CN103092574B - A kind of based on recurrence autonomous type complex task decomposing system and method - Google Patents
A kind of based on recurrence autonomous type complex task decomposing system and method Download PDFInfo
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Abstract
The invention discloses a kind of based on recurrence autonomous type complex task decomposing system and method.The present invention specifically comprises the steps: 1) Task-decomposing system is made up of ability base, streamline storehouse and recurrence decomposing module; 2) ability base comprises artificial ability and programing power, and two kinds of abilities comprise all again capacity of decomposition and executive capability; 3) combination of each executive capability after old Task-decomposing is comprised in streamline storehouse; 4) recurrence decomposing module accepts the task that user submits to, by Recursion process, this Task-decomposing is become each subtask, until can be corresponding with the executive capability in ability base, set up new task pipeline, adds in streamline storehouse; 5) user submits task to, judges whether task is new task, if new task first performs the coupling execution in streamline storehouse again of recurrence decomposing module, if known task directly coupling execution in streamline storehouse.The present invention adopts the pattern of recurrence autonomous type to allow user without the need to being concerned about that the complexity of task just can be decomposed and execute the task.
Description
Technical field
The present invention relates to computer software field, be specifically related to a kind of based on recurrence autonomous type complex task decomposing system and method.
Background technology
Along with the development of network technology, desktop computer, notebook, panel computer, the electronic equipments such as smart mobile phone also emerge in an endless stream, and greatly facilitate life and the work of people.People can pass through mobile device distributing electronic data whenever and wherever possible, such as send out microblogging, take pictures, and send out mail etc.Can say, we just live in data age, be difficult to estimate that the electronic data total amount that the whole world stores is how many, according to IDC (InternetDataCenter) estimate 2011 " Digital Global " project (digitaluniverse) data total amount be 1.8ZB, and these data are all increasing sharply every year.1ZB is equivalent to the data of the 21 power bytes of 10, or is equivalent to 1000EB, 1000000PB, or the data of 1,000,000,000 TB.This is equivalent to the order of magnitude of everyone disc driver in the world.In addition, also have mass data, most of data are locked in (as search engine) or financial and Scientific Organizations in maximum web page contents, and personal data also increase fast.But the more important thing is, the data that computing machine produces are more huge.Machine daily record, RFID reader, sensor network, vehicle GPS and retail transaction data etc., these all impel " mountain of data is more and more higher ".
The data volume published is also in cumulative year after year.As enterprise or tissue, then can not manage the data of oneself by all means, following success depends on whether it can from the extracting data bid value of its hetero-organization to a great extent.Therefore, the process of mass data ground just seems particularly important.MapReduce is the distributed programmed model of one that Google company develops for mass data processing in extensive group.In simple terms, Map is the process of " dividing ", and it goes process for mass data being divided into some fritters to give some processors; And Reduce is the process of " conjunction ", it mainly gathers the result after the execution of these processors.MapReduce model is divided into User, Master and Worker tri-roles in the entire system.User primary responsibility submits to Master user program; Master, primary responsibility Data Placement, task scheduling, load balancing, fault-tolerant processing etc., it can select idle Worker to distribute Map, Reduce task for it according to the loading condition of each Worker; Worker is working node, is responsible for receiving task from Master and carries out data processing and calculating.Worker is divided into MapWorker and ReduceWorker again, and MapWorker is responsible for the key-value pair of parsing task, performs Map operation, then intermediate result is buffered in local disk, and address is returned to Master; ReduceWorker obtains the key-value pair address of intermediate result from Master, reads data, carries out sequence abbreviation, and return results to user program by key.The very convenient use of this model, it conceals the details of parallel computation, mistake disaster tolerance, local optimization and load balancing.Easily complete large-scale calculations, such as, the Webpage search service of Google, sequence, data mining, machine learning, and other system.By MapReduce, application program can be run more than on the large-scale cluster of 1000 nodes again, and provides the wrong disaster tolerance through optimizing.
There is following problem in existing task analytic approach, 1. in existing task analytic approach, because Mission And Computer decomposing program is man-to-man relation, the normally large-scale and complexity of task that user submits to, program can only according to specific task design resolution process program.This method exacerbates the dependence of task and program: specific program can only process specific task, isolation serial, and executive mode is single; 2. the dependence of task and program, be unfavorable for the flexible last decomposition of task, such as, when the priority of task and processing speed change, computer network cannot be configured the generation dealing with this change automatically, thus the task processing power of network is reduced.
