CN113094260B - Distributed system time sequence relation modeling and simulation analysis method - Google Patents
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Abstract
The invention provides a distributed system time sequence relation modeling and simulation analysis method, which comprises the steps of firstly abstracting and modeling key component parts of a distributed embedded system by a bottom-up method, respectively establishing models of all the component parts, then establishing a mapping mode of system resources and processors in the distributed system, a partial sequence relation between tasks, a synchronization protocol between the processors and the like, and introducing a model of a virtual clock to realize time control in the system. The invention obtains a system model to describe the distributed embedded system, respectively establishes models of a processor, resources, tasks, a communication network, message transmission, end-to-end transactions, task partial order relation and time distance constraint of the system, obtains various time indexes, resource use conditions, task time sequence relation and other information of the distributed embedded system through system simulation analysis, provides quantitative guidance for designers, and helps the designers to reasonably plan the system resources and tasks.
Description
Technical Field
The invention relates to the technical field of distributed embedded systems, in particular to a distributed system time sequence relation modeling and simulation analysis method.
Background
The scale of the current distributed system is continuously enlarged, the system functions are more complex, more uncertainties are introduced in the conditions of concurrency, task dependence, resource competition and the like in the system, and modeling and analyzing the system time sequence are more difficult. In order to solve the problems, a time sequence modeling and simulation technology of a distributed system is researched, modeling is carried out on the related content of the time sequence of the system, wherein the time attribute of tasks in the system, the partial order relation among the tasks, the configuration of processors and resources, synchronization among the processors and the like are included, the execution process of the system is simulated, the simulation result of the time sequence of the system is obtained, and references are provided for the design and optimization of the time sequence relation of the system.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a distributed system time sequence relation modeling and simulation analysis method. Firstly, abstract and model key component parts of a distributed embedded system by a bottom-up method, respectively establish models of all the component parts, then establish models of a mapping mode of system resources and processors in the distributed system, a partial order relation between tasks, a synchronous protocol between the processors and the like, introduce a model of a virtual clock when simulating the system, and realize time control in the system and realize simulation of the system on the basis of the model.
The specific implementation steps of the technical scheme adopted for solving the technical problems are as follows:
step one, establishing a processor model;
a description of the distributed system processor model is first given:
Processor＝<p_id,type,num,preemption,speed,scheduling_strategy,switch_time>
wherein p_id is the identifier of the processor, type expresses the type of the processor, num expresses the number of the processors of the type, preemption is the preemption of the processor, indicates that the execution of a task on the processor is preempted or cannot be preempted, speed is the operation rate of the processor, the operation rate of the processor is a relative value, the operation rate of the processor affects the execution time of the task, and the operation rate of the task is x 1 If the execution time on the processor is c1, the operation rate is x 2 Execution time on processor c2=c1 (1/x); scheduling_strategy is a scheduling strategy used by a processor, and the switch_time task switching time represents the time spent by each preemption;
step two, establishing a system resource model;
establishing a model of various resources in the distributed system:
Resource＝＜preemption,num,type,requesttime,releasetime＞
wherein, preemption is preemption, which indicates whether the resource can be preempted; num is the number of resources, describing the number of such resources; type is used to distinguish the types of resources, such as shared data objects, buffers, memories, etc., which may be represented using different types; requesttime represents the time overhead of a task requesting this resource; releasetime represents the time overhead of a task releasing the resource;
step three, establishing a task model
The task model of the distributed system is divided into periodic tasks and sporadic tasks, and periodic task parameters in the system comprise: task identification, priority, task period, release time, phase, worst execution time distribution, response time, relative time limit, absolute time limit, utilization, time margin, blocking time, processor and resource requirements; sporadic task parameters include task identification, priority, release time, jitter, minimum time interval, worst execution time distribution, response time, relative time limit, absolute time limit, time margin, blocking time, processor and resource requirements;
establishing a communication network and an information transfer model;
abstracting network connection in the distributed system as a network processor, and abstracting information transmission among different network nodes of the distributed system as a message transmission task;
the model of the network processor is:
