CN103310349A - On-line incentive mechanism based perceptual data acquisition method - Google Patents
On-line incentive mechanism based perceptual data acquisition method Download PDFInfo
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Abstract
The invention discloses an on-line incentive mechanism based perceptual data acquisition method. The method includes the steps that S1, a perceptual system sends perceptual tasks to mobile phone users in a target perceptual area; S2, if the mobile phone users are interested in the received perceptual tasks, the mobile phone users submit competitive bidding schemes to the perceptual system according to efficiency functions of the mobile phone users; S3, the perceptual system decides whether to adopt the competitive bidding schemes or not by utilizing an on-line incentive mechanism based on an efficiency function of the perceptual system according to the received competitive bidding schemes, distributes remuneration to the mobile phone users if so, and refuses to distribute remuneration to the mobile phone users otherwise; S4, the mobile phone users receive adopted decisions of the perceptual system, execute the perceptual tasks and send perceptual data to the perceptual system. The on-line incentive mechanism implementation method has the advantages of timeliness and practicality, cannot be controlled by markets and makes the perceptual system and the users all satisfied.
Description
Technical field
The present invention relates to gunz perception field, particularly a kind of perception data acquisition methods based on online incentive mechanism.
Background technology
In recent years, the smart mobile phone increased popularity that becomes, according to the internationally famous IDC of data statistics company statistics, the sales volume of smart mobile phone in 2012 has reached 700,000,000 multi-sections, and the sales volume than 2011 has increased by 44.1%.On the other hand, the embedded sensors on the smart mobile phone also becomes increasingly abundant, so that smart mobile phone on the basis of the calculating that improves constantly and communication capacity, has increased the ability of the perception environment of various dimensions.These conditions have attracted a lot of researchists' concern, the smart mobile phone that they are devoted to utilize domestic consumer to carry is finished various large-scale mobile perception tasks, gather the data of specific region or application-specific by the mobile phone sensor, such as environmental monitoring, road traffic monitoring etc.These extensive perception tasks often need a large amount of cellphone subscriber to participate in, and utilize mobile phone to record various aspects with their life of perception, work and amusement, generate abundant perception information, comprise picture, sound, mobile message, positional information etc.Sensory perceptual system can provide information inquiry miscellaneous and service by merging a large amount of perception information that excavates these various dimensions.
The mobile phone resources that the user of participation perception task need to consume them, such as battery and computing power, in addition, the user share they with the perception data of positional information the time, even also to expose some their personal information, these information can be brought the problem of potential privacy exposure to them.Therefore common cellphone subscriber is not obtaining of equal valuely, can make in the situation of its satisfied excitation and repayment, and be to be difficult to the mobile perception task of aggressive participation.Yet, the perception task success or not largely depends on the number of users that participates in perception, some perception task then necessarily requires number of users to surpass certain critical value, large quantity research is before mainly paid close attention to the Design and implementation of various perception tasks, only has a small amount of research work to explore and how effectively encourages domestic consumer to participate in perception task.There is not the user of sufficient amount to participate in, mobile perception task just can't well be finished, follow-up service is not then known where to begin more, so incentive mechanism becomes the key point that promotes gunz perception task widespread deployment, designs the good incentive mechanism of a property and becomes very urgent.
Summary of the invention
The technical matters that (one) will solve
The technical problem to be solved in the present invention is: how a kind of perception data acquisition methods based on online incentive mechanism is provided, and the cellphone subscriber participates in the gunz perception task with excitation, thereby the perception data that obtains sufficient amount is finished large-scale gunz perception task.
(2) technical scheme
In order to solve the problems of the technologies described above, the invention provides a kind of perception data acquisition methods based on online incentive mechanism, described method comprises the steps:
S1: sensory perceptual system sends to perception task the cellphone subscriber in target perception zone;
S2: if described cellphone subscriber is interested in receiving described perception task, according to described cellphone subscriber's Efficiency Function, submit a competitive bidding scheme to described sensory perceptual system, described competitive bidding scheme comprises bidding price and perception plan; Otherwise, then ignore described perception task;
S3: described sensory perceptual system utilizes the online incentive mechanism based on the Efficiency Function of described sensory perceptual system according to the described competitive bidding scheme that receives, and determines whether adopt described competitive bidding scheme, if so, metes out rewards then for described cellphone subscriber; Otherwise, then refuse to mete out rewards to described intelligence cellphone subscriber;
S4: described cellphone subscriber receives the decision that described sensory perceptual system is adopted, and then carries out described perception task, and perception data is sent to described sensory perceptual system.
