CN114690719B - Platform-oriented efficient information physical production system - Google Patents
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Abstract
The invention relates to the technology of an information physical production system, in particular to a platform-oriented efficient information physical production system, which comprises a platform layer based on middleware and PoComp components. The platform layer is used for acquiring production information, realizing connectivity problems of execution tasks among the components, analyzing and calculating a schedule, resource requirements and adaptation parameters, and sending the acquired data and instructions to the PoComp component through an API; the PoComp component is used for executing the instruction and the configuration parameter received from the platform layer, carrying out resource adjustment, solving the problem of the difference of the execution time of equipment and realizing the operation required by the production process; the invention maximally ensures the time constraint of each task and realizes the new industrial production requirements of high-efficiency scheduling, high-reliability migration and the like of the components under tight arrangement.
Description
Technical Field
The invention relates to the technology of an information physical production system, in particular to a platform-oriented efficient information physical production system.
Background
Currently, CPPS (Cyber-Physical Production System) has developed an automated production architecture from a traditional hierarchical architecture to a distributed flattened architecture into a representative production model of industry 4.0 by virtue of its features of distributed operation, location independence, service description, connectivity, etc.
However, the existing CPPS design method follows a separate design paradigm, is manually integrated after independent control, scheduling and network design, and each part of optimization process only considers corresponding interest targets, and adopts modes of overall assumption, given value, resource reservation and the like to replace interaction relations in all aspects, so that the CPPS system cannot realize overall integrated management and control, and the purposes of overall optimization and efficient production are difficult to realize. The automatic hierarchical control decision method is not changed along with the network connection flattening, the production structure advantage of the distributed flattening cannot be realized, and the flexibility of the production process and the compactness of arrangement are difficult to improve. The traditional CPPS only considers flattening of transmission, the decision process also needs a top-level control unit decision, the intelligent degree of the edge side is low, and the system flexibility degree is poor; in addition, the processing process in CPPS adopts a scheduling mode, so that the processing time and algorithm execution overhead of each procedure are conservative in estimation, the cooperative capacity of multiple devices is weaker, and the improvement of productivity is limited.
Disclosure of Invention
According to the problems, the invention aims to provide a platform-oriented high-efficiency information physical production system, which realizes a self-adaptive time scale measurement mechanism under various protocols and various connection modes, improves the real-time performance of the system, ensures the time precision of tight arrangement, breaks through data, connection, analysis and decision barriers brought by a layered structure, and can flexibly adjust end side resources to provide a basis for end side real-time perception analysis decision control integration, thereby improving the utilization rate of system resources and flexible fault tolerance.
The technical scheme adopted by the invention for achieving the purpose is as follows:
A platform-oriented efficient information physical production system, comprising: a middleware-based platform layer and a plurality PoComp of components, wherein:
the middleware-based platform layer is used for acquiring production information, realizing connectivity problems of execution tasks between PoComp components, analyzing the production information to generate control instructions and configuration information, and sending the control instructions and the configuration information to the PoComp components;
The PoComp component is used for executing the control instruction and the configuration information received from the platform layer and carrying out resource adjustment so as to solve the problem of the execution time difference of the equipment.
The middleware-based platform layer comprises: OS-oriented middleware, a set of functional blocks, and a middleware API, wherein:
the middleware facing the OS is used for receiving production information;
the function block set is used for creating a new component, realizing the connectivity problem of execution tasks among PoComp components according to production information, analyzing the production information and generating a control instruction;
The middleware API is used for providing standard interfaces and protocols, providing communication services for heterogeneous environments, and sending control instructions and configuration information generated by the function block set to the PoComp component.
