阅读说明：本技术 用于边缘交互的调度信息建模方法、装置、设备和存储介质 (Scheduling information modeling method, device, equipment and storage medium for edge interaction ) 是由 王峰 谭少飞 王建民 宋刚 杨银香 底园园 于 2021-10-15 设计创作，主要内容包括：本发明涉及一种用于边缘交互的调度信息建模方法、装置、设备和存储介质,通过获取调度结果数据,基于预设分类规则对调度结果数据中的工序进行分类,以生成相应的工序状态数据,其中工序状态数据中包括有每个工序的操作信息；生成与工序状态数据中的每个工序的操作信息匹配的数据标识；基于数据标识和操作信息,生成每个工序的操作指令,以操作指令与管理层进行交互,使得操作指令可以直接被管理层进行识别和处理,从而使得相应的管理层能够直接根据操作指令对处理设备进行调度,不再单纯依赖于人的操作,从而提高了调度结果实施的效率,也使得服务层与管理层之间的交互更加的高效。(The invention relates to a scheduling information modeling method, a device, equipment and a storage medium for edge interaction, wherein the scheduling result data is obtained, and procedures in the scheduling result data are classified based on a preset classification rule to generate corresponding procedure state data, wherein the procedure state data comprises operation information of each procedure; generating a data identifier matched with the operation information of each process in the process state data; based on the data identification and the operation information, the operation instruction of each process is generated, the operation instruction interacts with the management layer, the operation instruction can be directly identified and processed by the management layer, the corresponding management layer can directly schedule the processing equipment according to the operation instruction, the operation is not only dependent on human operation, the implementation efficiency of the scheduling result is improved, and the interaction between the service layer and the management layer is more efficient.)

1. A scheduling information modeling method for edge interaction is characterized by comprising the following steps:

acquiring scheduling result data;

classifying the processes in the scheduling result data based on a preset classification rule to generate corresponding process state data, wherein the process state data comprises operation information of each process;

generating a data identifier matched with the operation information of each process in the process state data;

and generating an operation instruction of each process based on the data identification and the operation information, and interacting the operation instruction with a management layer.

2. The method of claim 1, wherein the classifying the process in the scheduling result data based on a preset classification rule to generate corresponding process status data comprises:

the process is divided into a transportation stage and a processing stage based on the type of the processing equipment corresponding to the process to generate the process status data of the corresponding stage.

3. The method according to claim 2, wherein the obtaining of the type of processing equipment of the process comprises:

and acquiring equipment information of the processing equipment corresponding to the process, and identifying the equipment information to determine the type of the processing equipment.

4. The method of claim 1, wherein said generating a data identifier that matches the operational information for each of the process steps in the process state data comprises:

and converting the operation information into the data identification containing the label name and the label content based on a preset conversion rule.

5. The method of claim 1, wherein generating the operation command for each process based on the data identifier and the operation information, and interacting with a management layer with the operation command comprises:

and processing the data identifier and the operation information into an operation instruction data block in a JSON format based on a JSON data exchange format, and interacting the operation instruction data block in the JSON format with the management layer.

6. The method according to any of claims 1 to 5, wherein the obtaining of the scheduling result data comprises: acquiring scheduling result data based on a simple heuristic method and/or an intelligent heuristic method;

the simple heuristic method comprises a method for scheduling the working procedure by taking the shortest arrival-as-service and processing time as a target;

the intelligent heuristic method comprises a method for scheduling the working procedure based on a genetic algorithm and/or a particle swarm algorithm.

7. A scheduling information modeling apparatus for edge interaction, comprising:

the reading module is used for acquiring scheduling result data;

the classification module is used for classifying the procedures in the scheduling result data based on a preset classification rule so as to generate corresponding procedure state data, and the procedure state data comprises operation information of each procedure;

the identification conversion module is used for generating a data identification matched with the operation information of each procedure in the procedure state data; and

and the format conversion module is used for generating an operation instruction of each procedure based on the data identification and the operation information, and interacting the operation instruction with a management layer.

8. An apparatus, comprising: a memory and a processor;

the memory is used for storing programs;

the processor is configured to execute the program to implement the steps of the method for modeling scheduling information for edge interaction according to any one of claims 1 to 6.

