CN108269129A - User's motivational techniques in a kind of mobile gunz sensing network based on reverse auction - Google Patents
User's motivational techniques in a kind of mobile gunz sensing network based on reverse auction Download PDFInfo
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Abstract
User's motivational techniques in a kind of mobile gunz sensing network based on reverse auction are claimed in the present invention, and this method encourages the relevant perception activity of user's participant position using reverse auction frame, and consider to exit situation at random in user's perception.The program under the premise of budget is feasible to maximize enthusiasm of the user utility as target raising user's participation perception activity.First, the mark person that wins of method choice user centered on task perceptually task is used to ensure higher task coverage rate.Secondly, according to the task performance for winning mark person, temporally ratio is used to share rule, remuneration payment is carried out to user to ensure the authenticity of excitation.User's motivational techniques in the mobile gunz sensing network based on reverse auction that the present invention is carried, which have, calculates validity, individual rationality, the characteristics such as budget equalization and authenticity.The present invention enables to user to obtain maximum utility, and excitation user participates in task, improves the participation enthusiasm of user.
Description
Technical field
The invention belongs to intelligent perception technical field, more particularly to a kind of mobile gunz sensing network based on reverse auction
Middle user's motivational techniques.
Background technology
Current smart mobile phone has integrated many sensors, such as GPS, accelerometer, gyroscope, microphone, camera,
These sensors can monitor mankind's activity and surrounding enviroment jointly so that people can perceive and obtain whenever and wherever possible surrounding ring
Border information.It perceives using the smart phone user of generally existing and collects large-scale data and have become a kind of novel perception
Mode.Having some projects at present and being based on mobile intelligent perception realizes environmental monitoring, intelligent transportation, behavior monitoring, indoor fixed
Different application in the fields such as position.
The data acquisition of mobile gunz aware application needs the terminal by a large amount of mobile subscribers to carry out data collection, however
Mobile terminal can cause the consumption of the resources such as time, electricity, flow while data collection, in the relevant aware application in position
In, user is while shared own location information, it is also possible to face privacy leakage threat.Under normal circumstances, one it is normal
Rationality user can just go to provide perception or calculate service only under the premise of excitation is returned.Therefore, it is enough in order to recruit
User needs the incentive mechanism of reasonable design, improves the enthusiasm that user participates in perception activity, user is promoted to participate in intelligent perception
Using.
At present, the research of mobile intelligent perception incentive mechanism mainly encourages user's sense of participation by different energisation modes
Know task, energisation mode can be divided mainly into three categories：Amusement game, credit value and remuneration payment.Wherein amusement game and prestige
Value belongs to non-pecuniary energisation mode, and amusement game refers to participate in mobile gunz sense by location-based game stimuli user
Know in task, the research emphasis of such mechanism is to be appropriate to the relevant amusement game in position of perception task by setting come rich
Rich user experience, such as mobile phone games Ostereiersuche, Treasure etc..Credit value refers to that user appoints by performing to perceive
Business obtains certain credit value, and user can therefrom obtain satisfaction (social status etc.), and platform can also be according to the prestige of user
Value chooses the high user of quality and performs perception task.It is social status, the profit of safeguarding itself that such mechanism, which is laid particular emphasis on through user,
Benefit wait and bring participation perception task enthusiasm, to improve the quality of perception data.Such as DWI mechanism, IRONMAN mechanism
Deng.Reddy S and Estrin D et al. points out to take the incentive mechanism of money, the i.e. incentive mechanism based on remuneration payment, often
The interest of user's participation can be more improved than non-pecuniary energisation mode.Reverse auction is as the common remuneration means of payment, not
It is used as basic model in same research work to solve the problems in mobile intelligent perception incentive mechanism.Intelligent perception platform is clothes
Be engaged in requesting party, i.e. buyer, and user is then service provider, i.e. the seller.
However, selfishness and randomness due to people so that the mobile intelligent perception excitation side based on reverse auction model
The design of method faces certain challenge.