The set of functional blocks includes: the system comprises a protocol set module, a scheduler module, a time unification module and a service module, wherein:
The protocol set module comprises a plurality of protocol sets for protocol conversion of external equipment and a physical production system, and a corresponding relation for representing time slots, equipment network addresses and execution operations, and is used for realizing interconnection and semantic interpretation between PoComp components;
the scheduler module is used for acquiring the estimated execution time of the distributed time module, comparing the latest deadline with the estimated execution time, acquiring the sequential constraint relation between PoComp assembly production logic and PoComp assembly production logic according to the production requirement of the service module, acquiring the adjusted resource proportion information, and forming configuration information together with the estimated execution time and sending the configuration information to the resource adjustment module;
the time unifying module is used for synchronizing the time between PoComp components;
the service module is used for receiving the production information, converting the time stamp of the production information when the production information is transmitted between PoComp components, forming the production requirement and sending the production requirement to the scheduler module.
The PoComp assembly includes: control rule module, state module, resource adjustment module, distributed time module and semantic matching module, wherein:
the state module is used for providing environment variables required by PoComp component restarting and upgrading, acquiring PoComp component production logic from the scheduler module and acquiring production requirements from the semantic matching module, and obtaining a precedence constraint relation between PoComp component production logic;
The semantic matching module is used for acquiring the production requirement of the control instruction containing the current task from the scheduler module, carrying out semantic interaction on PoComp assembly operation, obtaining behavior parameters and sending the behavior parameters to the state module to realize the matching between the production language and the machine language;
the control rule module is used for realizing the operation required by the production process, comprises a deployment method, a control algorithm and a corresponding parameter configuration method required by component function realization, and is used for taking the task execution sequence constraint relation obtained by the state module and the behavior parameter of the semantic matching module as time constraint analysis conditions of the control rule and providing the latest deadline of the execution time for each task;
The distributed time module is used for dynamically adjusting the resource quantization relation function and estimating the execution time so as to realize consistency and instantaneity of the component time in the migration process;
the resource adjusting module is used for receiving the resource demand information obtained by the estimated execution time of the distributed time module, dynamically adjusting the resource proportion allocated to the task according to the resource proportion information adjusted by the scheduler module when the estimated execution time cannot meet the latest deadline, or elastically allocating the resource when the application resource amount is higher than the resource amount required by completing the current task, namely reserving the redundant resource for other component tasks so as to ensure the resource utilization rate of the system.
The distributed time module includes: the system comprises a function completion time estimation module and a distributed time scale dynamic adjustment module, wherein:
The function completion time estimation module is used for acquiring resources required by each production link according to the latest deadline of the control rule module, carrying out system maximization resource demand estimation, analyzing the obtained resource quantification relation functions DBF and SBF, obtaining the maximum delay corresponding to a certain resource and the maximum backlog under the current resource condition in a certain time period according to the curve relation of the DBF, SBF and the resources, obtaining the estimated execution time according to the function relation of the DBF and the SBF, and sending the estimated execution time and the resource proportion information to the scheduler module;
And the distributed time scale dynamic adjustment module is used for carrying out fine granularity on the component tasks with time constraint precision larger than the threshold according to the obtained sequential constraint relation and the latest deadline between PoComp component production logics, and sending the results to the scheduler module so as to realize real-time coordination of a plurality of different time scale components.
The DBF represents a component task load maximum arrival curve, which is:
Wherein I is the length of time from 0; t is defined as the task overcycle, which is the least common multiple of all machining cycles, i.e P (l) is a time-dependent system task parallelism function; phi is a processing task which can be executed in parallel, theta is a processing task which cannot be executed in parallel, and (phi+theta) is all processing links of the product i; delta is the resource waste caused by the waiting delay generated by the processing of the waiting node in the current procedure; z is the sum of overhead and tail task resource requirements for non-full cycle operation.
The SBF represents a minimum service curve of computing resources, which is:
Wherein, C n is the computing power of PoComp components N at time l, N is the number of all PoComp components, T' is the arrival cycle of the physical production system resources, and Q is the computing resource provided by the non-positive cycle physical production system.