Summary of the invention
The object of the invention is for the deficiencies in the prior art, provide a kind of based on recurrence autonomous type complex task decomposing system and method.
A kind of based on recurrence autonomous type complex task decomposing system, comprise ability base, streamline storehouse and recurrence decomposing module.
Ability base refers to the set to the various abilities that task processes, and comprises artificial ability and programing power, and artificial ability and programing power include capacity of decomposition and executive capability; Artificial ability is by the ability of artificial treatment task, programing power is by the ability of computer programs process task, capacity of decomposition is multiple subtask by Task-decomposing, executive capability is finished the work according to the treatment scheme of task, by multiple executive capability combination being obtained the ability of bulky grain degree, need to comprise characterisitic parameter in each ability description in ability base, comprise the price of ability, prestige, execution time and restrictive condition, each ability in ability base is registered to ability base by the owner of ability.
Streamline storehouse comprises many streamlines, every bar streamline comprises the combination of executive capability corresponding to each subtask after known task decomposition, and this combination arranges by the execution sequencing of each executive capability, streamline storehouse refers to carries out unified management by certain logic the streamline of all known task.
Recurrence decomposing module accepts the task that user submits to, by Recursion process, Task-decomposing is become each subtask, until each subtask is all corresponding with the executive capability in ability base, sets up new streamline, and is added in streamline storehouse by new streamline.
A kind of based on recurrence autonomous type complex task decomposition method, specifically comprise the steps:
Step (1) Task-decomposing system accepts submitting to of task, first gives recurrence decomposing module and processes;
Step (2) recurrence decomposing module searches in streamline storehouse the corresponding streamline whether having this task, if can not find, task is new task, start the streamline setting up new task, and jump to step (3), if found, jump to step (5) for processed task;
Described recurrence decomposing module search procedure is as follows:
Extract task names key word, search in streamline storehouse according to key word, see if there is the streamline corresponding with key word; If there are many streamlines, then require to carry out deleting choosing by user profile, select optimum matching; If there is unique streamline, then direct as optimum matching; If there is no corresponding streamline, then set up the streamline of new task;
Step (3) task matching capacity storehouse, obtain capacity of decomposition or executive capability by coupling, obtain capacity of decomposition and forward step (4) to, obtain executive capability and forward step (5) to, if capacity of decomposition and executive capability all mate less than, then stop decompose;
Described mate the task of referring to according to the granularity degree of self and characterisitic parameter with ability base, with the capabilities match of multi-granule in ability base and many characterisitic parameters, by existing task process streamline is registered in ability base as a kind of new executive capability the ability realizing multi-granule, need the characterisitic parameter of the characterisitic parameter of task and ability to carry out comprehensive matching during capabilities match, in the multiple abilities meeting characterisitic parameter, select optimum ability.
Described multi-granule and many characterisitic parameters refer to the granularity of multiple subtask and the summation of characterisitic parameter.
This Task-decomposing is each subtask by step (4) capacity of decomposition, and each subtask is resubmited, and forwards step (2) to;
Step (5) adds this executive capability in the task process streamline of this task;
Step (6) decomposes by the recurrence of step (1) ~ step (5) the task process streamline obtaining this task, adds task process streamline storehouse to.
Beneficial effect of the present invention is as follows:
One aspect of the present invention decreases the dependence of task and program in Task-decomposing process, strengthens the processing power of network task on the other hand, is applicable to process complex task increasing in network; The present invention, by recurrence and pipelining, is applied in network in conjunction with artificial and computer program ability and is carried out Task-decomposing and execution.In task decomposable process, recurrence is decomposed into the less subtask of multiple scale layer by layer a large complicated task and performs, and greatly reduces the complexity of calculating.In task implementation, the procedural order modularization that each subtask processes by streamline, executed in parallel, greatly increases the treatment effeciency of task.Meanwhile, the present invention has been used by real system and has proved practicable, meets the demand of in computer network, complex task being carried out to flexible and changeable decomposition and execution.