The problem of selfishness causes：Most participants are participated in perception task by the payment incentive of intelligent perception platform,
In intelligent perception system, user's income is to influence the principal element that user participates in, i.e. user utility is higher, sense of participation
Know that enthusiasm is higher.At present, for more users is attracted to participate in, researcher proposes many excitation models.For example, Yang
Dejun et al. proposes the excitation model Msensing of customer-centric in the mobicom meetings of 2012, to user
While cost is recompensed, main purpose is to seek optimal user's set to reach the mesh of platform maximization of utility
, and the effectiveness of user is relatively low, user is caused to participate in enthusiasm relatively low.Feng Zhenni et al. propose TRAC mechanism, consider to appoint
Business and the correlation of position selects to pay for the purpose of minimizing platform cost the user of Least-cost as win mark person.Therefore,
At present in the design of mechanism, consideration be more intelligent perception platform maximizing the benefits, this be also participant's enthusiasm not
The reason of high.Platform selects to offer minimum using the competitive relation between participant, pays participant's subset of Least-cost
As win mark person.In this way, the incentive mechanism centered on platform does not pay the utmost attention to the interests of participant, can not more increase
Excitation participant in effect ground adds in perception task.The incentive mechanism of customer-centric is designed, to maximize user utility as target,
Better incentive action can be played.
The problem of randomness causes：The random movement or emergency situations of people causes user to be left during execution task
Place is perceived, task is caused not complete.Lee Juongsik etc. artificially ensure higher while platform payment cost is minimized
Participation rate, using reverse auction mechanism, choose and bid minimum as winner and to pay, while introduce virtual ginseng in participant
With the concept of integration, the participant repeatedly to fail in bidding is avoided to exit participation, compared to the side of regular price stochastic payoffs
Formula proposes that dynamic price and the virtual method for participating in integration ensure that participation rate, and minimize payment cost, but do not fully consider
In the case that winner is dropped by the wayside during the execution task, how it is paid.Zhang Xiang et al. are according to group
The quantity of intelligence aware platform and the difference of user's competitive bidding quantity propose SS-Model (Single-requester respectively
Single-bid), SM-Model (Single-requester Multiple-bid) and MM-Model (Multiple-
Requester Multiple-bid) three kinds of excitation models, wherein SM-Model is the general type of SS-Model, MM-Model
Then consider two kinds of competitive ways of the competition between competition and the multiple users between multiple intelligent perception platforms, but three excitations
Model, which does not fully consider, wins mark person exit perception during execution task with random chance the problem of, and assuming to win mark person can
The perception task won is completed, however, above-mentioned hypothesis is unpractiaca.
Invention content
Present invention seek to address that above problem of the prior art.Propose a kind of mobile intelligent perception based on reverse auction
User's motivational techniques IMRAL (Incentive Method based on ReverseAuction in network
Location-aware Sensing), under reverse auction frame, selfishness and the randomness of user are considered, in gunz
User utility is maximized under the premise of aware platform budget is feasible to improve the enthusiasm of user's participation, and considers that user is performing
How authenticity to ensure excitation is paid to user in the case of being dropped by the wayside during task.The present invention is directed to logical
The win mark person selection method crossed centered on task and temporally ratio share regular method of payment, and excitation user participates in appointing
Business improves the method that user participates in the enthusiasm and task coverage rate perceived.Technical scheme is as follows：
User's motivational techniques in a kind of mobile gunz sensing network based on reverse auction, include the following steps：
Intelligent perception platform issues several perception tasks, several perception tasks form set Γ={ 1,2 ..., m }, m
The number of expression task, each task k ∈ Γ have corresponding attribute, with a quadruple notation<sk,dk,tk,Vk>, wherein sk
Represent job start time, dkExpression task deadline, from job start time to the period of task deadline to appoint
It is engaged in effective time, tkThe time needed for perception task, V are completed for userkThe value of expression task；
If interested user's collection is combined into U={ 1,2 ..., n } to task, n represents to task interested user's number,
Reporting position tasks of the user i according to where itself is bidded to Bi=(Γi,bi), the wherein task subset of reporting of user
biIt bids for user, i.e. user i is ready to provide the reverse auction price of data service；
It is bidded pair according to the task that user submits, intelligent perception platform uses the user choosing method centered on task to select
Select user's subsetIt is covered as the win mark person of task with maximizing task；
It wins mark person and performs perception task, submit perception data to intelligent perception platform；
According to task performance, intelligent perception platform payment piGive win mark person i.