9. A storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for modeling scheduling information for edge interaction according to any one of claims 1 to 6.

Technical Field

The invention relates to the technical field of production management, in particular to a scheduling information modeling method, device, equipment and storage medium for edge interaction.

Background

In the production and manufacturing process, calculation and formulation of a scheduling plan need to consume a large amount of labor, material resources and time cost, and as the production management system develops towards edge calculation, the scheduling calculation service also becomes one of the key components of the edge calculation module.

In a production management system, scheduling calculation services are usually deployed in a service layer of the system, corresponding scheduling result data are calculated in the service layer, then the scheduling result data are transmitted to a management layer, corresponding management personnel issue corresponding control instructions according to the generated scheduling result data, the scheduling result data are usually displayed in forms of Gantt charts, tables and the like, and the management personnel need to correspondingly understand and arrange the scheduling result data and then send the scheduling instructions of corresponding equipment to corresponding equipment operators for implementation. The manual intervention undoubtedly reduces the efficiency of the implementation of the scheduling result, and also limits the interaction efficiency between the service layer and the management layer.

Disclosure of Invention

In order to solve the problem of low data interaction efficiency of scheduling results in the prior art, the invention provides a scheduling information modeling method, device, equipment and storage medium for edge interaction, which have the characteristics of higher interaction efficiency, quicker identification of scheduling results and the like.

According to the scheduling information modeling method for edge interaction provided by the specific implementation manner of the invention, the method comprises the following steps:

acquiring scheduling result data;

classifying the processes in the scheduling result data based on a preset classification rule to generate corresponding process state data, wherein the process state data comprises operation information of each process;

generating a data identifier matched with the operation information of each process in the process state data;

and generating an operation instruction of each process based on the data identification and the operation information, and interacting the operation instruction with a management layer.

Further, the classifying the processes in the scheduling result data based on the preset classification rule to generate corresponding process status data includes:

the process is divided into a transportation stage and a processing stage based on the type of the processing equipment corresponding to the process to generate the process status data of the corresponding stage.

Further, the process of acquiring the type of the processing equipment of the process includes:

and acquiring equipment information of the processing equipment corresponding to the process, and identifying the equipment information to determine the type of the processing equipment.

Further, the generating a data identifier matching with the operation information of each process in the process state data includes:

and converting the operation information into the data identification containing the label name and the label content based on a preset conversion rule.

Further, the generating an operation instruction of each process based on the data identifier and the operation information, and interacting with a management layer by the operation instruction includes:

and processing the data identifier and the operation information into an operation instruction data block in a JSON format based on a JSON data exchange format, and interacting the operation instruction data block in the JSON format with the management layer.

Further, the obtaining of the scheduling result data includes: acquiring scheduling result data based on a simple heuristic method and/or an intelligent heuristic method;

the simple heuristic method comprises a method for scheduling the working procedure by taking the shortest arrival-as-service and processing time as a target;

the intelligent heuristic method comprises a method for scheduling the working procedure based on a genetic algorithm and/or a particle swarm algorithm.

According to a specific embodiment of the present invention, a scheduling information modeling apparatus for edge interaction includes:

the reading module is used for acquiring scheduling result data;

the classification module is used for classifying the procedures in the scheduling result data based on a preset classification rule so as to generate corresponding procedure state data, and the procedure state data comprises operation information of each procedure;

the identification conversion module is used for generating a data identification matched with the operation information of each procedure in the procedure state data; and

and the format conversion module is used for generating an operation instruction of each procedure based on the data identification and the operation information, and interacting the operation instruction with a management layer.

According to a specific embodiment of the present invention, there is provided an apparatus including: a memory and a processor;

the memory is used for storing programs;

the processor is configured to execute the program to implement the steps of the scheduling information modeling method for edge interaction as described above.

According to a specific embodiment of the present invention, a storage medium is provided, in which a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps of the scheduling information modeling method for edge interaction as described above.