NetworkProcessor＝＜scheduling_strategy,bandwidth＞
wherein: scheduling_strategy represents a scheduling policy used in the network processor; the bandwidth represents the network bandwidth;
the model of the message transmission task is:
MessageTask＝<t_id,WCET,bandwidth,sourceProcessor,destionProcessoor>
wherein t_id represents an identification of a message transmission task, WCET represents a worst execution time of the message transmission task, bandwidth represents a bandwidth required for executing the task, sourceProcessor represents a processor which sends the message, and destimonProcessor represents a processor which accepts the message;
step five, modeling End-to-End Transaction (End-to-End Transaction)
Defining a set of tasks completing a specific function, called end-to-end transaction, for short;
Transaction＝<Sequences,release_time,deadline,response_time,utilization>
in the formula, sequences represent task Sequences in the transaction, which not only describe the contained tasks, but also restrict the front-back relation of the tasks; the release_time is the release time of a transaction, the release time of a first task is used for representing, the readline is the deadline of the transaction, the deadline of a last task is used for representing, the response time response_time of the transaction is the sum of the execution time of all tasks, and the utilization rate of the transaction is the ratio of the execution time of all tasks to the difference between the deadline of the last task and the release time of the first task;
step six, partial order relation of tasks;
for the partial order relationship between tasks, several types are included:
precursor, successor, direct precursor, direct successor, AND/OR precursor, AND/OR successor;
if the task K cannot start to be executed before the task T is executed, the task T is called as a precursor of the task K, the task K is a successor of the task T, and a "<" is used for describing a precedence constraint relation between the tasks, namely T < K;
direct precursor: if the task T can be executed after the execution of the task T is completed, the task T is called as a direct precursor of the K, and the task T is called as a direct successor of the task T;
AND/OR precursor constraint: if a task has multiple direct precursors, then it must wait before all of its direct precursors complete before it can execute, then it is called an AND task, AND the dependencies between them are called AND priority constraints. In contrast to the AND priority constraint, a task is called an OR task if it can be executed after its release time as long as one OR a portion of the immediate predecessor of the task has been completed.
AND/OR successor constraint: in the conventional model, all immediate successors to a task must be performed, AND all constraints are AND constraints. If a task is directly followed by an OR constraint, then only a portion of the task is directly followed by execution, and if only one of the directly followed tasks needs to be executed, then the task is referred to as a conditional block.
The partial order relationship between tasks is described using a task graph;
step seven, modeling time and distance constraint;
not only are there sequential constraints between tasks, in some cases requiring that the difference between the completion times of two tasks be within a certain range, a time distance is defined to describe this situation, and the model of the time distance is as follows:
TemporalDistance＝<preTask,tDistance,suTask>
wherein, prestask represents a preamble task; tDistance represents the time distance between two tasks; subtask represents a subsequent task.
Step eight, system level timing simulation
On the basis of completing the modeling of the distributed system, the execution process of the system is simulated based on the model.
The simulation step of the step eight is as follows:
1) Defining a system global clock and a local clock, wherein the time of the clock is increased along with the increase of the simulation step length;
2) Scheduling and executing tasks on the processor according to a preset scheduling algorithm;
3) Comparing the sequence relation and time attribute of task execution with the system model in each simulation step, if no violation occurs, continuing the next simulation step, and if violation occurs, stopping simulation;
4) Recording the response time and the blocking time of each task by using a local clock in the simulation process, and the response time of an end-to-end transaction; recording the release time of the task, the time interval of task execution and the completion time of the task by using a global clock, wherein the release time and the completion time of the end-to-end transaction are recorded;
5) The time-varying usage of different types of resources in the system is recorded.
The method has the beneficial effects that the distributed embedded system is described by abstracting and modeling the distributed system to obtain a system model, the models of a processor, resources, tasks, a communication network, message transmission, end-to-end transactions, a task partial order relation, time distance constraint of the system are respectively built, various time indexes, resource use conditions, task time sequence relation and other information of the distributed embedded system are obtained through system simulation analysis, whether the system execution process meets the preset requirements is verified according to the information, whether the results of system task sequence arrangement, processor, resource configuration and the like are reasonable or not is judged according to the information, whether the design requirements can be met or not, quantitative guidance is provided for a designer, and the designer is helped to reasonably plan the system resources and tasks.
