduling method can better manage the slack time, and the scheduling is completed before the deadline of the low critical task without losing the execution time of the low critical task. Compared with the existing FMC, the Flexible Mixed Critical Improvement (FMCI) model can ensure the completion of high critical tasks, simultaneously schedule more low critical tasks, and has greater advantages in the aspect of supporting the execution of the low critical tasks.
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FIG. 1 is a diagram illustrating FMC-EDF-VD scheduling results;
FIG. 2 is a diagram illustrating the FMCI-EDF-VD scheduling result of the present invention;
FIG. 3 is a graph showing the results of the experiment according to the present invention.
Detailed Description
In order to better understand the purpose, structure and function of the present invention, the following describes a flexible hybrid critical scheduling method based on EDF-VD in detail with reference to the accompanying drawings.
Establishing an FMCI task model: the present invention considers N Γ ═ τ1,τ2,...,τnCase where independent periodic tasks mix critical scheduling on a single-core processor platform is Γ ═ τ1,τ2,...,τnIn which any task τ isiCan be expressed as
Figure BDA0003477308070000061
Wherein L isiRepresenting the critical level of a task, the present invention considers the case of a dual critical system, namely Li＝{LO,HI}。TiIndicating the period of the task, and in the present invention, the deadline is equal to its period.
Figure BDA0003477308070000062
Representing tasks τiWorst execution time (WCET) in high critical mode.
Figure BDA0003477308070000063
Representing tasks τiWorst execution time (WCET) in low critical mode. The WCET of the low critical task in the low critical mode is equal to that of the high critical task in the high critical mode, and the high critical task respectively has two different WCETs which meet the requirements
Figure BDA0003477308070000064
The utilization rate of the task set of the mixed critical system can be calculated by the following formula
Figure BDA0003477308070000065
Figure BDA0003477308070000066
Figure BDA0003477308070000067
Figure BDA0003477308070000068
When any high-critical task is out of support and needs the low-critical task to compensate, the new system utilization of the low-critical task is updated as follows:
Figure BDA0003477308070000069
k represents the number of tasks for the high critical task to enter the high critical mode,
Figure BDA0003477308070000071
representing a low critical task in case k high critical tasks enter a high critical mode
Figure BDA0003477308070000072
The utilization ratio of (2).
Specifically, the FMCI proposed by the present invention is mainly different from the FMC model in that a method of reducing the utilization-based low critical task service level in the compensation strategy is improved. In the FMC model, the service level of the low critical task is dynamically adjusted by reducing the execution time of the FMC model, and the FMCI proposed by the present invention is implemented by extending the period (frequency) of the low critical task. The calculation method is as follows:
Figure BDA0003477308070000073
Figure BDA0003477308070000074
since the system behavior in the FMCI is the same as the FMC, we can ensure schedulability of tasks in the FMCI high critical mode by equation (6), and can calculate how much less utilization needs to be consumed by the low critical task to compensate for any high critical task overrun condition. When in use
Figure BDA0003477308070000075
Meaning that the high critical task overrun condition need not be compensated for at the expense of reducing the low critical task utilization, and the high critical task overrun portion costs to be compensated for by the remaining idle resources of the system. When in use
Figure BDA0003477308070000076
In this case, the low critical task needs to reduce the utilization rate to fill the overhead of the high critical task over-run. Therefore, the total compensation required to be provided by the low-critical task can be calculated by the formula (7), and further combining the formulas (1) and (2), the cycle of the low-critical task which needs to be prolonged can be calculated.
The FMCI-EDF-VD scheduling method comprises the following steps: the FMCI-EDF-VD scheduling method is based on the application of the traditional EDF-VD method and is suitable for the FMCI model. The whole scheduling method is divided into two parts: offline computation and online scheduling. Before scheduling, we need to calculate the virtual deadline factor x for the high critical task in the low critical mode. To ensure the feasibility of FMCI-EDF-VD, we also need to satisfy equation (10),
Figure BDA0003477308070000077
is the minimum total utilization of the low critical task.
Figure BDA0003477308070000081
Figure BDA0003477308070000082
Figure BDA0003477308070000083
In the system task scheduling operation process, the service level of the low critical task is dynamically adjusted on line according to the over-support condition of the high critical task, and the specific flow and method framework of FMCI-EDF-VD is shown in Table 2.
Table 2: the FMCI-EDF-VD scheduling method comprises the following steps:
Figure BDA0003477308070000084
lines 1-2 are offline processes, and according to formulas (8) and (9), we first calculate the virtual deadline factor x, and need to satisfy formula (10) to ensure the scheduling capability of FMCI-EDF-VD. Lines 3-12 are the process of online scheduling. The initial state of all tasks is low critical mode (also referred to as level 0 high critical mode). In the low critical mode, the high critical tasks are scheduled according to their virtual deadlines. The system selects the task from the ready task queue with the shortest deadline to schedule (row 5). Once any high-critical task exceeds its execution time in the low-critical mode, the task state is immediately switched from the low-critical mode to the high-critical mode, and the other high-critical tasks remain in the current mode, while the excess is computed by equation (6), updating the service level of the low-critical task to balance the resource demand (line 8). When there are no tasks in the ready task queue (i.e., the system detects idleness), the outstanding status of all low critical tasks is calculated and updated, and all task resets switch back to low critical mode (line 12). PFJ is computed after scheduling is complete (line 13). PFJ represents the proportion of successfully completing the low critical task before the cutoff time.