The invention has the beneficial effects that: the method comprises the steps of classifying processes in scheduling result data based on a preset classification rule by obtaining the scheduling result data to generate corresponding process state data, wherein the process state data comprises operation information of each process; generating a data identifier matched with the operation information of each process in the process state data; based on the data identification and the operation information, the operation instruction of each process is generated, the operation instruction interacts with the management layer, the operation instruction can be directly identified and processed by the management layer, the corresponding management layer can directly schedule the processing equipment according to the operation instruction, the operation is not only dependent on human operation, the implementation efficiency of the scheduling result is improved, and the interaction between the service layer and the management layer is more efficient.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

FIG. 1 is a flow diagram of a method for modeling scheduling information for edge interaction provided in accordance with an illustrative embodiment;

FIG. 2 is a block diagram of scheduling result data provided in accordance with an exemplary embodiment;

FIG. 3 is a block diagram of process state data provided in accordance with an exemplary embodiment;

FIG. 4 is a look-up table of data identifications provided in accordance with an exemplary embodiment;

FIG. 5 is a schematic diagram of a scheduling information modeling apparatus for edge interaction provided in accordance with an exemplary embodiment;

fig. 6 is a schematic diagram of an apparatus provided in accordance with an example embodiment.

Reference numerals

1-a reading module; 2-a classification module; 3-an identity conversion module; 4-format conversion module; 5-a memory; 6-a processor.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, an embodiment of the present invention provides a scheduling information modeling method for edge interaction, which specifically includes the following steps:

101. acquiring scheduling result data;

generally, the calculation of the scheduling result in production scheduling can be performed by adopting a conventional simple heuristic method and an intelligent heuristic method, wherein the simple heuristic method can comprise the calculation of the scheduling result aiming at the purposes of instant service, shortest processing time and the like; the intelligent heuristic method comprises the steps of calculating scheduling result data by using a genetic algorithm, a particle swarm algorithm and the like, wherein the generally calculated scheduling result data can be visually displayed through a Gantt chart.

102. Classifying the processes in the scheduling result data based on a preset classification rule to generate corresponding process state data, wherein the process state data comprises operation information of each process;

since the processes in the scheduling result data are generally divided on the basis of the corresponding processing equipment, the processes in the scheduling result data can be classified on the basis of the processing equipment, thereby forming process status data, wherein the process status data includes operation information of each process, such as information required for processing, such as workpiece information, processing equipment, transportation equipment, equipment status, processing time, start time, completion time, and the like.

103. Generating a data identifier matched with the operation information of each process in the process state data;

the operation information of the process can be converted into a universal data identifier through a corresponding conversion rule, information such as operation content in the operation information is represented in the form of the identifier, and the operation information is converted into a data identifier which is in a uniform format and can be translated.

104. And generating an operation instruction of each process based on the data identification and the operation information, and interacting the operation instruction with the management layer.

The operation instruction of each process can be generated by combining the data identification and the corresponding operation information, and the instruction interaction can be directly carried out between the service layer and the management layer of the production management system through the instruction, so that the corresponding management layer can directly schedule the processing equipment according to the operation instruction without purely relying on human operation, the efficiency of implementing the scheduling result is improved, and the interaction between the service layer and the management layer is more efficient.

In another embodiment of the present invention, classifying the processes in the scheduling result data based on a preset classification rule to generate corresponding process status data includes:

the process is divided into a transportation stage and a processing stage based on the type of the processing equipment corresponding to the process to generate process status data of the corresponding stage.

The acquisition process of the type of the processing equipment of the process comprises the following steps:

and acquiring equipment information of the processing equipment corresponding to the working procedure, and identifying the equipment information to determine the type of the processing equipment.

Because the production and manufacturing process of the workpiece can be divided into a transportation stage and a processing stage, and the corresponding processing stage is processed by various processing devices, the process can be divided into the transportation stage and the processing stage by dividing the types of the processing devices, wherein the transportation stage can transport the workpiece by using a robot, an AGV, a traveling frame and other devices as carriers. In the processing stage, equipment such as a lathe, a milling machine, a grinding machine, a drilling machine, a machining center and the like are used as carriers.

The corresponding equipment information can be obtained by obtaining the information of the processing equipment of the procedure in the scheduling result and carrying out corresponding identification to determine the type of the processing equipment. Taking the gantt chart display type of the scheduling result data as an example, the gantt chart is a process division performed by the processing equipment, and for each processing equipment corresponding to a process with workpieces ordered according to time, the corresponding process is found only by searching and the like, if the position of the process is determined in the form of horizontal and vertical coordinates, the processing equipment corresponding to the process is also determined, and the type of the equipment can be determined after the information of the corresponding equipment is read. For the process of acquiring the device information, a person skilled in the art may select an existing identification mode according to actual application requirements, and the present invention is not described herein again.