Accompanying drawing explanation
Fig. 1 is based on the system model of recurrence autonomous type Task-decomposing;
Fig. 2 recurrence Task-decomposing block flow diagram;
The principle schematic of Fig. 3 embodiment.
Embodiment
Below in conjunction with drawings and Examples, the present invention will be further described.
As shown in Figure 1, a kind of based on recurrence autonomous type complex task decomposing system, comprise ability base, streamline storehouse and recurrence decomposing module.
Ability base refers to the set to the various abilities that task processes, and comprises artificial ability and programing power, and artificial ability and programing power include capacity of decomposition and executive capability; Artificial ability is by the ability of artificial treatment task, programing power is by the ability of computer programs process task, capacity of decomposition is multiple subtask by Task-decomposing, executive capability is finished the work according to the treatment scheme of task, by multiple executive capability combination being obtained the ability of bulky grain degree, need to comprise characterisitic parameter in each ability description in ability base, comprise the price of ability, prestige, execution time and restrictive condition, each ability in ability base is registered to ability base by the owner of ability.
Streamline storehouse comprises many streamlines, every bar streamline comprises the combination of executive capability corresponding to each subtask after known task decomposition, and this combination arranges by the execution sequencing of each executive capability, streamline storehouse refers to carries out unified management by certain logic the streamline of all known task.
Recurrence decomposing module accepts the task that user submits to, by Recursion process, Task-decomposing is become each subtask, until each subtask is all corresponding with the executive capability in ability base, sets up new streamline, and is added in streamline storehouse by new streamline.
As shown in Figure 2, a kind of based on recurrence autonomous type complex task decomposition method, specifically comprise the steps:
Step (1) Task-decomposing system accepts submitting to of task, first gives recurrence decomposing module and processes;
Step (2) recurrence decomposing module searches in streamline storehouse the corresponding streamline whether having this task, if can not find, task is new task, start the streamline setting up new task, and jump to step (3), if found, jump to step (5) for processed task;
Described recurrence decomposing module search procedure is as follows:
Extract task names key word, search in streamline storehouse according to key word, see if there is the streamline corresponding with key word; If there are many streamlines, then require to carry out deleting choosing by user profile, select optimum matching; If there is unique streamline, then direct as optimum matching; If there is no corresponding streamline, then set up the streamline of new task;
Step (3) task matching capacity storehouse, obtains capacity of decomposition or executive capability by coupling, obtains capacity of decomposition and forward step (4) to, obtain executive capability and forward step (5) to;
The described ability of mating granularity and characterisitic parameter in the task of referring to ability base, with the capabilities match of multi-granule in ability base and many characterisitic parameters, by existing task process streamline is registered in ability base as a kind of new executive capability the ability realizing multi-granule, need the characterisitic parameter of the characterisitic parameter of task and ability to carry out comprehensive matching during capabilities match, in the multiple abilities meeting characterisitic parameter, select optimum ability.
This Task-decomposing is each subtask by step (4) capacity of decomposition, and each subtask is resubmited, and forwards step (2) to;
Step (5) adds this executive capability in the task process streamline of this task;
Step (6) decomposes by the recurrence of step (1) ~ step (5) the task process streamline obtaining this task, adds task process streamline storehouse to.
embodiment 1:
Understand for the ease of persons skilled in the art and realize the present invention, now 3 further illustrating the present invention by reference to the accompanying drawings.
As shown in Figure 3, the present embodiment by the browser of the PC of a WindowsXP operating system as client, the server of a linux operating system, this server has the service function such as web and database purchase, is used for processing the client user's task of submitting to.
Loading tasks decomposing system on server end, server end according to Task-decomposing system decomposition and process client submit to task, the ability base stored in match server database or streamline storehouse, eventually to client feedback task result.We have constructed the hardware environment of the Task-decomposing system based on web for this reason, decompose executive routine process the various tasks submitted to from client user by a Task-decomposing website and background task.
Translate into English " translation paper " task for Chinese Papers below, the decomposition method process based on recurrence autonomous type complex task be described in detail:
Steps A: first build Task-decomposing System Implementation environment, Task-decomposing system comprises browser, the server of client, and wherein server has web, database purchase function and recurrence Task-decomposing program; Database in server comprises Task-decomposing website, ability base table, task pipeline storehouse table.