A platform-oriented efficient physical information production method comprises the following steps:
The connectivity between the network protocol and the components of each module in the platform layer is unified through a protocol set, and interaction semantics in the interface description are specified through a semantic matching module;
The production information is transmitted to a service module for analysis through the middleware facing the OS, and the production information representing the task is transmitted to a PoComp component;
The PoComp component optimizes two resource quantization relation functions representing the shortest processing time and the minimum processing energy consumption through a distributed time module, adjusts the production speed according to time constraint, and generates estimated execution time of corresponding processing steps of each station;
According to the task execution sequence constraint relation obtained by the state module and the behavior parameters obtained by the semantic matching module through conversion, performing time constraint analysis on the control rule module and providing the latest deadline of the execution time for the task;
And according to whether the latest deadline given to the scheduler module by the control rule module is met, performing online scheduling optimization by the scheduler module: changing the ratio of the resource adjusting module to the resource request and the allocation, dynamically adjusting the ratio of the resources allocated to the task through the scheduler module when the estimated execution time cannot meet the latest deadline, or elastically allocating the resources through the module when the application resource amount is higher than the resource amount required by completing the current task, and reserving redundant resources for other component tasks;
The PoComp component acquires a control instruction and configuration information generated by online dispatching optimization of the platform layer dispatcher module through the middleware API, analyzes operation required by the production process through the control rule module to carry out production logic control output action, and feeds back a result to the platform layer to wait for the next instruction after the operation is finished.
The invention has the following beneficial effects and advantages:
1. According to the invention, time constraint conditions are introduced, a self-adaptive time scale measurement mechanism under multiple protocols and multiple connection modes is realized, the real-time performance of the system is improved, the time constraint of each task is ensured to the maximum extent, and the new industrial production requirements of high-efficiency scheduling, high-reliability migration and the like of the components under tight arrangement are realized.
2. The invention breaks through the barriers of data, connection, analysis and decision making brought by the hierarchical structure of the traditional CPPS, so that the terminal side resource can be flexibly regulated to provide a basis for the integration of terminal side real-time perception analysis decision control, the utilization rate of system resources and flexible fault tolerance are improved, the invention is suitable for production links with large flexible scale and high real-time requirement, and has stronger practicability and economic value.
Drawings
FIG. 1 is a schematic diagram of a platform-oriented high-efficiency information physical production system;
FIG. 2 is a graph of minimum service curve versus maximum arrival for a distributed time module based on a function;
fig. 3 is a flow chart of scheduler operation.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The invention designs a platform-oriented efficient information physical production system, orders are transmitted to a middleware interface of a PoECPPS system through a network, then a production flow is decomposed into a linked list taking components as processing units, and parameters, hardware equipment and models which are adapted by different components are obtained by analysis and calculation by a scheduler, a time unification module and the like; finally, the middleware API sends the calculated parameters to the corresponding controllers and activates the components thereon for processing. It should be noted that, the components in the component chain table only represent functions and are not necessarily bound to the physical location of the hardware, so there is no hierarchical relationship between the components in the PoECPPS system. Wherein PoECPPS system includes PoComp component, middleware-based platform layer.
The middleware-based platform layer includes: middleware, function block set and middleware API facing OS; the middleware facing the OS is used for receiving production information transmitted to the platform by the operating system through a network; a set of functional blocks including a kernel and a shell; and the middleware API is used for providing a standard interface and a protocol, providing communication service for the heterogeneous environment and sending the control instruction and the configuration information to the PoComp component.
