CN109255479A - A kind of relevant participant's selection method of time window based on dynamic programming algorithm - Google Patents
A kind of relevant participant's selection method of time window based on dynamic programming algorithm Download PDFInfo
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- CN109255479A CN109255479A CN201811001421.0A CN201811001421A CN109255479A CN 109255479 A CN109255479 A CN 109255479A CN 201811001421 A CN201811001421 A CN 201811001421A CN 109255479 A CN109255479 A CN 109255479A
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Abstract
The present invention utilizes a kind of relevant participant's selection method of time window based on dynamic programming algorithm.This method designs a kind of about the relevant participant's selection method of time window, maximization data benefit while covering task time section using dynamic programming algorithm, meanwhile, data reliability is defined according to the perception data amount of participant and perception credit value.Introducing credit value update mechanism for participant's credit value dynamic changes makes method have efficient dynamic.A large amount of emulation experiment demonstrates the feasibility of method, improves and collects data reliability and data benefit.
Description
Technical field
The present invention relates to the relevant participant's selection methods of time window in a kind of mobile intelligent perception to be particularly related to
A kind of relevant participant's selection method of time window based on dynamic programming algorithm.
Background technique
In mobile gunz sensing network, microphone, camera, temperature sensor, optical sensor are embedded in smart machine
With the sensors such as positioning, people can use convenient and fast smart machine and collect data, to complete various perception tasks.Entire
In intelligent perception network, including task publisher, task platform and the task participant for carrying smart machine.Task publisher exists
Task platform issues the task of oneself, and pays certain expense to platform, and task platform is in the crowd for participating in perception task
It chooses satisfactory personnel and participates in perception task, while giving certain reward incentive participant, last task platform will be received
The data transmission collected gives task publisher, and perception task terminates.In document topic " MCS data collection
Mechanism for participants ' reputation awareness " author: Yang Jing, Li Pengchen,
Yan Junjie, Chinese Journal of Engineering proposes a kind of participant's letter in 2017,1922-1934
The data collection mechanism of reputation degree perception, and divide and directly transmit and receive and send two class participant of data, dynamic update participates in
The credit worthiness of person reasonably to select task participant.In Documetary Title " CrowdRecruiter:Selecting
Participants for Piggyback Crowdsensing under Probabilistic Coverage
Constraint " author: Zhang Daqiong, Xiong Haoyi, Wang Leye, ACM International Joint
It proposes in Conference on Pervasive and Ubiquitous Computing.2014,703-714 and appoints in satisfaction
On the basis of coverage rate of being engaged in requires, the number of optimum option participant reduces the cost of task.In document topic
《Participant selection for data collection through device-to-device
Communications in mobile sensing " author: Wang Yu, Li Hanshang, Li Ting, et al.,
Personal and Ubiquitous Computing proposes the participant in point-to-point transmission mode in 2017,31-41
Select permeability.
The present invention is directed to the relevant participant's select permeability of time window, proposes a kind of participant's selection method, the party
Method mainly includes two aspects: first is that participant's selection method based on dynamic programming algorithm, target is in covering task time window
Data benefit is maximized on the basis of mouthful.Second is that the credit value update mechanism of participant, the wish of task is executed according to participant
Degree and the quality of data of collection update participant's credit value.
Summary of the invention
The technical problem to be solved by the present invention is
In mobile gunz sensing network, for the relevant participant's select permeability of time window, propose a kind of based on dynamic
The relevant participant's selection method of the time window of planning algorithm.This method is based on dynamic programming algorithm, and target is covering task
Data benefit is maximized while period；And propose participant's credit value update mechanism, the meaning of task is participated according to participant
Hope degree and the quality of data update the credit value of participant.
The technical scheme is that
Using a kind of relevant participant's selection method of time window based on dynamic programming algorithm, system model is defined,
When participating in task according to participant can perception data amount and credit value define data reliability parameter.Data reliability is higher,
Sensing results are better.
Detailed description of the invention
Fig. 1 average data reliability
Fig. 2 cumulative data reliability
Fig. 3 average data benefit
Fig. 4 cumulative data benefit
Fig. 5 average data is spent
Specific embodiment
The present invention is further described below with reference to embodiment.The scope of the present invention proposes in detail in the claims.
1) key parameter is arranged
Experiment carries out experiment simulation using MATLAB, and the length that a time window of task is arranged is 12 hours, and
10 time windows are continuously performed, participant's number of candidates is 100 people, is randomly provided the detecting period that participant reports, and is participated in
Being uniformly distributed on section [1,10] is obeyed in the quotation of person.The equipment electricity of participant obeys being uniformly distributed on [1,100], joins
Being uniformly distributed on [0,1] is obeyed with timeliness, integrality, accuracy and the value of person.