Step B: ability base table comprises capability names main fields, other fields such as the mode of operation corresponding with ability, ability granularity.For " translation paper " task, ability base table need comprise the program translation ability of human translation ability and computer-internal, there is provided when wherein human translation ability is registered to Task-decomposing website by the member being responsible for translation service, as translated one section, translate one, translation multistage, translates the executive capability of a section, and splits the capacity of decomposition of paper, fractionation paragraph.The program translation ability of computer-internal by manually having loaded on computers, as the executive capability of the translation software that Baidu's translation software, Google's translation software, member write, by paragraph or sentence segmentation broken down into program ability;
Step C: comprise the task names of known task, process streamline two main fields corresponding with task in the table of streamline storehouse, and other fields such as task processing time, process cost;
Step D: Task-decomposing system accepts the request of the task that user submits to, be transmitted to recurrence Task-decomposing program, by the mode of Recursion process, this task is progressively decomposed into less subtask, until subtask can be corresponding with the executive capability in ability base, set up new task pipeline, add in task pipeline storehouse, its concrete steps comprise:
A: user is according to the demand of oneself, send to the Task-decomposing system of server end task requests Chinese Papers being translated into English " translation paper " by client browser, specify the attribute specification to task result simultaneously, as needs completed in 5 hours, the price expected is 300 yuan, and translation quality is high.
B: Task-decomposing system extracts the key word " translation " in the subtask title that original or Step d resubmits, and searches, see if there is the streamline corresponding with key word according to key word to streamline storehouse in showing; If there are many streamlines, then require to carry out deleting choosing by user profile, after selecting optimum matching, jump to step e; If there is unique streamline, then directly jump to step e as after optimum matching; If there is no corresponding streamline, then set up the streamline of new task, jump to step c;
C: Task-decomposing system, by the ability base table in keyword query databases such as " translations ", returns capacity of decomposition or executive capability result by matching database, if return capacity of decomposition to forward steps d to, returns executive capability and forward step e to.
D: the Task-decomposing of " translation paper " is less subtask to recurrence Task-decomposing program by Task-decomposing system forwards task requests, such as " translation paragraph ", " translation of the sentence ", Task-decomposing website forwards less subtask again to recurrence Task-decomposing program again, forwards step b to.
E: in Task-decomposing system task pipeline storehouse table in a database, find out corresponding streamline, the executive capability that then intron task is corresponding.
F: decompose the task process streamline obtaining " translation paper " by the recurrence of step a to e, adds to this streamline in the task process streamline storehouse table in database.
Step e: by above step, Task-decomposing system has just completed the process to " translation paper " task, the task pipeline now mated may have multiple choices, Task-decomposing system submits the attribute specification of specifying during task to according to user, filter out in satisfied 5 hours and complete, the price expected is 300 yuan, the optimum matching streamline that translation quality is high.
Step F: putting in order and executive mode that executive capability is corresponding of the corresponding executive capability in the subtask of adding in the best streamline that Task-decomposing system filters out according to step e, such as best streamline comprises the ability of the translation 5 that member A registers, member B translates the ability of 2 sections, Baidu's translation software translates the ability of 1 section, then the translation duties corresponding with member registration capacity of water distribute by mail he by the ability of member registration, until each paragraph or sentence translation result feedback get back to Task-decomposing system, this optimum matching streamline is re-registered the task coupling in order to later same attribute specification in ability base by Task-decomposing system, English papers after translation is returned to decomposition and the execution of user's completing user " translation paper " task by each result of final integration.
According to " translation paper " task that user submits to, if processed task, then directly executed the task by keyword query database matching streamline storehouses such as " translations ".If new task, then to realize an expert system, complete and be decomposed into little and simple task, the intelligent decision of matching task attribute from complex task.Completing in 5 hours such as required by user, the English quality of translation is high, and Task-decomposing specific to each sentence, is then mated the respective attributes of each sentence ability base by recurrence Task-decomposing program.The expert system of Task-decomposing website needs the demand these mission requirements changed into individual subtask, carefully checks each sentence as met the demand needs.
According to the complexity of task, first the task that user submits to by recurrence Task-decomposing program is decomposed into translate phase and begins task, and these subtasks can be decomposed into less subtask again, as translation of the sentence subtask.Until the executive capability in matching capacity storehouse, subtask, namely in ability base table, there is the translator of English of this sentence.Meanwhile, the decomposing program of logger task is set up capacity of decomposition and is stored in a database, to meet the decomposition of same task later.