Preferably, described bidding price refers to that described user is ready to participate in the needed minimum price of described perception task.
Preferably, the described cellphone subscriber's of step S2 Efficiency Function is calculated as follows:
Wherein, c
iTrue cost for user i; p
iPay the remuneration of the user i that is employed for sensory perceptual system; u
iEfficiency Function for user i; The user set of T for being employed.
Preferably, the Efficiency Function of the described sensory perceptual system of step S3 is calculated as follows:
Wherein, the user set of T for being employed, v (T)=∑
I ∈ Tv
i, v
iFor by the user i that the employed value to sensory perceptual system, υ (T) is the user that the employed value to sensory perceptual system; P (T)=∑
I ∈ Tp
i, p
iPay the remuneration of the user i that is employed for sensory perceptual system, P(T) pay the total remuneration of user that all are employed for sensory perceptual system; The logarithmic function item
React sensory perceptual system and employed cellphone subscriber's the edge usefulness of successively decreasing; Parameter lambda is used for controlling the gradient that edge usefulness is successively decreased.
Preferably, described online incentive mechanism is based on the auction mechanism of threshold value or based on the real online incentive mechanism of bidding.
Preferably, the method for described auction mechanism based on threshold value comprises the steps:
S311: employed cellphone subscriber's set T to be set to 0, obtain at random k sampled value according to binomial distribution B (n, 1/2);
S312: according to the competitive bidding scheme of front k candidate cellphone subscriber submission, utilize the inferior mould character of the Efficiency Function of described sensory perceptual system, calculate optimal edge gain of performance vector δ=SubmodMaxCardinality (Q, the m of described sensory perceptual system, and user's sequence i=k+1 is set u);
S313: if i＜n and | T|＜m then enters step S314; Otherwise, finish;
S314: if u
i(T) 〉=δ
| T|+1/ τ, then described sensory perceptual system determines to employ user i, user i is added among the set T that is employed the cellphone subscriber, and prop up the bidding price b that pays user i to user i
iThe remuneration p that equates number
iOtherwise refusal is employed user i;
S315: make i=i+1, return step S313;
Wherein, n is potential user's sum; M is for employing total number of users; K is cutoff value, utilizes edge usefulness threshold value to determine whether employ after k; δ is optimal edge gain of performance vector;
Q={b
1, b
2..., b
kBe that a front k candidate's cellphone subscriber submits the bidding price set to described sensory perceptual system; U is the Efficiency Function of described sensory perceptual system; u
i(T) user i is added to employed the cellphone subscriber to gather after the T, the edge gain of performance that described sensory perceptual system obtains; δ
| T|+1/ τ be the degree of approximation be τ edge usefulness threshold vector | the T|+1 item.
Preferably, described method based on the real online incentive mechanism of bidding comprises the steps:
S321: employed cellphone subscriber's set T to be set to 0,
With
Obtain at random k sampled value according to binomial distribution B (n, 1/2);
S322: according to the statistic of the bidding price of a front r candidate user, calculate described sensory perceptual system standardized payment, i.e. price thresholds threshold=CalThreshold (Q), and i=r+1 is set;
S323: if i＜k and | T＜| l then enters step S324; Otherwise, then enter step S326;
S324: if user's bidding price b
i＜threshold and threshold≤u
i(T)+b
i, then described sensory perceptual system determines to employ user i, and props up the remuneration p that pays the equal number of price thresholds threshold to user i
iOtherwise refusal is employed user i;
S325: make i=i+1, return step S323;
S326: according to a front k cellphone subscriber's competitive bidding scheme, utilize the inferior mould character of the Efficiency Function of described sensory perceptual system, calculate the optimal edge gain of performance vector of described sensory perceptual system, be δ=Submod MaxCardinality (U (1:k), m, and j=m-|T| is set, index=1 u);
S327: if j＜n and | T|＜m then enters step S328; Otherwise, finish;
S328: if user's bidding price b
j≤ threshold and
, then described sensory perceptual system determines to employ user j, and props up the remuneration P that the standard metering threshold value threshold that pays paying equates number to user j
j, and make index=index+1; Otherwise refusal is employed user j;
S329: make j=j+1, return step S327;
Wherein, n is potential user's sum; L is the predetermined number of users of employing; M is for employing total number of users; α is balance parameters; R is cutoff value, utilizes price thresholds to determine whether employ between r and k; K is cutoff value, utilizes price thresholds and edge usefulness threshold value to determine whether employ after k; δ is optimal edge gain of performance vector; J=m-|T| will be employed the number of users sequence behind the cutoff value k;
Q={b
1, b
2..., b
rBe that a front r candidate's cellphone subscriber is to the bidding price set of described sensory perceptual system submission; U is the Efficiency Function of described sensory perceptual system; u
j(T) user j is added to employ after the user gathers the edge gain of performance that described sensory perceptual system obtains; Index is index optimal edge gain vector δ;
The expression degree of approximation is the index item of the edge usefulness threshold vector of τ.