The kernel is used for creating new components, realizing connectivity problems of executing tasks among the components, analyzing a calculation schedule, resource requirements and adaptation parameters; the housing is used for compressing all the components, providing a container structure for the components, and a unified interface for interacting with the rest of the PoECPPS system;
The kernel comprises: the system comprises a protocol set module, a scheduler module, a time unification module and a service module;
The protocol set module comprises a plurality of protocol sets for protocol conversion of external equipment and a physical production system, and a corresponding relation for representing time slots, equipment network addresses and execution operations, and is used for realizing interconnection and semantic interpretation between PoComp components;
The scheduler module is used for scheduling all messages and threads in the form of task unloading and migration by comparing the estimated execution time acquired from the distributed time module with the latest deadline acquired from the control rule module and acquiring the adjusted resource proportion information according to the sequence constraint relation between PoComp assembly production logic and PoComp assembly production logic acquired by the production requirement of the service module, wherein the scheduling result can influence the dynamic change of the resource adjustment module;
the time unifying module is used for synchronizing the time among the components, dynamically performing feedforward adjustment on the estimated execution time, and providing high-precision time guarantee for the cooperation of the components;
the service module is used for receiving the production information obtained from the middleware facing the OS and converting the time stamp of the message when the message is transmitted between PoComp components to form the production information and transmitting the production information to the scheduler module.
The PoComp assembly includes: the system comprises a control rule module, a state module, a resource adjusting module, a distributed time module and a semantic matching module;
The control rule module is used for realizing the operation required by the production process, comprises a deployment method, a control algorithm and a corresponding parameter configuration method required by component function realization, and is used for taking the task execution sequence constraint relation obtained by the state module and the behavior parameter obtained by the semantic matching module through conversion as time constraint analysis conditions of the control rule and providing the latest deadline of the execution time for each task;
The state module is used for providing environment variables required by PoComp component restarting and upgrading, acquiring PoComp component production logic from the scheduler and acquiring production requirements from the semantic matching module, and obtaining a sequence constraint relation between PoComp component production logic, such as the operation that a mechanical arm clamps before machining in the part production process, wherein the component state can be checked and recovered during reinitialization;
The resource adjusting module is used for receiving the resource demand information obtained by the distributed time module and the task execution time analyzed by the scheduler, applying for calculation and network resource to the hardware equipment, dynamically adjusting the resource proportion allocated to the task according to the resource proportion information adjusted by the scheduler module when the estimated execution time cannot meet the latest deadline, or elastically allocating the resource through the module when the applied resource amount is higher than the resource amount required by completing the current task, reserving redundant resources to other component tasks, and guaranteeing the resource utilization rate of the system;
The distributed time module is used for dynamically adjusting the resource quantization relation function and estimating the execution time so as to realize consistency and instantaneity of the component time in the migration process;
The semantic matching module is used for acquiring production requirements of control instructions containing a current task from the scheduler module, carrying out semantic interaction on PoComp component operations, acquiring control parameters of the current task such as the clamping position and height of a mechanical arm, constructing a multi-component collaborative unified semantic model which covers perception, analysis, decision and control, and in the unified model, each sub-model can be regarded as a system transmission process, namely M= (S, S 0, R, I, O and N), wherein S and S 0 represent system states and initial states, R represents conversion rules, I and O represent input and output, N= (t, c, phy 0,phy1) represents system semantic feature vectors, t represents time, c represents physical coordinates, and phy x represents the rest physical quantities.
The distributed time module comprises the following two-part modules:
(1) The function completion time estimation module is used for acquiring resources required by each production link according to the latest deadline of the control rule module, carrying out system maximization resource demand estimation, analyzing the obtained resource quantification relation functions DBF and SBF, obtaining the maximum delay corresponding to a certain resource and the maximum backlog under the current resource condition in a certain time period according to the curve relation of the DBF, SBF and the resources, obtaining the estimated execution time according to the maximum delay and the maximum backlog, and sending the estimated execution time and the resource proportion information to the scheduler module, wherein the estimated execution time and the resource proportion information are adjusted by the scheduler module, wherein the maximum delay and the maximum backlog are the same as the maximum delay of the current resource in the certain time period
Wherein I is the length of time from 0; t is defined as the task overcycle, which is the least common multiple of all machining cycles, i.eP (l) is a time-dependent system task parallelism function; phi is a processing task which can be executed in parallel, theta is a processing task which cannot be executed in parallel, and (phi+theta) is all processing links of the product i; delta is the resource waste caused by the waiting delay generated by the processing of the waiting node in the current procedure; z is the sum of the additional overhead caused by task unloading, node cooperative interaction and other factors and the tail task resource requirement of the non-full period operation; wherein,
Wherein C n is the computing power of node N at time l, N is the number of all edge nodes, T' is the system resource arrival period, and Q is the computing resource provided by the non-positive period system.