Drawings
Fig. 1 is a diagram of a resource allocation of the present invention.
FIG. 2 is a system task diagram of the present invention.
FIG. 3 is a schematic diagram of the simulation analysis process of the system of the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
Referring to fig. 1-3, the method for modeling and simulating analysis of a distributed system time sequence relationship according to the present invention comprises the following steps:
step one, establishing a model of a processor
Establishing a set of processors in the distributed system, the set of processors being represented by the formula, wherein n represents the number of processors in the system:
Processors＝<Processor 1 ,Processor 2 ,...,Processor n >
the model for each processor is described as follows:
Processor＝<p_id,type,num,preemption,speed,scheduling_strategy,switch_time>
wherein: p_id is the identity of the processor, type represents the type of processor, num represents the number of processors of this type, preemption is the preemption of the processor, and indicates anyExecution on the processor is preempted or cannot be preempted, speed is the processor operation rate: the operation rate of the processor is a relative value, the operation rate of the processor can influence the execution time of the task, and the operation rate of the task is x 1 If the execution time on the processor is c1, the operation rate is x 2 Execution time on processor c2=c1 (1/x); scheduling_strategy is the scheduling policy used by the processor, the switch_time task switch time, and characterizes the time spent for each preemption.
Step two, establishing a system resource model
Establishing a model of various resources in the distributed system:
Resource＝＜preemption,num,type,requesttime,releasetime＞
wherein, preemption is preemption, which indicates whether the resource can be preempted; num is the number of resources, describing the number of such resources; type is used to distinguish the types of resources, such as shared data objects, buffers, memories, etc., which may be represented using different types; requesttime represents the time overhead of a task requesting this resource; releasetime represents the time overhead of a task releasing the resource.
Step three, task model
Tasks in a distributed system include periodic tasks and sporadic tasks:
1) Periodic tasks
2) Sporadic tasks:
step four, establishing a communication network and an information transfer model
Abstracting network connection in the distributed system as a network processor, abstracting information transmission among different network nodes of the distributed system as a message transmission task, and a scheduling algorithm used by the message transmission task is similar to a priority driving algorithm scheduled by using the processor. In all cases, the inter-processor communication overhead can be accounted for by including the network processor and message transmission tasks in the model, without having to take these factors into account in a special way alone, simplifying the analysis process.
The model of the network processor is:
NetworkProcessor＝＜scheduling_strategy,bandwidth＞
wherein: scheduling_strategy represents a scheduling policy used in the network processor; bandwidth represents network bandwidth.
The model of the message transmission task is:
MessageTask＝<t_id,WCET,bandwidth,sourceProcessor,destionProcessoor>
where t_id represents the identity of the message transfer task, WCET represents the worst execution time of the message transfer task, bandwidth represents the bandwidth required to execute the task, sourcepocessor represents the processor that sent the message, and destimonprocessor represents the processor that accepted the message.
Step five, modeling End-to-End Transaction (End-to-End Transaction)
A collection of tasks that perform a particular function is defined, called an end-to-end transaction, or simply a transaction.
Transaction＝<Sequences,release_time,deadline,response_time,utilization>
In the formula, sequences represent task Sequences in the transaction, which not only describe the contained tasks, but also restrict the front-back relation of the tasks; the release_time is the release time of the transaction, the release time of the first task is used for representing, the readline is the deadline of the transaction, the deadline of the last task is used for representing, the response time response_time of the transaction is the sum of the execution time of all tasks, and the utilization rate of the utilization is the ratio of the execution time of all tasks to the difference between the deadline of the last task and the release time of the first task.
Step six, partial order relation of tasks
For the partial order relationship between tasks, several types are included:
precursor, successor, direct precursor, direct successor, AND/OR precursor, AND/OR successor.