Further, in the step 3), intelligent perception platform selecting can maximize user's subset of task coveringAs the win mark person of task, a kind of win mark person's selection method centered on task is designed, maximizes task coverage rate,
It specifically includes：
31) according to reporting of user situation B=∪i∈UBi, the set of tasks Γ ', each task k of counting user participation competitive bidding
Suitor's set U of ∈ Γ 'kAnd suitor's quantity nk；
32) set of tasks that initialization S=Φ, Γ "=Φ, Γ " expression is covered by win mark person；
33) for each task k ∈ Γ ', step 34) is performed；
If 34) nk=1, then step 35) is performed, if nk＞ 1, then perform step 36)；
35) b is calculatedi/vi, wherein biFor bidding for user i, viThe total value of task is reported for user i, if bi/vi≤ 1,
Then user i is added in and wins executors of the mark collection S as task k：S=S ∪ { i } perform step 37), otherwise perform 33)；
36) to all user i ∈ UkBi/viCarry out ascending sort：b1/v1≤b2/v2≤…≤bL/vL, wherein bL/vLTable
Show bid in all suitors of task k with its report task total value ratio maximum value, b1/v1It is then the institute of task k
If have bid in suitor with its report task total value ratio minimum value b1/v1≤ 1, then the user is added in and win mark
Collect executors of the S as task k, perform step 37), otherwise perform 33)；
37) task k is added in set Γ "：Γ "=Γ " ∪ { k }；
38) it returns and wins mark collection S, the set of tasks Γ ", the b of each task k ∈ Γ " of collection covering are marked by win1/v1And bL/
vL, terminate.
Further, the definition of task covering is：If win mark person's quantity num of task kk>=1, then it represents that the task
It is capped, numk=0 represents the unmanned execution of task, numk=1 representative has a people to perform task, numk>=2 representatives have more than two people
Execution task；
Further, in the step 5), according to the task performance for winning mark person, remuneration payment is carried out to winning mark person,
The critical value method of payment that temporally ratio shares rule is taken to pay user, user when performing a certain task,
Normally complete task and two kinds of possibility dropped by the wayside during execution task, normally complete the probability of task as p, then in
The probability that exits of way is q=1-p, obeys Bernoulli Jacob's distribution, and payment includes user and bids biT is rewarded with taskkTwo parts.
Further, the payment includes user and bids biT is rewarded with taskkTwo parts are as follows：
51) p is initializedi=0；The set of tasks that Γ " '=Φ, Γ " ' expressions are completed by user；
52) for each task k ∈ Γ ", step 53) is performed；
53) T is setkTask for task k is rewarded, and has T if task k is completedk=Vk(bL/vL-b1/v1), Γ " '=
Γ " ' ∪ { k }, otherwiseWherein Δ tkRepresent that user performs the time of task；
54) it calculatesvΓ”'Represent the total value of task completed by win mark person；
55) for each user i ∈ S, step 56) is performed；
56) each remuneration for winning mark person is calculatedWherein x represents the number for the task that user i is performed；
57) it calculatesIf P ＞ vΓ”', then step 58) is performed, is otherwise performed 59)；
58) S=Φ, pi=0；
59) p is returnedi, terminate.
Further, it further includes to four user's average utility, task coverage rate, task completion rate and platform effectiveness aspects
The step of being evaluated.
Further, user's average utility：User's average utility is defined as all win mark person total utilities and is marked with winning
The ratio of person's quantity calculates as follows：Wherein | S | it represents to win mark person's quantity；
Task coverage rate：Task coverage rateWherein cov is represented by all number of tasks for winning and marking user and covering, m
Represent general assignment number；
Task completion rate：Task completion rate γ is defined as the number of tasks com and general assignment number m completed by all win mark persons
The ratio between, it calculates as follows：
Platform effectiveness：Budget feasible important evaluation index when platform effectiveness is assessment motivational techniques, can be according to public affairs
Formula 2 calculates, and is defined as follows：
The utility function of intelligent perception platform is defined as the total value v (s) of being completed by all win mark persons for task and to institute
There is the difference for the total payoff for winning mark person,
It advantages of the present invention and has the beneficial effect that：
Compared with prior art, the present invention the present invention provides in a kind of mobile gunz sensing network based on reverse auction
User's motivational techniques.Consider selfishness and the randomness of user, user's participation is improved as target to maximize user utility
Enthusiasm is perceived, and considers that the user caused by user's randomness exits perception during execution task with random chance
Situation.The user choosing method centered on task is used to maximize task coverage rate first, secondly, is winning mark person with random general
In the case that rate exits perception, temporally ratio is used to share rule and is paid to ensure the true of excitation to winning mark user
Property.It has further the advantage that simultaneously：
It is relatively low to calculate time complexity, the time complexity of the user choosing method in the motivational techniques centered on task
For O (mn2), the time complexity that temporally ratio shares the method for payment of rule is O (mn), and wherein n is number of users, and m is appoints
Business number.It is a complete multinomial time method, the value with practical application.