(2) And the distributed time scale dynamic adjustment module is used for carrying out fine granularity on the component tasks with time constraint precision larger than the threshold according to the obtained sequential constraint relation and the latest deadline between PoComp component production logics, and sending the results to the scheduler module so as to realize real-time coordination of a plurality of different time scale components.
As shown in fig. 2, the distributed time module establishes a system resource arrival curve and a service curve based on the DBF and the SBF, both of which are affected by the actual production environment and have maximum and minimum curves, respectively. Wherein the minimum service curve of the computing resource is xi l, and the maximum arrival curve of the component task load is lambda u. By analyzing the relation between the two, the maximum time of calculating the time estimated value of the component under different hardware equipment resource service curves can be obtained through analysis, namely, the stable working state can be achieved by how long the component is migrated to the hardware equipment. And backlog and maximum delay of the process production task before steady state is reached.
According to the invention, time constraint conditions are introduced, a self-adaptive time scale measurement mechanism under multiple protocols and multiple connection modes is realized, the real-time performance of the system is improved, the time constraint of each task is ensured to the maximum extent, and the new industrial production requirements of high-efficiency scheduling, high-reliability migration and the like of the components under tight arrangement are realized; the invention breaks through the barriers of data, connection, analysis and decision making brought by the hierarchical structure of the traditional CPPS, so that the terminal side resource can be flexibly regulated to provide a basis for the integration of terminal side real-time perception analysis decision control, the utilization rate of system resources and flexible fault tolerance are improved, the invention is suitable for production links with large flexible scale and high real-time requirement, and has stronger practicability and economic value.
As shown in fig. 1, the system production flow specifically comprises the following steps:
(1) Firstly, the connectivity between the network protocols and the components of each part is unified through a protocol set, and interaction semantics in interface description are designated through a semantic matching module;
(2) The production information is transmitted to a service module for analysis through an OS-oriented middleware, the production quantity and the product type are analyzed, and task information is transmitted to a PoComp component;
(3) PoComp component optimizes two targets of the shortest processing time and the minimum processing energy consumption through a distributed time module, adjusts the production speed according to time constraint, and generates estimated execution time of processing steps corresponding to each station
(4) According to the task execution sequence constraint relation obtained by the state module and the behavior parameters obtained by the semantic matching module through conversion, performing time constraint analysis on the control rule module and providing the latest deadline of the execution time for the task;
(5) According to whether the latest deadline is met or not, the result information is fed back to the platform layer, online scheduling optimization is carried out through a scheduler according to the production time range of each part, the proportion of resource request and allocation by a resource adjusting module is changed, when the estimated execution time cannot meet the latest deadline, the proportion of resources allocated to tasks is dynamically adjusted through the scheduler, or when the application resource amount is higher than the resource amount required by completing the current task, the resources are elastically allocated through the module, and redundant resources are reserved for other component tasks;
(6) Meanwhile, the platform layer carries out dynamic feedforward adjustment on the estimated execution time according to the time unification module, so that the limitation of communication resources is prevented, the interaction frequency between components is reduced, and the high-precision coordination between the components is ensured;
(7) And finally, carrying out production scheduling on the generated scheduling and processing scheme by a scheduler, acquiring instructions and data generated by the platform layer by the PoComp component through a middleware API, analyzing the operation required by the product by a control rule module to carry out production logic control output action, feeding back the result to the platform layer to wait for the next instruction after the operation is finished, and controlling and outputting the platform layer and inputting corresponding strategy instructions through a function block set if an emergency component exists.