Preferably, described price thresholds is the average of bidding price or the intermediate value of bidding price.
(3) beneficial effect
A kind of perception data acquisition methods based on online incentive mechanism provided by the present invention has the following advantages:
One, the form by online competitive bidding, allow the user can demarcate the bidding price of own mobile phone resources, require corresponding remuneration to sensory perceptual system, the user can not obtain negative usefulness when finishing perception task, can effectively encourage the user to participate in having satisfied individual reason in the mobile perception task positively; Two, sensory perceptual system is when the competitive bidding that receives each user, by optimal edge gain of performance threshold value, immediately make optimizing decision, determine whether to accept user's quotation, sensory perceptual system can not obtain negative usefulness when finishing perception task, satisfied the benefit of sensory perceptual system and calculated high efficiency; Three, by price thresholds, safeguard the user of minimum bidding price, make the user of competitive bidding improve the usefulness of its acquisition with the inconsistent bidding price of its true value by submitting one to, satisfied the authenticity of bidding of incentive mechanism.
Description of drawings
Fig. 1 is the process flow diagram of the online incentive mechanism implementation method of a kind of gunz perception of the present invention;
Fig. 2 is the method flow diagram based on the auction mechanism of threshold value among the present invention;
Fig. 3 is the method flow diagram based on the real online incentive mechanism of bidding among the present invention;
Fig. 4 is sensory perceptual system of the present invention and user interactions figure;
Fig. 5 is that systematic parameter α is on the impact of sensory perceptual system usefulness;
Fig. 6 is that potential user's sum n is on the impact of sensory perceptual system usefulness;
Fig. 7 employs total number of users m on the impact of usefulness;
Fig. 8 is that parameter lambda is on the impact of usefulness;
Fig. 9 is that parameter τ is on the impact of algorithm approximation;
Figure 10 is that parameter τ is on successfully employing the impact of number of users;
Figure 11 is the authenticity of bidding based on the real online incentive mechanism of bidding.
Embodiment
Below in conjunction with Figure of description and embodiment, the specific embodiment of the present invention is described in further detail.Following examples only are used for explanation the present invention, but are not used for limiting the scope of the invention.
Embodiment one:
As shown in Figure 1, the present embodiment has been put down in writing a kind of perception data acquisition methods based on online incentive mechanism, and described method comprises the steps:
S1: sensory perceptual system sends to perception task the cellphone subscriber in target perception zone;
S2: if described cellphone subscriber is interested in receiving described perception task, according to described cellphone subscriber's Efficiency Function, submit a competitive bidding scheme to described sensory perceptual system, described competitive bidding scheme comprises bidding price and perception plan; Otherwise, then ignore described perception task;
S3: described sensory perceptual system utilizes the online incentive mechanism based on the Efficiency Function of described sensory perceptual system according to the described competitive bidding scheme that receives, and determines whether adopt described competitive bidding scheme, if so, metes out rewards then for described cellphone subscriber; Otherwise, then refuse to mete out rewards to described intelligence cellphone subscriber;
S4: described cellphone subscriber receives the decision that described sensory perceptual system is adopted, and then carries out described perception task, and perception data is sent to described sensory perceptual system.
Target perception zone refers to the interested zone of system, if this zone has the user to enter, then system can send to it description of perception task.
Bidding price refers to that described user is ready to participate in the needed minimum price of described perception task, and this price is relevant with the perception plan that the user formulates.The perception plan then depends on specific application scenarios, such as, a perception plan can be described the duration that the user participates in perception task, perhaps describes the user and is ready to participate in what perception tasks.