The motivational techniques are personal financings, i.e. the effectiveness u of user iiNot less than zero.WhenWhen, ui=0；As i ∈ S
When, ui=pi-ci, whereinAnd ci≤bi, Tk>=0, then there is ui≥0.Therefore, which is individual rationality
's.
The motivational techniques are budget equalization for platform, i.e. platform effectiveness u0Not less than zero.When no user is selected in
When winning mark collection, u0=0；When win mark integrates as nonvoid set, v is understood by step 57)Γ”'-P≥0.Therefore the motivational techniques are budgets
Balance.
The motivational techniques are true.According to Myerson, the motivational techniques are illustrated in terms of monotonicity and key value two
Authenticity.
Monotonicity：Due to by bi/viIt is ranked up from small to large, if user i is with biAs mark person is won, when user is with bi'≤
biDuring competitive bidding, due to viConstant, user i, which can equally become, wins mark person.
Key value：Assuming that the number of users for participating in competitive bidding task k is more than or equal to 2, user i is with the b that bidsiAs mark person is won, then
It pays pi=bi+TkIf user i is to be more than piValue as competitive bidding valency, then bi＞ bi+Tk, then Tk＜ 0, becauseB can be obtainedL/vL＜ b1/v1, then user i cannot win task k, if therefore
User is to be more than piValue as competitive bidding valency will not become win mark person.
Therefore, which meets authenticity, and authenticity is for preventing corner on the market from playing an important roll.
Description of the drawings
Fig. 1 is the execution flow that the present invention provides preferred embodiment intelligent perception platform and the exchange method of user；
Fig. 2 is the execution flow of user's selection algorithm centered on task；
Fig. 3 is the execution flow that temporally ratio shares regular compensation methods；
Fig. 4 is user's average utility comparison diagram；
Fig. 5 is the comparison diagram of perception task coverage rate；
Fig. 6 is the comparison diagram of perception task completion rate；
Fig. 7 is intelligent perception platform effectiveness comparison diagram.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, detailed
Carefully describe.Described embodiment is only the part of the embodiment of the present invention.
The present invention solve above-mentioned technical problem technical solution be：A kind of mobile gunz sensing network based on reverse auction
In user's motivational techniques, the method includes：Mobile gunz aware platform and the exchange method of user, step are as follows：
1) publication of intelligent perception platform perception task set Γ={ 1,2 ..., m }, each task k ∈ Γ have its correspondence
Attribute, with a quadruple notation<sk,dk,tk,Vk>.Wherein skWith dkWhen representing that job start time ends with task respectively
Between, it is task effective time from job start time to the period of task deadline.tkPerception task institute is completed for user
The time needed, value are not more than the effective time of task.VkThe value of expression task is the private information of platform, and perceives
Task is related to position, i.e., each task is required for complete in specific place.
2) it sets interested user's collection to task and is combined into U={ 1,2 ..., n }, reporting positions of the user i according to where itself
Task is bidded to Bi=(Γi,bi), the wherein task subset of reporting of userbiIt bids for user, i.e., user i is ready to carry
For the reverse auction price of data service.
3) being submitted according to user for task is bidded pair, and intelligent perception platform selecting can maximize user's subset of task coveringWin mark person as task.
4) it wins mark person and performs perception task, submit perception data to intelligent perception platform.
5) according to task performance, intelligent perception platform payment piGive win mark person i.
User participates in the cost of the task energy loss as caused by providing and service, network bandwidth resources consumption and potential hidden
The factors such as private threat determine.The cost that user i participates in perception task is ci(ci≤bi), the private information for user.