As shown in fig. 3, the specific execution logic of the scheduler is as follows:
(1) Firstly, the platform layer analyzes production information and transmits the production information to PoComp components through a middleware API;
(2) Comparing the estimated execution time of the task with the time constraint deadline given by the control rule module according to the distributed time module, unloading the task and judging whether the current task can finish operation before the deadline;
(3) If the operation can not be completed in the current state, the system returns the data to the dispatcher of the platform layer;
(4) Then the scheduler judges whether the operation can be executed in the current executor of the component, and the methods such as increasing the demand of the current task for the resource to the resource adjusting module in a dynamic mode to reduce the execution time of the operation and the like are optimized;
(5) When the judging result is still no, the system inquires the working state of the executor and transfers the current task to the executor capable of meeting the deadline;
(6) If all the executors cannot meet the deadline requirement, the system still gives a relatively optimal solution, for example, the resource allocation proportion of the system is reduced on the premise of not influencing the time constraint of other components, and a feasible scheme is provided for the current task.
The foregoing is merely an embodiment of the present invention and is not intended to limit the scope of the present invention. Modifications, equivalents, improvements, extensions, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (6)
1. A platform-oriented efficient information physical production system, comprising: a middleware-based platform layer and a plurality PoComp of components, wherein:
the middleware-based platform layer is used for acquiring production information, realizing connectivity problems of execution tasks between PoComp components, analyzing the production information to generate control instructions and configuration information, and sending the control instructions and the configuration information to the PoComp components;
The PoComp component is used for executing the control instruction and the configuration information received from the platform layer and carrying out resource adjustment so as to solve the problem of the execution time difference of the equipment;
the middleware-based platform layer comprises: OS-oriented middleware, a set of functional blocks, and a middleware API, wherein:
the middleware facing the OS is used for receiving production information;
the function block set is used for creating a new component, realizing the connectivity problem of execution tasks among PoComp components according to production information, analyzing the production information and generating a control instruction;
The middleware API is used for providing a standard interface and a protocol, providing communication service for heterogeneous environments and sending control instructions and configuration information generated by the function block set to the PoComp component;
The PoComp assembly includes: control rule module, state module, resource adjustment module, distributed time module and semantic matching module, wherein:
the state module is used for providing environment variables required by PoComp component restarting and upgrading, acquiring PoComp component production logic from the scheduler module and acquiring production requirements from the semantic matching module, and obtaining a precedence constraint relation between PoComp component production logic;
The semantic matching module is used for acquiring the production requirement of the control instruction containing the current task from the scheduler module, carrying out semantic interaction on PoComp assembly operation, obtaining behavior parameters and sending the behavior parameters to the state module to realize the matching between the production language and the machine language;
the control rule module is used for realizing the operation required by the production process, comprises a deployment method, a control algorithm and a corresponding parameter configuration method required by component function realization, and is used for taking the task execution sequence constraint relation obtained by the state module and the behavior parameter of the semantic matching module as time constraint analysis conditions of the control rule and providing the latest deadline of the execution time for each task;
The distributed time module is used for dynamically adjusting the resource quantization relation function and estimating the execution time so as to realize consistency and instantaneity of the component time in the migration process;
the resource adjusting module is used for receiving the resource demand information obtained by the estimated execution time of the distributed time module, dynamically adjusting the resource proportion allocated to the task according to the resource proportion information adjusted by the scheduler module when the estimated execution time cannot meet the latest deadline, or elastically allocating the resource when the application resource amount is higher than the resource amount required by completing the current task, namely reserving the redundant resource for other component tasks so as to ensure the resource utilization rate of the system.