The following is an example of scheduling based on the present invention. In bookIn the scheduling example, there are a total of six tasks, where τ2～τ4The tasks are high critical tasks, and the rest are low critical tasks. DiIs the deadline of the task, Di' is DiVirtual cut-off time, D, obtained by multiplying a virtual time factor xi' is only applicable in case the high critical task is in the low critical mode. Specific task parameter values are shown in table 1. The specific process of scheduling by using the two methods before and after the improvement can be seen in fig. 1 and fig. 2.
Table 1: scheduling sample task parameter values:
Figure BDA0003477308070000091
let τ be4，1An overshoot occurs and the high critical mode is entered. FIG. 1 shows the scheduling in FMC model, at time 3, τ4，1Entering a high critical mode, calculating tau by formula (6)4，1The overbooking of the high critical mode is not enough to compensate the overbooking because the slack that can be given to it, so its overbooking part needs to be compensated by the low critical task tau5Compensating by reducing its execution time, after compensation τ5The new execution time of (2) is 7.48. However, as can be seen from FIG. 1, at τ5，1Before the deadline (i.e., time 137), there are still a number of slack time blocks that are abundant. Practically, τ is not reduced5The execution time of (2) can also complete the scheduling of the task.
Fig. 2 is a scheduling scenario with an improved method for dynamically reducing its service level for its low critical tasks. At time 3, τ4，1Entering the high critical mode, τ is also calculated by equation (6)4，1The excess condition for entering the high critical mode is distinguished by tau4，1The excess part is obtained by extending the low critical task tau5Is compensated, after compensation tau5311, its execution time is still 17. As can be seen from fig. 2, this method enables better management of the slack time without losing the low-critical task τ5The scheduling is also completed at the execution time and before its cut-off time.
Experiment: the experimental parameters of the invention are set as follows:
each task τiPeriod T ofiIs in [20,150 ]]Uniformly randomly drawn integers.
Each task τiLow critical utilization ratio of
Figure BDA0003477308070000101
Is at [0.05,015]Randomly decimated real numbers.
Ratio of high critical utilization to Low critical utilization of high critical tasks
Figure BDA0003477308070000102
Is in [2,3 ]]Uniformly randomly drawn integers.
The probability pCri that a task is a high-critical task is 0.5
Minimum total utilization of low critical tasks
Figure BDA0003477308070000103
Is 0.3
WCET from which a low-critical task can be derived
Figure BDA0003477308070000104
WCET for high critical tasks is
Figure BDA0003477308070000105
And
Figure BDA0003477308070000106
to ensure the scheduling of the mixed-critical system, we give a limit u of the utilizationBAnd generating one task at a time until the following two conditions are met, and if the two conditions are not met, regenerating the task.
(1)
Figure BDA0003477308070000107
(2) Generating at least 3 high-critical tasks
The same set of test tasks generated was used to evaluate the PFJ (i.e., the percentage of successful completion of the low critical task before the cutoff time) of the FMCI and FMC presented in this patent, respectively.
Since the experiments are based on a randomly generated set of MC tasks, more reliable results are obtained. The data is repeated with 10 averaging results, and the scheduling time of each set of test task set is 200000 time units. The experimental parameters comprise the probability p of the occurrence of the hyper-branch of the high-critical task, the p belongs to {0.1,0.3,0.5,0.7,0.9} and the utilization rate u of the task setB，uBE {0.7,0.75,0.8,0.85,0.9}, and the results of the scheduling with FMCI and FMC, respectively, for different combinations of these two parameters are shown in fig. 3. The horizontal axis represents the task set utilization and the vertical axis represents the degree of completion (PFJ value) of low-bound tasks.
The following conclusions can be observed: (1) under the same conditions, FMCI always outperforms FMC for PFJ. (2) Under the same conditions, the volatility of FMCI is small. This means that when the probability of a high critical task entering the high critical mode is high or the set of scheduled tasks is crowded, the effect on the execution of low critical tasks is less affected. (3) The performance advantage of FMCI on PFJ is more pronounced as the probability of a high critical task entering high critical mode increases.
It is to be understood that the present invention has been described with reference to certain embodiments, and that various changes in the features and embodiments, or equivalent substitutions may be made therein by those skilled in the art without departing from the spirit and scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.