User's i utility functions are defined as follows：
piThe remuneration for winning mark person i is paid for platform.
The utility function of intelligent perception platform is defined as the total value v (s) of being completed by all win mark persons for task and to institute
There is the difference for the total payoff for winning mark person, be defined as follows：
The present invention is directed to preferentially be maximized under the premise of platform budget is feasible by user's selection and compensation methods
User utility, excitation user participate in, and improve user and participate in perceiving enthusiasm, are represented by：
Target：Condition：
Wherein B represents the spending budget of platform, it is assumed that its task budget B is no more than by the task of all win mark persons completions
Total value v (s).One feasible effective motivational techniques needs to meet：
It calculates effective：Calculating effectively refers to that its operation result can export in polynomial time.
Individual rationality：The effectiveness of each user is non-negative.
Budget equalization：The effectiveness of intelligent perception platform is nonnegative value, i.e., its total payoff is no more than the task that win mark collection is completed
Total value.
Authenticity：Authenticity refers to, no matter in the case of the bidding of other suitors, for any user, with it
Bona fide cost competitive bidding is dominant strategy, i.e. user cannot obtain more effectiveness from the value of bidding of the true valuation of deviation task.
First three characteristic is the primary condition for ensureing that auction is feasible, and authenticity can eliminate worry of the user to market dominance,
Myerson et al. proves that an auction mechanism is really to must satisfy that selection rule is dull and the reward value of win mark person is
Two conditions of key value.If monotonicity is user with the b that bidsjAs win mark person, then with bj' ＜ bjIt remains to become and wins mark person.
Key value is referred to if competitive bidding valency bjHigher than remuneration pj, then it, which will not become, wins mark person.
The realization of user's motivational techniques in mobile gunz sensing network proposed by the present invention based on reverse auction is related to
User's select permeability and remuneration payment problem.
In step 3), a kind of user choosing method centered on task is designed, returns and wins mark person set S, is maximized
Task coverage rate.First, it was demonstrated that the user's select permeability for meeting maximization task coverage rate is NP hardly possiblies, secondly, with reference to perception
There are diminishing marginal utilities for the collection of data, design a kind of effective user choosing method of low computation complexity, i.e., with task
Centered on user choosing method.
Define 1 (task covering)：If win mark person's quantity num of task kk>=1, then it represents that the task is capped, numk=0
Represent the unmanned execution of task, numk=1 representative has a people to perform task, numk>=2 representatives, which have, more than two people performs task.
Theorem 1：User's select permeability is NP hardly possiblies.
It proves：Weight multitask collection covering problem (weightedmultiple set coverproblem, WMSCP)
Np hard problem is proved by Yang Jian et al..And weight multitask covering problem can in linear session reduction to user
Select permeability.Therefore, user's select permeability is NP hardly possiblies.
When participating in the quantity increase of user of same perception task, the diminishing marginal utility caused by data redundancy can be cured
Hair is serious.For example, when several mobile phones acquire the noise in some region simultaneously, the data of one or two mobile phone acquisition are enough to estimate
Go out the noise level in the region, more mobile phones is allowed, which to be acquired, can not effectively improve the accurate of the noise that estimates
Degree, can increase data redundancy and social cost instead.Perception task value is certain, and the user for participating in same task is more, often
It is fewer that a user can be obtained remuneration.Therefore, it to improve user utility and task coverage rate, in user's choice phase, proposes
Win mark person's selection algorithm centered on task, with the principle that any one task is performed by a people, selection is bidded low and is reported
The big user of task total value perform perception task, improve user utility, user promoted to participate in.