Cellphone subscriber's Efficiency Function is calculated as follows:
Wherein, c
iTrue cost for user i; p
iPay the remuneration of the user i that is employed for sensory perceptual system; u
iEfficiency Function for user i; The user set of T for being employed.
The Efficiency Function of sensory perceptual system is calculated as follows:
Wherein, the user set of T for being employed, v (T)=∑
I ∈ Tv
i, v
iFor by the user i that the employed value to sensory perceptual system, υ (T) is the user that the employed value to sensory perceptual system; P (T)=∑
I ∈ Tp
i, p
iPay the remuneration of the user i that is employed for sensory perceptual system, P(T) pay the total remuneration of user that all are employed for sensory perceptual system; The logarithmic function item
React sensory perceptual system and employed cellphone subscriber's the edge usefulness of successively decreasing; Parameter lambda is used for controlling the gradient that edge usefulness is successively decreased.
The Efficiency Function u of sensory perceptual system has the character of inferior mould, the approximate data that this character can facilitate for maximizing Efficiency Function.
The target of incentive mechanism is that system platform and user are satisfied with, and it can react by Efficiency Function.Sensory perceptual system and user need to obtain their maximum efficiency, angle from sensory perceptual system, user's perception plan and corresponding bidding price are its input parameters that calculates usefulness, usefulness by evaluates calculation can obtain from the specific user there decides its competitive bidding of whether accepting this user and paying; And from user's angle, they also can evaluates calculation its participate in the obtainable usefulness of perception task and determine whether to the system platform competitive bidding.
Because it is arbitrarily that the user enters into the time in target perception zone, online incentive mechanism is made and is needed instant, online decision-making, more can adapt to the demand of practical application.
Online incentive mechanism comprises based on the auction mechanism of threshold value with based on the real online incentive mechanism of bidding.
As shown in Figure 4, sensory perceptual system and the user interactions figure of the present embodiment have been put down in writing; Describe interaction flow complete between sensory perceptual system platform and the common smart phone user, comprised the result of three kinds of typical platforms and user interactions.
Embodiment two:
As shown in Figure 2, the present embodiment has been put down in writing a kind of method of the auction mechanism based on threshold value, comprises the steps:
S311: employed cellphone subscriber's set T to be set to 0, obtain at random k sampled value according to binomial distribution B (n, 1/2);
S312: according to the competitive bidding scheme of front k candidate cellphone subscriber submission, utilize the inferior mould character of the Efficiency Function of described sensory perceptual system, calculate the optimal edge gain of performance vector δ of described sensory perceptual system=Submod MaxCardinality (Q, m, and user's sequence i=k+1 is set u);
S313: if i＜n and | T|＜m then enters step S314; Otherwise, finish;
S314: if u
i(T) 〉=δ
| T|+1/ τ, then described sensory perceptual system determines to employ user i, user i is added among the set T that is employed the cellphone subscriber, and prop up the bidding price b that pays user i to user i
iThe remuneration p that equates number
iOtherwise refusal is employed user i;
S315: make i=i+1, return step S313;
Wherein, n is potential user's sum; M is for employing total number of users; K is cutoff value, utilizes edge usefulness threshold value to determine whether employ after k; δ is optimal edge gain of performance vector;
Q={b
1, b
2..., b
kBe that a front k candidate's cellphone subscriber submits the bidding price set to described sensory perceptual system; U is the Efficiency Function of described sensory perceptual system; u
i(T) user i is added to employed the cellphone subscriber to gather after the T, the edge gain of performance that described sensory perceptual system obtains; δ
| T|+1/ τ be the degree of approximation be τ edge usefulness threshold vector | the T|+1 item.
Edge gain refers to recruit after the user for system, the gain of the usefulness that can bring to system.The edge gain vector refers to for system recruits after a plurality of users the class value that the gain of performance that each user brings to system successively forms.The optimal edge gain vector, namely by after investigating the recruitment order of calculating one group of user, edge gain vector corresponding to the obtainable maximum whole effect gain of system.
Based on being contemplated that of the auction mechanism of threshold value:
At first, estimate to select m user's optimum efficiency value.Submit to the candidate cellphone subscriber's of competitive bidding scheme information to carry out submodular function optimization computation under the travel line to sensory perceptual system front k, obtain optimal edge gain of performance vector δ=Sub mod MaxCardinality (Q, m, u).