2) the relevant participant's selection method of time window based on dynamic programming algorithm
The data reliability that fully consider participant in participant's selection course first, in each time window
It is all based on dynamic programming algorithm selection current data reliability and high participant, (3) two attached drawing (2), figure data are reliable
Property is with the increased trend chart of task time window number.It can see from figure (2), with the increase of time window, this hair
Bright proposed method has apparent advantage in average data reliability；Display in (3) is schemed, with the increasing of task time window
More, algorithm proposed in this paper is also gradually increased in cumulative reliability.
In terms of data benefit, trust state update mechanism is added in algorithm proposed by the invention, and use dynamic
Planning algorithm, so, the reliability summation that is selected in each time window and quotation and maximum, the final participant of ratio
Data benefit also highest, so in average data cost and minimum.
Claims (4)
1. a kind of relevant participant's selection method of time window based on dynamic programming algorithm, which is characterized in that including following
Step:
(1) height for the perception data quality being capable of providing according to the credit value of participant and participant, determination data can
By property；
(2) suitable participant is screened for each time window goal task, maximizes task data benefit；
(3) credit value more new system is used, so that the confidence level of participant is more quasi-.
2. the relevant participant's selection method of the time window according to claim 1 based on dynamic programming algorithm, special
Sign is, the data reliability in the step (1) the following steps are included:
The height of perception data accuracy rate directly affect perception task as a result, so platform reasonably to select participant to
More reliable perception data is obtained while meeting mission requirements, the reliability of participant is mainly related with two factors, first is that
The confidence level of participant itself, the i.e. credit value of participant, the credit value of participant is higher, and the reliability of perception data is higher；
Second is that the perception data amount that participant is capable of providing, data volume is bigger, and quality data is more, and data reliability is higher；According to
The reliability formula of the above two o'clock, participant is defined as follows:
Wherein,Indicate the reliability of participant, riIndicate the credit value of participant,It indicates to perceive number in the unit time
According to amount.
3. the relevant participant's selection method of the time window according to claim 1 based on dynamic programming algorithm, special
Sign is, obtain data maximizing the benefits in the step (2) the following steps are included:
(3.A) scene set is to have sufficient participant to participate in perception task, and screen to participant；
(3.B) setting mission requirements are that continuous perception task is collected in N number of actual window, it is ensured that each time window internal reference
With the continuous cover time window of detecting period of person；
(3.C) is to realize to maximize data benefit, and define majorized function, formula is as follows:
Wherein,Indicate participant in the quotation of k-th of time window of task.
4. the relevant participant's selection method of the time window according to claim 1 based on dynamic programming algorithm, special
Sign is, credit value more new system in the step (3) the following steps are included:
(4.A) participates in the movement when time scale and participant's k-th of time window of participation of perception task according to participant
Equipment current electric quantityIt defines participant and participates in wish degree, formula is as follows:
(4.B) defines the quality of data, formula is as follows according to four timeliness, integrality, accuracy and value factors:
The calculation method of (4.C) trust state value of feedback is selected according to other in trust state and task in task of participant
What the average trust state of participant compared, trust state and the obtained remuneration of participant are in inverse ratio, and participant obtains report
Reward more high platform collection data cost is higher, is unfavorable for the completion of perception task, trust state at this time is lower, the following institute of formula
Show:
(4.D) after each task time window, platform is according to the trust state value of feedback of participant in this time window
The current credit value of participant is updated, updated credit value will participate in the credit value of next time window as participant,
Formula is as follows:
Wherein,Indicate participant UiParticipate in obtained trust state value of feedback after k-th of time window.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117789955A (en) * | 2024-02-28 | 2024-03-29 | 济南大学 | Medical service distribution and path planning method, system, equipment and medium |
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| CN104657133A (en) * | 2015-01-28 | 2015-05-27 | 南京邮电大学 | Single time window task excitation method for mobile crowd-sourcing perception |
| CN107066322A (en) * | 2017-02-28 | 2017-08-18 | 吉林大学 | A kind of online task allocating method towards self-organizing intelligent perception system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117789955A (en) * | 2024-02-28 | 2024-03-29 | 济南大学 | Medical service distribution and path planning method, system, equipment and medium |
| CN117789955B (en) * | 2024-02-28 | 2024-05-03 | 济南大学 | Medical service distribution and path planning method, system, equipment and medium |
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