In step 3), a kind of user choosing method centered on task is designed, returns and wins mark person set S, is maximized
Task coverage rate.First, it was demonstrated that the user's select permeability for meeting maximization task coverage rate is NP hardly possiblies, secondly, with reference to perception
There are diminishing marginal utilities for the collection of data, design a kind of effective user choosing method of low computation complexity, i.e., with task
Centered on user choosing method.The execution flow of user's selection algorithm centered on task is as shown in Fig. 2, step is as follows：
31) according to reporting of user situation B=∪i∈UBi, the set of tasks Γ ', each task k of counting user participation competitive bidding
Suitor's set U of ∈ Γ 'kAnd suitor's quantity nk；
32) set of tasks that initialization S=Φ, Γ "=Φ, Γ " expression is covered by win mark person；
33) for each task k ∈ Γ ', step 34) is performed；
If 34) nk=1, then step 35) is performed, if nk＞ 1, then perform step 36)；
35) b is calculatedi/vi, wherein biFor bidding for user i, viThe total value of task is reported for user i, if bi/vi≤ 1,
Then user i is added in and wins executors of the mark collection S as task k：S=S ∪ { i } perform step 37), otherwise perform 33)；
36) to all user i ∈ UkBi/viCarry out ascending sort：b1/v1≤b2/v2≤…≤bL/vLIf b1/v1≤ 1,
Then the user is added in and wins executors of the mark collection S as task k, step 37) is performed, otherwise performs 33)；
37) task k is added in set Γ "：Γ "=Γ " ∪ { k }；
38) it returns and wins mark collection S, the set of tasks Γ ", the b of each task k ∈ Γ " of collection covering are marked by win1/v1And bL/
vL, terminate.
In step 5), according to the task performance for winning mark person, remuneration payment is carried out to winning mark person.To ensure excitation side
The authenticity of method, at the same consider in user's perception it is random exit situation, take temporally ratio share the critical of rule
Value method of payment pays user.User only normally completes task and in the task of execution when performing a certain task
Two kinds of possibility are dropped by the wayside in the process, and the probability for normally completing task is p, then the probability dropped by the wayside is q=1-p, obeys primary
Nu Li is distributed.Payment includes user and bids biT is rewarded with taskkTwo parts are as follows：
51) p is initializedi=0；The set of tasks that Γ " '=Φ, Γ " ' expressions are completed by user；
52) for each task k ∈ Γ ", step 53) is performed；
53) T is setkTask for task k is rewarded, and has T if task k is completedk=Vk(bL/vL-b1/v1), Γ " '=
Γ " ' ∪ { k }, otherwiseWherein Δ tkRepresent that user performs the time of task；
54) it calculatesvΓ”'Represent the total value of task completed by win mark person；
55) for each user i ∈ S, step 56) is performed；
56) each remuneration for winning mark person is calculatedWherein x represents the number for the task that user i is performed；
57) it calculatesIf P ＞ vΓ”', then step 58) is performed, is otherwise performed 59)；
58) S=Φ, pi=0；
59) p is returnedi, terminate.
To illustrate the feasibility and validity of the motivational techniques, study under same experimental conditions, what this illustrated to propose swashs
Encourage method IMRAL and TRAC (truthful auction for location-aware collaborative sensing
In mobile crowdsourcing) and IMC-SS (incentive mechanism for crowdsourcing in the
Single-requester single-bid-model) in user's average utility, task coverage rate, task completion rate and platform
The performance of four aspects of effectiveness.
User's average utility：User's average utility is defined as ratio of all win mark person total utilities with winning mark person's quantity,
It calculates as follows：Wherein | S | it represents to win mark person's quantity.
Task coverage rate：Task coverage rateWherein cov is represented by all number of tasks for winning and marking user and covering, m
Represent general assignment number.
Task completion rate：Task completion rate γ is defined as the number of tasks com and general assignment number m completed by all win mark persons
The ratio between, it calculates as follows：
Platform effectiveness：Budget feasible important evaluation index when platform effectiveness is assessment motivational techniques, can be according to public affairs
Formula 2 is calculated.
Relevant parameter is initialized first, and assumes that the probability that user exits perception during execution task is 0.2, if
User exits perception task k, it assumes that its Δ tk/tkIt obeys and is uniformly distributed between 0 to 1, and at most allow appointing for reporting of user
Business number is 5.Design parameter setting is as shown in table 1.
1 experiment parameter of table is set
Since most participants by the payment incentive of intelligent perception platform are participated in perception task, then in intelligent perception system
User's income is to influence the key factor that user participates in system, and user utility is higher, participates in the enthusiasm of perception task
It is higher.On the other hand, the enthusiasm of user is higher, and the received possibility of task is bigger, that is, task coverage rate is higher,
Task coverage rate is also related with the factors such as user choosing method and compensation methods simultaneously.Consequently, to facilitate comparing, can pass through
User's average utility and the two indexs of task coverage rate illustrate that user participates in the enthusiasm of perception task.