If the task K cannot start executing before the task T is executed, the task T is called a precursor of the task K, and the task K is a follow-up of the task T. "<" is used to describe the precedence constraint relationship between tasks, i.e., T < K.
Direct precursor: if K is executable after task T is executed, then T is called a direct precursor of K, and K is called a direct successor of T.
AND/OR precursor constraint: if a task has multiple direct precursors, then it must wait before all of its direct precursors complete before it can execute, then it is called an AND task, AND the dependencies between them are called AND priority constraints. In contrast to the AND priority constraint, a task is called an OR task if it can be executed after its release time as long as one OR a portion of the immediate predecessor of the task has been completed.
AND/OR successor constraint: in the conventional model, all immediate successors to a task must be performed, AND all constraints are AND constraints. If a task is directly followed by an OR constraint, then only a portion of the task is directly followed by execution, and if only one of the directly followed tasks needs to be executed, then the task is referred to as a conditional block. The partial order relationship between tasks is described using a task graph.
Step seven, time distance constraint modeling
Not only are there sequential constraints between tasks, in some cases requiring that the difference between the completion times of two tasks be within a certain range, a time distance is defined to describe this situation, and the model of the time distance is as follows:
TemporalDistance＝<preTask,tDistance,suTask>
wherein, prestask represents a preamble task; tDistance represents the time distance between two tasks; subtask represents a subsequent task.
Step eight, system level timing simulation
On the basis of completing the modeling of the distributed system, the execution process of the system is simulated based on the model, and the steps are as follows:
1) Defining a system global clock and a local clock, wherein the time of the clock is increased along with the increase of the simulation step length;
2) Scheduling and executing tasks on the processor according to a preset scheduling algorithm;
3) Comparing the sequence relation and time attribute of task execution with the system model in each simulation step, if no violation occurs, continuing the next simulation step, and if violation occurs, stopping simulation;
4) Recording the response time and the blocking time of each task by using a local clock in the simulation process, and the response time of an end-to-end transaction; recording the release time of the task, the time interval of task execution and the completion time of the task by using a global clock, wherein the release time and the completion time of the end-to-end transaction are recorded;
5) The time-varying usage of different types of resources in the system is recorded.
Claims (2)
1. A distributed system time sequence relation modeling and simulation analysis method is characterized by comprising the following steps:
step one, establishing a processor model;
a description of the distributed system processor model is first given:
Processor＝<p_id,type,num,preemption,speed,scheduling_strategy,switch_time>
wherein p_id is the identifier of the processor, type expresses the type of the processor, num expresses the number of the processors of the type, preemption is the preemption of the processor, indicates that the execution of a task on the processor is preempted or cannot be preempted, speed is the operation rate of the processor, the operation rate of the processor is a relative value, the operation rate of the processor affects the execution time of the task, and the operation rate of the task is x 1 If the execution time on the processor is c1, the operation rate is x 2 Execution time on processor c2=c1 (1/x); the scheduling_strategy isThe scheduling strategy used by the processor, the switch_time task switching time, the time spent for each preemption is represented;
step two, establishing a system resource model;
establishing a model of various resources in the distributed system:
Resource＝＜preemption,num,type,requesttime,releasetime＞
wherein, preemption is preemption, which indicates whether the resource can be preempted; num is the number of resources, describing the number of such resources; type is used for distinguishing the types of resources, and the shared data object, the buffer area and the memory can be represented by different types; requesttime represents the time overhead of a task requesting this resource; releasetime represents the time overhead of a task releasing the resource;
step three, establishing a task model
The task model of the distributed system is divided into periodic tasks and sporadic tasks, and periodic task parameters in the system comprise: task identification, priority, task period, release time, phase, worst execution time distribution, response time, relative time limit, absolute time limit, utilization, time margin, blocking time, processor and resource requirements; sporadic task parameters include task identification, priority, release time, jitter, minimum time interval, worst execution time distribution, response time, relative time limit, absolute time limit, time margin, blocking time, processor and resource requirements;