Claims (8)

1. A flexible mixed critical scheduling method based on EDF-VD is characterized by comprising the following steps:
step 1: establishing an FMCI task model: the service level of the low-critical task is dynamically adjusted by prolonging the period of the low-critical task;
step 2: the FMCI-EDF-VD scheduling method is provided: and in the system task scheduling and running process, the service level of the low-critical task is dynamically adjusted on line according to the over-support condition of the high-critical task.
2. The EDF-VD based flexible hybrid critical scheduling method according to claim 1, wherein said step 1 comprises the following specific steps:
n Γ ═ τ ═ N1,τ2,...,τnThe situation that the independent periodic tasks are mixed with critical scheduling on a single-core processor platform is that gamma is { tau ═ tau }1,τ2,...,τnIn which any task τ isiIs characterized by being represented as
Figure FDA0003477308060000011
Wherein L isiIndicating the critical level of the task, L in the case of a dual critical systemi＝{LO,HI}，TiRepresenting the period of the task, the deadline being equal to its period;
Figure FDA0003477308060000012
representing tasks τiWorst execution time (WCET) in high critical mode,
Figure FDA0003477308060000013
representing tasks τiThe worst execution time (WCET) of the low critical task in the low critical mode is equal to the WCET of the high critical task in the low critical mode, and the high critical task respectively has two different WCETs and meets the requirements
Figure FDA0003477308060000014
3. The EDF-VD based flexible hybrid critical scheduling method according to claim 2, wherein the step 1 includes calculating the utilization rate of the task set of the hybrid critical system, and the calculation formula is as follows:
Figure FDA0003477308060000015
Figure FDA0003477308060000016
Figure FDA0003477308060000017
Figure FDA0003477308060000018
when any high-critical task is out of support and needs the low-critical task to compensate, the new system utilization of the low-critical task is updated as follows:
Figure FDA0003477308060000021
k represents the number of tasks for the high critical task to enter the high critical mode,
Figure FDA0003477308060000029
representing a low critical task in case k high critical tasks enter a high critical mode
Figure FDA00034773080600000210
The utilization ratio of (2).
4. The flexible hybrid critical scheduling method based on EDF-VD according to claim 3, wherein the FMCI is implemented by means of extending the period or frequency of low critical tasks, which is calculated as follows:
Figure FDA0003477308060000022
Figure FDA0003477308060000023
ensuring the schedulability of the tasks in the FMCI high critical mode through the formula (6), calculating the utilization rate of the low critical task to compensate the condition that any high critical task is over-supported, and when the utilization rate is higher than the required utilization rate, calculating the maximum utilization rate of the low critical task
Figure FDA0003477308060000024
That is, the high-critical task overbooking condition is not compensated by reducing the utilization rate of the low-critical task, and the expense of the overbooking part of the high-critical task can be compensated by the rest idle resources of the system; when in use
Figure FDA0003477308060000025
In this case, the low-critical task needs to reduce the utilization rate to fill up the expense of the high-critical task over-branch portion, the total compensation needed to be provided by the low-critical task is calculated through the formula (7), and the cycle of how long the low-critical task needs to be extended can be calculated by combining the formulas (1) and (2).
5. The flexible hybrid critical scheduling method based on EDF-VD according to claim 1, wherein the FMCI-EDF-VD scheduling method in step 2 comprises off-line calculation and on-line scheduling, before scheduling, a virtual deadline factor x of a high critical task in a low critical mode is first calculated to satisfy formula (10),
Figure FDA0003477308060000026
is the minimum total utilization of the low critical task;
Figure FDA0003477308060000027
Figure FDA0003477308060000028
Figure FDA0003477308060000031
and in the system task scheduling and running process, the service level of the low-critical task is dynamically adjusted on line according to the over-support condition of the high-critical task.
6. The flexible hybrid critical scheduling method based on EDF-VD according to claim 5, wherein the FMCI-EDF-VD scheduling method comprises the following specific steps:
step 2.1: in the off-line process, according to formulas (8) and (9), firstly, a virtual deadline factor x is calculated to meet the formula (10), and the scheduling capability of FMCI-EDF-VD is ensured;
step 2.2: and (3) an online scheduling process: the initial state of all tasks is a low critical mode, which can also be called a 0-level high critical mode, under the low critical mode, the high critical tasks are scheduled according to the virtual deadline, and the system selects the task with the shortest deadline from a ready task queue for scheduling; once any high-critical task exceeds the execution time of the high-critical task in the low-critical mode, the task state is immediately switched from the low-critical mode to the high-critical mode, other high-critical tasks keep the current mode unchanged, the excess condition is calculated through a formula (6), and the service level of the low-critical task is updated to balance the resource demand; when no task exists in the ready task queue, namely the system detects idleness, the unfinished conditions of all the low critical tasks are calculated and updated, and all the tasks are reset and switched back to the low critical mode;
step 2.3: PFJ is calculated after scheduling is finished, and represents the proportion of successfully completing the low-critical task before the deadline.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
8. A mobile terminal comprising a mobile terminal body and a controller, characterized in that the controller comprises a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the steps of the method according to any of claims 1-6.
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