User's average utility is as shown in Figure 4.Fig. 4 shows this motivational techniques IMRAL and TRAC, IMC-SS for illustrating to propose
User's average utility comparison.For TRAC and IMC-SS, the remuneration payment of TRAC mechanism and IMC-SS mechanism only with
Its bid it is related to number of tasks, due to this illustrate propose motivational techniques in task payment TkAccumulative action, user can obtain
Relatively high task compensation, improves the wish degree that user participates in perception task.Fig. 5 shows lower of three kinds of motivational techniques
The situation for coverage rate of being engaged in.It can be seen from the figure that the task coverage rate under IMC-SS is slightly below the task covering under IMRAL
Rate.With reference to user utility and task coverage condition, synthesis can obtain, and compared to TRAC and IMC-SS mechanism, user's is positive under IMRAL
Property is higher.
As shown in fig. 6, Fig. 6 is the comparison diagram of perception task completion rate.Two kinds of mechanism of TRAC and IMC-SS assume task
Covering is that task is completed, therefore its task completion rate is identical with its task coverage rate variation tendency, and IMRAL is considered because user's
Randomness causes user to be dropped by the wayside during execution task, the situation that perception task is caused not to be completed.Thus it can see
Go out, the randomness of user will reduce perception task completion rate.
Fig. 7 is the comparison diagram of intelligent perception platform effectiveness.As can be seen that certain in number of users from Fig. 7 (a), with appointing
It is engaged in the increase of number, the platform effectiveness under IMRAL and IMC-SS increases, also, compared to IMC-SS, and IMRAL platform effectiveness is relatively low.
In Fig. 7 (b), the platform effectiveness of three kinds of motivational techniques tends towards stability afterwards first to increase, and is due to the growth of number of users, appointing
Completion rate of being engaged in increases, and after task-set saturation, platform effectiveness is not further added by.It can thus be seen that the randomness of user will reduce group
The effectiveness of intelligence aware platform.
For the researcher of this field, it is clear that the present invention is not limited to the details of above-mentioned exemplary embodiment, Er Qie
In the case of without departing substantially from spirit or essential attributes of the invention, researcher can make various changes or modifications the present invention, this
A little equivalence changes and modification equally fall into the scope of the claims in the present invention.
The above embodiment is interpreted as being merely to illustrate the present invention rather than limit the scope of the invention.
After the content for having read the record of the present invention, technical staff can make various changes or modifications the present invention, these equivalent changes
Change and modification equally falls into the scope of the claims in the present invention.
Claims (7)
1. user's motivational techniques in a kind of mobile gunz sensing network based on reverse auction, which is characterized in that including following step
Suddenly：
1) intelligent perception platform issues several perception tasks, several perception tasks form set Γ={ 1,2 ..., m }, m tables
Show the number of task, each task k ∈ Γ have corresponding attribute, with a quadruple notation<sk,dk,tk,Vk>, wherein skTable
Show job start time, dkExpression task deadline is task from job start time to the period of task deadline
Effective time, tkThe time needed for perception task, V are completed for userkThe value of expression task；
2) it sets interested user's collection to task and is combined into U={ 1,2 ..., n }, n represents to task interested user's number, uses
Reporting position tasks of the family i according to where itself is bidded to Bi=(Γi,bi), the wherein task subset of reporting of userbi
It bids for user, i.e. user i is ready to provide the reverse auction price of data service；
3) being submitted according to user for task is bidded pair, and intelligent perception platform uses the user choosing method centered on task to select
User's subsetIt is covered as the win mark person of task with maximizing task；
4) it wins mark person and performs perception task, submit perception data to intelligent perception platform；
5) according to task performance, intelligent perception platform payment piGive win mark person i.