In some embodiments of the present invention, generating a data identifier that matches the operational information for each process in the process state data comprises:

and converting the operation information into a data identifier containing a label name and label content based on a preset conversion rule.

Specifically, the process operation information in each scheduling result in the comparison table shown in fig. 4 includes tag names including a process entity code (ID), a work number (joba) of the process, a work number (Ope), a device number (Mac) of the operation process, a Start time (Start) of the process, an End time (End) of the process, a device state (Status) of the operation process, and total information (Con) of the process entity, and each tag name has a corresponding definition, and the corresponding tag content can be represented by numbers, english letters, and other characters, and has a corresponding explanation. When the method is applied specifically, a set of lightweight and standardized full-scheduling information modeling specification can be adopted for a production management system.

It is understood that, regarding the form and content of the tag name and the specific definition of the tag name, those skilled in the art can select the tag name according to different practical application scenarios, and the invention is not limited herein.

Generating an operation instruction of each procedure based on the data identification and the operation information, and interacting the operation instruction with the management layer, wherein the operation instruction comprises the following steps:

and processing the data identifier and the operation information into an operation instruction data block in a JSON format based on the JSON data exchange format, and interacting with the management layer by using the operation instruction data block in the JSON format.

The process set information after the data identifier conversion is completed is expressed as a JSON data block, and JSON (javascript Object notification) is a lightweight data exchange format. The method is easy to read and write by human, and is easy to analyze and generate by a machine. Taking the actual transportation stage and the machining preparation stage of the workpiece 3 in the process 2 as an example, JSON data in the following form can be generated:

wherein the data block with ID of 7 is the actual transportation stage of the working procedure 2 of the workpiece 3, the number of the corresponding transportation equipment is T1, the starting time is that the scheduling task of the working procedure starts from 0 moment, the node of the current time is 315 minutes, the ending time is that the scheduling task of the working procedure starts from 0 moment, the node of the current time is 325 minutes, the state of the transportation equipment is the actual transportation stage, and the corresponding working procedure state T corresponds to^o(ii) a The actual transport phase of the process 2 of the workpiece 3 is from the area 2 to the area 1.

Similarly, the data block with ID 8 is the machining preparation stage of the process 2 of the workpiece 3, the number of the machining equipment is M1, the machining start time is the time from the time 0 of the scheduling task of the process, the time node to the present is 325 minutes, the end time is the time from the time 0, the time node to the present is 328 minutes, the equipment state is the machining preparation stage, and the actual state is the machining preparation stage of the process 2 of the workpiece 3. Therefore, the scheduling result data can be expressed as entity JSON data consisting of a plurality of data blocks, the rapid interaction in a production management system and among systems can be realized based on the characteristic that the entity JSON data has light weight, and the system receiving the data can analyze and obtain the scheduling information according to the same rule.

Referring to the operation information conversion look-up table shown in fig. 4, the operation information of a process includes workpiece information, processing equipment, transportation equipment, equipment states, processing time, start time, completion time and the like corresponding to the process, the data block with ID 8 shown in fig. 2 is one state in the process indicated by the vertical coordinate M1 in fig. 2, one state is a rectangular frame shown in the gantt chart, the (3, 2) displayed in the area on the gantt chart indicates the process 2 of the workpiece 3, the vertical coordinate M1 indicates the corresponding processing equipment number, the numerical values of the horizontal coordinates corresponding to the left and right sides of the rectangular frame of the process state respectively indicate the start time and the end time of the state, and the state itself is the processing preparation stage. Based on the process operation information, referring to the rule shown in fig. 4, a JSON data block having an ID of 8 can be generated.