According to the diversity of streamline, the price that Task-decomposing website can go out according to user, the time how long completed, the attributes match streamlines such as translation quality.If the translation quality of user feedback paper does not reach his requirement, then website the member of service is provided or staff can register artificial ability base, have and manually paper verified, until meet the demand of user.
According to above-mentioned Task-decomposing process, when user proposes a kind of mission requirements to Task-decomposing website, Task-decomposing website is according to recurrence Task-decomposing program recurrence task resolution, until the executive capability of corresponding granularity is mated in subtask, if programing power can not meet the processing attribute of task, artificial ability Processing tasks can be asked, finally obtain the streamline of a satisfaction to perform this task.
Although depict the present invention by embodiment, those of ordinary skill in the art know, the present invention has many distortion and change and do not depart from spirit of the present invention, and the claim appended by wishing comprises these distortion and change and do not depart from spirit of the present invention.
Claims (2)
1., based on a recurrence autonomous type complex task decomposing system, comprise ability base, streamline storehouse and recurrence decomposing module; It is characterized in that:
Ability base refers to the set to the various abilities that task processes, and comprises artificial ability and programing power, and artificial ability and programing power include capacity of decomposition and executive capability; Artificial ability is by the ability of artificial treatment task, programing power is by the ability of computer programs process task, capacity of decomposition is multiple subtask by Task-decomposing, executive capability is finished the work according to the treatment scheme of task, by multiple executive capability combination being obtained the ability of bulky grain degree, need to comprise characterisitic parameter in each ability description in ability base, comprise the price of ability, prestige, execution time and restrictive condition, each ability in ability base is registered to ability base by the owner of ability;
Streamline storehouse comprises many streamlines, every bar streamline comprises the combination A of executive capability corresponding to each subtask after known task decomposition, and combination A arranges by the execution sequencing of each executive capability, streamline storehouse refers to carries out unified management by certain logic the streamline of all known task;
Recurrence decomposing module accepts the task that user submits to, by Recursion process, Task-decomposing is become each subtask, until each subtask is all corresponding with the executive capability in ability base, sets up new streamline, and is added in streamline storehouse by new streamline.
2. a kind of method based on recurrence autonomous type complex task decomposing system as claimed in claim 1, specifically comprises the steps:
Step (1) Task-decomposing system accepts submitting to of task A, first gives recurrence decomposing module and processes;
Step (2) recurrence decomposing module searches in streamline storehouse the corresponding streamline whether having task A or subtask D, if can not find, task A or subtask D is new task B, start the streamline setting up new task B, and jump to step (3), if found, jump to step (5) for processed task C;
Described recurrence decomposing module search procedure is as follows:
Extract task names key word, search in streamline storehouse according to key word, see if there is the streamline corresponding with key word; If there are many streamlines, then require to carry out deleting choosing by user profile, select optimum matching; If there is unique streamline, then direct as optimum matching; If there is no corresponding streamline, then set up the streamline of new task;
Step (3) new task B matching capacity storehouse, obtain capacity of decomposition or executive capability by coupling, obtain capacity of decomposition and forward step (4) to, obtain executive capability and forward step (5) to, if capacity of decomposition and executive capability all mate less than, then stop decompose;
The coupling of ability base refers to that task is according to the granularity degree of self and characterisitic parameter, with the capabilities match of multi-granule in ability base and many characterisitic parameters, by existing task process streamline is registered in ability base as a kind of new executive capability the ability realizing multi-granule, need the characterisitic parameter of the characterisitic parameter of task and ability to carry out comprehensive matching during capabilities match, in the multiple abilities meeting characterisitic parameter, select optimum ability;
Described multi-granule and many characterisitic parameters refer to the granularity of multiple subtask and the summation of characterisitic parameter;
New task B is decomposed into each subtask D by step (4) capacity of decomposition, and each subtask D is resubmited, and forwards step (2) to;
Step (5) adds the executive capability obtained in step 3 in the task process streamline of new task B or processed task C;
Step (6) decomposes by the recurrence of step (1) ~ step (5) the task process streamline obtaining task A, adds task process streamline storehouse to.
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