establishing a communication network and an information transfer model;
abstracting network connection in the distributed system as a network processor, and abstracting information transmission among different network nodes of the distributed system as a message transmission task;
the model of the network processor is:
NetworkProcessor＝＜scheduling_strategy,bandwidth＞
wherein: scheduling_strategy represents a scheduling policy used in the network processor; the bandwidth represents the network bandwidth;
the model of the message transmission task is:
MessageTask＝<t_id,WCET,bandwidth,sourceProcessor,destionProcessoor>
wherein t_id represents an identification of a message transmission task, WCET represents a worst execution time of the message transmission task, bandwidth represents a bandwidth required for executing the task, sourceProcessor represents a processor which sends the message, and destimonProcessor represents a processor which accepts the message;
step five, modeling End-to-End Transaction (End-to-End Transaction)
Defining a set of tasks completing a specific function, called end-to-end transaction, for short;
Transaction＝<Sequences,release_time,deadline,response_time,utilization>
in the formula, sequences represent task Sequences in the transaction, which not only describe the contained tasks, but also restrict the front-back relation of the tasks; the release_time is the release time of a transaction, the release time of a first task is used for representing, the readline is the deadline of the transaction, the deadline of a last task is used for representing, the response time response_time of the transaction is the sum of the execution time of all tasks, and the utilization rate of the transaction is the ratio of the execution time of all tasks to the difference between the deadline of the last task and the release time of the first task;
step six, partial order relation of tasks;
for the partial order relationship between tasks, several types are included:
precursor, successor, direct precursor, direct successor, AND/OR precursor, AND/OR successor;
if the task K cannot start to be executed before the task T is executed, the task T is called as a precursor of the task K, the task K is a successor of the task T, and a "<" is used for describing a precedence constraint relation between the tasks, namely T < K;
direct precursor: if the task T can be executed after the execution of the task T is completed, the task T is called as a direct precursor of the K, and the task T is called as a direct successor of the task T;
AND/OR precursor constraint: if a task has multiple direct precursors, then it must wait before all of its direct precursors are completed before it can execute, then it is called an AND task, where the dependency between AND tasks is called an AND priority constraint; contrary to the AND priority constraint, a task is called an OR task if it can be executed after its release time as long as one OR a portion of the immediate predecessor of the task has been completed;
AND/OR successor constraint: in the traditional model, all immediate successor of a task must be performed, AND all constraints are AND constraints; if the direct successor of a task is an OR constraint, only part of the task is directly successor-executed, and if only one of the direct successor needs to be executed, the task is called a conditional block;
the partial order relationship between tasks is described using a task graph;
step seven, modeling time and distance constraint;
not only are there sequential constraints between tasks, in some cases requiring that the difference between the completion times of two tasks be within a certain range, a time distance is defined to describe this situation, and the model of the time distance is as follows:
TemporalDistance＝<preTask,tDistance,suTask>
wherein, prestask represents a preamble task; tDistance represents the time distance between two tasks; subtask represents a subsequent task;
step eight, system level timing simulation
On the basis of completing the modeling of the distributed system, the execution process of the system is simulated based on the model.
2. The distributed system timing relationship modeling and simulation analysis method according to claim 1, wherein: the simulation step of the step eight is as follows:
1) Defining a system global clock and a local clock, wherein the time of the clock is increased along with the increase of the simulation step length;
2) Scheduling and executing tasks on the processor according to a preset scheduling algorithm;
3) Comparing the sequence relation and time attribute of task execution with the system model in each simulation step, if no violation occurs, continuing the next simulation step, and if violation occurs, stopping simulation;
4) Recording the response time and the blocking time of each task by using a local clock in the simulation process, and the response time of an end-to-end transaction; recording the release time of the task, the time interval of task execution and the completion time of the task by using a global clock, wherein the release time and the completion time of the end-to-end transaction are recorded;
5) The time-varying usage of different types of resources in the system is recorded.
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| 基于时间事件模型的实时系统仿真与时序分析;陈艳;徐晓峰;李晓潮;郭东辉;系统仿真学报;20111231(009);全文 * |
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