2. The platform-oriented efficient physical production system of information of claim 1, wherein the set of functional blocks comprises: the system comprises a protocol set module, a scheduler module, a time unification module and a service module, wherein:
The protocol set module comprises a plurality of protocol sets for protocol conversion of external equipment and a physical production system, and a corresponding relation for representing time slots, equipment network addresses and execution operations, and is used for realizing interconnection and semantic interpretation between PoComp components;
the scheduler module is used for acquiring the estimated execution time of the distributed time module, comparing the latest deadline with the estimated execution time, acquiring the sequential constraint relation between PoComp assembly production logic and PoComp assembly production logic according to the production requirement of the service module, acquiring the adjusted resource proportion information, and forming configuration information together with the estimated execution time and sending the configuration information to the resource adjustment module;
the time unifying module is used for synchronizing the time between PoComp components;
the service module is used for receiving the production information, converting the time stamp of the production information when the production information is transmitted between PoComp components, forming the production requirement and sending the production requirement to the scheduler module.
3. The platform-oriented efficient physical production system of information of claim 1, wherein the distributed time module comprises: the system comprises a function completion time estimation module and a distributed time scale dynamic adjustment module, wherein:
The function completion time estimation module is used for acquiring resources required by each production link according to the latest deadline of the control rule module, carrying out system maximization resource demand estimation, analyzing the obtained resource quantification relation functions DBF and SBF, obtaining the maximum delay corresponding to a certain resource and the maximum backlog under the current resource condition in a certain time period according to the curve relation of the DBF, SBF and the resources, obtaining the estimated execution time according to the function relation of the DBF and the SBF, and sending the estimated execution time and the resource proportion information to the scheduler module;
And the distributed time scale dynamic adjustment module is used for carrying out fine granularity on the component tasks with time constraint precision larger than the threshold according to the obtained sequential constraint relation and the latest deadline between PoComp component production logics, and sending the results to the scheduler module so as to realize real-time coordination of a plurality of different time scale components.
4. A platform-oriented efficient physical information production system according to claim 3, wherein the DBF represents a component task load maximum arrival curve, which is:
Wherein I is the length of time from 0; t is defined as the task overcycle, which is the least common multiple of all machining cycles, i.e P (l) is a time-dependent system task parallelism function; phi is a processing task which can be executed in parallel, theta is a processing task which cannot be executed in parallel, and (phi+theta) is all processing links of the product i; delta is the resource waste caused by the waiting delay generated by the processing of the waiting node in the current procedure; z is the sum of overhead and tail task resource requirements for non-full cycle operation.
5. A platform-oriented efficient physical information production system according to claim 3, wherein the SBF represents a computational resource minimum service profile that is:
Wherein, C n is the computing power of PoComp components N at time l, N is the number of all PoComp components, T ′ is the arrival cycle of the physical production system resources, and Q is the computing resource provided by the non-positive cycle physical production system.
6. The platform-oriented efficient information physical production method is applied to the platform-oriented efficient information physical production system as claimed in claim 1, and is characterized by comprising the following steps:
The connectivity between the network protocol and the components of each module in the platform layer is unified through a protocol set, and interaction semantics in the interface description are specified through a semantic matching module;
The production information is transmitted to a service module for analysis through the middleware facing the OS, and the production information representing the task is transmitted to a PoComp component;
The PoComp component optimizes two resource quantization relation functions representing the shortest processing time and the minimum processing energy consumption through a distributed time module, adjusts the production speed according to time constraint, and generates estimated execution time of corresponding processing steps of each station;
According to the task execution sequence constraint relation obtained by the state module and the behavior parameters obtained by the semantic matching module through conversion, performing time constraint analysis on the control rule module and providing the latest deadline of the execution time for the task;
And according to whether the latest deadline given to the scheduler module by the control rule module is met, performing online scheduling optimization by the scheduler module: changing the ratio of the resource adjusting module to the resource request and the allocation, dynamically adjusting the ratio of the resources allocated to the task through the scheduler module when the estimated execution time cannot meet the latest deadline, or elastically allocating the resources through the module when the application resource amount is higher than the resource amount required by completing the current task, and reserving redundant resources for other component tasks;
The PoComp component acquires a control instruction and configuration information generated by online dispatching optimization of the platform layer dispatcher module through the middleware API, analyzes operation required by the production process through the control rule module to carry out production logic control output action, and feeds back a result to the platform layer to wait for the next instruction after the operation is finished.
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