The scheduling information interaction method of the present invention will be further described with reference to the processing procedure of the representation form of the gantt chart of the scheduling result data:

referring to fig. 2, the full scheduling result data is set to D, and is defined as follows:

d ═ O, E formula (1)

O in formula (1) is a process set composed of all processes in the scheduling result data, for example: o ═ O₁₁,O₁₂,O₂₁,O₂₂,O₂₃,O₃₁,O₃₂Denotes process set information with three workpieces, where O₁₁Step 1 of the workpiece 1 is shown, and so on. The process set therefore means: the workpiece 1 has two processes, the workpiece 2 has three processes, the workpiece 3 has two processes, and the processing sequence is the process 1 of the workpiece 1, the process 2 of the workpiece 1, the process 1 of the workpiece 2, the process 2 of the workpiece 2, the process 3 of the workpiece 2, the process 1 of the workpiece 3, and the process 2 of the workpiece 3.

E in formula (1) represents an allocation information set of the process on the equipment, which is defined as follows:

e in formula (2)_jRepresents the subset of the process on device j (j ∈ m), m being the set of all devices. For example, the above-mentioned process set case is referred to as O₁₁And O₂₃To the device 2, then E₂＝{O₁₁,O₂₃}. Will schedule the resultAnd taking the equipment as an object, and acquiring full-scheduling result data D.

Then the manufacturing process is divided into a transportation stage and a processing stage, wherein the transportation stage takes robots, AGVs, racks and other equipment as carriers, the processing stage takes lathes, milling machines, grinding machines, drilling machines, processing centers and other equipment as carriers, the process information composition of different stages is different, and the state composition of any one process is defined as follows:

O'＝∪(T^tw，Tⁿ，T^o，T^r)∪(T^mw，T^l，T^p，T^s) Formula (3)

Wherein' (T) in the formula (3)^tw,Tⁿ,T^o,T^r) Data composition of process states, T, representing the transport phase^twRepresenting the waiting time, T, of the transport equipment after the end of the previous stage of transport until the start of the stageⁿIndicating the time, T, of the empty-load travel of the transport device to the position of the workpiece to be transported^oIndicating the time, T, at which the transport apparatus transports the work to be transported to the destination^rIndicating the time for the transport equipment to complete the transport task and return to the initial point. For the conventional transportation process, if the front and rear working procedures of the workpiece are processed on different equipment, T is carried out^oNot zero, TⁿAnd T^rIs determined based on the position of the transport apparatus and the workpiece.

U (T) in formula (3)^mw,T^l,T^p,T^s) A process state data composition representing a process stage, wherein T^mwIndicating the waiting time, T, of the processing equipment after the end of the previous stage of processing and before the start of the stage^lIndicating preparatory processes prior to the working stage, e.g. mounting of work, T^pIndicating the actual working hours of the working equipment, T^sIndicating when the machining task is completed and the apparatus returns to a state in which it can machine the next workpiece, e.g., unload the workpiece, etc.

Taking scheduling result data D as input, for E in D_jClassifying, and classifying into transportation phase and processing phase according to equipment type, wherein all process state data in the transportation phase is formed into U (T)^tw,Tⁿ,T^o,T^r) All process state data in a processing stage are formed as @ (T @)^mw,T^l,T^p,T^s)。

The process is classified into a transportation stage and a processing stage according to the type of equipment. Because the final implementation objects of the scheduling result data are processing equipment and transportation equipment, and the implementation contents of the two processing equipment are different, all the procedures are classified according to the execution of the processed equipment and the execution of the transportation equipment by taking a Gantt chart of the scheduling result data as an example. The method specifically comprises the following processing steps:

201. traversing each ordinate in the Gantt chart;

202. judging whether the ordinate represents processing equipment or transportation equipment;

203. if the ordinate is processing equipment, all the procedures in the corresponding row are the procedures in the processing stage, and all the procedure state data in the processing stage form U (T) correspondingly^mw,T^l,T^p,T^s)；

204. If the ordinate is transportation equipment, all the procedures in the corresponding row are procedures in a transportation phase, and all the procedure state data in the transportation phase form U (T) correspondingly^tw,Tⁿ,T^o,T^r)。

As shown in FIG. 2, the process of extracting and analyzing the scheduling result data is explained, the transportation process and the state composition of the processing process of a scheduling result Gantt chart are described, the scheduling result data of three workpieces on three processing devices and one transportation device are shown in the chart, the transportation process of the 2 nd procedure of the workpiece 3 is extracted, and the state of the transportation process can be obtained as U (T)^tw,Tⁿ,T^o,T^r) The processing of the 2 nd step of extracting the work 3 can obtain the state of U (T)^mw,T^l,T^p,T^s)。

And building a modular operation instruction data block for all states in all process state data O' in the D by combining the scheduling result data D and the analysis result, and establishing an operation instruction data block model based on JSON (JavaScript Object Notation), wherein the JSON is a light-weight data exchange format, and each JSON block represents one state in the process data.