2. user's motivational techniques in the mobile gunz sensing network according to claim 1 based on reverse auction, feature
It is, in the step 3), intelligent perception platform selecting can maximize user's subset of task coveringAs task
Mark person is won, designs a kind of win mark person's selection method centered on task, task coverage rate is maximized, specifically includes：
31) according to reporting of user situation B=∪i∈UBi, the set of tasks Γ ', each task k ∈ Γ ' of counting user participation competitive bidding
Suitor's set UkAnd suitor's quantity nk；
32) set of tasks that initialization S=Φ, Γ "=Φ, Γ " expression is covered by win mark person；
33) for each task k ∈ Γ ', step 34) is performed；
If 34) nk=1, then step 35) is performed, if nk＞ 1, then perform step 36)；
35) b is calculatedi/vi, wherein biFor bidding for user i, viThe total value of task is reported for user i, if bi/vi≤ 1, then will
User i adds in the executor for winning mark collection S as task k：S=S ∪ { i } perform step 37), otherwise perform 33)；
36) to all user i ∈ UkBi/viCarry out ascending sort：b1/v1≤b2/v2≤…≤bL/vL, wherein bL/vLIt represents to appoint
Be engaged in k all suitors in bid with its report task total value ratio maximum value, b1/v1It is then all competing of task k
Bid in mark person with its report task total value ratio minimum value, if b1/v1≤ 1, then the user is added in and win mark collection S
As the executor of task k, step 37) is performed, is otherwise performed 33)；
37) task k is added in set Γ "：Γ "=Γ " ∪ { k }；
38) it returns and wins mark collection S, the set of tasks Γ ", the b of each task k ∈ Γ " of collection covering are marked by win1/v1And bL/vL, knot
Beam.
3. user's motivational techniques in the mobile gunz sensing network according to claim 2 based on reverse auction, feature
It is, the definition of the task covering is：If win mark person's quantity num of task kk>=1, then it represents that the task is capped, numk=
0 represents the unmanned execution of task, numk=1 representative has a people to perform task, numk>=2 representatives, which have, more than two people performs task.
4. user's motivational techniques in the mobile gunz sensing network based on reverse auction according to one of claim 1-3,
It is characterized in that, in the step 5), according to the task performance for winning mark person, remuneration payment is carried out to winning mark person, take by
The critical value method of payment that time scale shares rule pays user, and user is when performing a certain task, only normally
Completion task and two kinds of possibility are dropped by the wayside during execution task, the probability for normally completing task is p, then drops by the wayside
Probability for q=1-p, obey Bernoulli Jacob's distribution, payment includes user and bids biT is rewarded with taskkTwo parts.
5. user's motivational techniques in the mobile gunz sensing network according to claim 4 based on reverse auction, feature
It is, the payment includes user and bids biT is rewarded with taskkTwo parts are as follows：
51) p is initializedi=0；The set of tasks that Γ " '=Φ, Γ " ' expressions are completed by user；
52) for each task k ∈ Γ ", step 53) is performed；
53) T is setkTask for task k is rewarded, and has T if task k is completedk=Vk(bL/vL-b1/v1), Γ " '=Γ " ' ∪
{ k }, otherwiseWherein Δ tkRepresent that user performs the time of task；
54) it calculatesvΓ”'Represent the total value of task completed by win mark person；
55) for each user i ∈ S, step 56) is performed；
56) each remuneration for winning mark person is calculatedWherein x represents the number for the task that user i is performed；
57) it calculatesIf P ＞ vΓ”', then step 58) is performed, is otherwise performed 59)；
58) S=Φ, pi=0；
59) p is returnedi, terminate.
6. user's motivational techniques in the mobile gunz sensing network according to claim 1 based on reverse auction, feature
It is, further includes the step evaluated four user's average utility, task coverage rate, task completion rate and platform effectiveness aspects
Suddenly.
7. user's motivational techniques in the mobile gunz sensing network according to claim 6 based on reverse auction, feature
It is, user's average utility：User's average utility is defined as ratio of all win mark person total utilities with winning mark person's quantity,
It calculates as follows：Wherein | S | it represents to win mark person's quantity；
Task coverage rate：Task coverage rateWherein cov represents that, by all number of tasks for winning and marking user and covering, m is represented
General assignment number；
Task completion rate：Task completion rate γ be defined as the number of tasks com and general assignment number m completed by all win mark persons it
Than calculating as follows：
Platform effectiveness：Budget feasible important evaluation index when platform effectiveness is assessment motivational techniques, can count according to formula 2
It calculates, is defined as follows：
The utility function of intelligent perception platform is defined as the total value v (s) of being completed by all win mark persons for task and to all win
The difference of the total payoff of mark person,
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