Referring to fig. 3, the actual transportation process and the machining preparation stage of the workpiece are translated into JSON data blocks. The two operation instruction data blocks respectively show that the data block with the ID of 7 is the actual transportation stage of the process 2 of the workpiece 3, and the data block with the ID of 8 is the processing preparation stage of the process 2 of the workpiece 3.

Based on the same design idea, referring to fig. 5, an embodiment of the present invention further provides a scheduling information modeling apparatus for edge interaction, configured to perform each step in the above scheduling information modeling method for edge interaction, including:

the reading module 1 is used for acquiring scheduling result data;

the classification module 2 is used for classifying the processes in the scheduling result data based on a preset classification rule to generate corresponding process state data, and the process state data comprises operation information of each process;

the identification conversion module 3 is used for generating a data identification matched with the operation information of each procedure in the procedure state data; and

and the format conversion module 4 is used for generating an operation instruction of each procedure based on the data identification and the operation information so as to interact the operation instruction with the management layer.

The scheduling information interaction apparatus provided in this embodiment and the scheduling information interaction method provided in the foregoing embodiment have the same beneficial effects, and are not described herein again.

The embodiment of the present invention shown with reference to fig. 6 also provides an apparatus comprising: a memory 5 and a processor 6;

the memory 5 is used for storing programs;

the processor 6 is used for executing programs to implement the steps of the scheduling information modeling method for edge interaction as described in the above embodiments.

Embodiments of the present invention also provide a storage medium having a computer program stored therein, where the computer program is executed by a processor to implement the steps of the scheduling information modeling method for edge interaction as described in the above embodiments.

The scheduling information modeling method, device, equipment and storage medium for edge interaction provided by the embodiments of the invention are oriented to an intelligent manufacturing mode under an edge computing framework from scheduling result data, and perform interaction of the scheduling result data by establishing data blocks containing full scheduling information such as workpiece information, processing equipment, transportation equipment, equipment state, processing time, starting time, completion time and the like, so that a new efficient and feasible way is provided for interaction of results in actual production among different systems and interaction in the systems, the efficiency of data interaction of the scheduling result is improved, interaction can be performed based on JSON data format rules, and the method, device, equipment and storage medium have the characteristics of light weight and standardization.

While, for purposes of simplicity of explanation, the foregoing method embodiments have been described as a series of acts or combination of acts, it will be appreciated by those skilled in the art that the present invention is not limited by the illustrated ordering of acts, as some steps may occur in other orders or concurrently with other steps in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.

It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the device-like embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The steps in the method of each embodiment of the present invention may be sequentially adjusted, combined, and deleted according to actual needs, and the technical features described in each embodiment may be replaced or combined.

The modules and sub-modules in the device and the terminal of the embodiments of the invention can be combined, divided and deleted according to actual needs.

In the embodiments provided in the present invention, it should be understood that the disclosed terminal, apparatus and method may be implemented in other ways. For example, the above-described terminal embodiments are merely illustrative, and for example, the division of a module or a sub-module is only one logical division, and there may be other divisions when the terminal is actually implemented, for example, a plurality of sub-modules or modules may be combined or integrated into another module, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.

The modules or sub-modules described as separate parts may or may not be physically separate, and parts that are modules or sub-modules may or may not be physical modules or sub-modules, may be located in one place, or may be distributed over a plurality of network modules or sub-modules. Some or all of the modules or sub-modules can be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, each functional module or sub-module in each embodiment of the present invention may be integrated into one processing module, or each module or sub-module may exist alone physically, or two or more modules or sub-modules may be integrated into one module. The integrated modules or sub-modules may be implemented in the form of hardware, or may be implemented in the form of software functional modules or sub-modules.

Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software unit executed by a processor, or in a combination of the two. The software cells may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.