Then, this vector δ is used to make up a degree of approximation edge usefulness threshold vector that is τ.
At last, next submitting among the user of competitive bidding scheme to sensory perceptual system, surpassing respective threshold as long as observe user's edge usefulness, then system can employ this user, and Xiang Qizhi pays the remuneration that bidding price equates number.Till will lasting till that based on the selection user's of threshold value process the sensory perceptual system system has employed the user of predetermined number.
Auction mechanism based on threshold value has the high efficiency of calculating, individual reason and sensory perceptual system benefit property, has guaranteed the availability based on the auction mechanism of threshold value.
Based on the auction mechanism (TBA) of threshold value, main target is to make sensory perceptual system obtain maximum usefulness, does not possess the real character of bidding, and means that the user can obtain higher remuneration by concealing its true cost, thereby can be controlled by market.
Embodiment three:
As shown in Figure 3, the present embodiment has been put down in writing a kind of method based on the real online incentive mechanism of bidding, and comprises the steps:
S321: employed cellphone subscriber's set T to be set to 0,
With
Obtain at random k sampled value according to binomial distribution B (n, 1/2);
S322: according to the statistic of the bidding price of a front r candidate user, calculate described sensory perceptual system standardized payment, i.e. price thresholds threshold=CalThreshold (Q), and i=r+1 is set;
S323: if i＜k and | T|＜l then enters step S324; Otherwise, then enter step S326;
S324: if user's bidding price b
i＜threshold and threshold≤u
i(T)+b
i, then described sensory perceptual system determines to employ user i, and props up the remuneration p that pays the equal number of price thresholds threshold to user i
iOtherwise refusal is employed user i;
S325: make i=i+1, return step S323;
S326: according to a front k cellphone subscriber's competitive bidding scheme, utilize the inferior mould character of the Efficiency Function of described sensory perceptual system, calculate the optimal edge gain of performance vector of described sensory perceptual system, be δ=Sub mod MaxCardinality (U (1:k), m, and j=m-|T| is set, index=1 u);
S327: if j＜n and | T|＜m then enters step S328; Otherwise, finish;
S328: if user's bidding price b
j≤ threshold and
, then described sensory perceptual system determines to employ user j, and props up the remuneration P that the standard metering threshold value threshold that pays paying equates number to user j
j, and make index=index+1; Otherwise refusal is employed user j;
S329: make j=j+1, return step S327;
Wherein, n is potential user's sum; L is the predetermined number of users of employing; M is for employing total number of users; α is balance parameters; R is cutoff value, utilizes price thresholds to determine whether employ between r and k; K is cutoff value, utilizes price thresholds and edge usefulness threshold value to determine whether employ after k; δ is optimal edge gain of performance vector; J=m-|T| will be employed the number of users sequence behind the cutoff value k;
Q={b
1, b
2..., b
rBe that a front r candidate's cellphone subscriber is to the bidding price set of described sensory perceptual system submission; U is the Efficiency Function of described sensory perceptual system; u
j(T) user j is added to employ after the user gathers the edge gain of performance that described sensory perceptual system obtains; Index is index optimal edge gain vector δ;
The expression degree of approximation is the index item of the edge usefulness threshold vector of τ.
Price thresholds can observe user's the statistic of bidding obtain by calculating, has for example observed the average of bidding, intermediate value etc.Concrete application can be adopted different statistics.
Design based on the real online incentive mechanism of bidding:
At first, safeguard user's set of minimum bidding price, namely r candidate cellphone subscriber calculates the standardized payment that sensory perceptual system is ready to pay the acceptance of the bid cellphone subscriber in the bidding price set of described sensory perceptual system submission in the past, be price thresholds threshold, as the user's of the competitive bidding of newly arriving bidding price b
iLess than price thresholds threshold, and price thresholds be not more than that sensory perceptual system obtains the edge gain of performance time, just determine to employ this user, and to the identical remuneration of this user Zhi Fuyu price thresholds.Wherein,
Secondly, k cellphone subscriber obtains optimal edge gain of performance vector δ=Sub mod MaxCardinality (U (1:k), m, u), the edge usefulness threshold vector that it is τ that this vector δ is used to make up a degree of approximation in the past.
At last, if the user's of the competitive bidding of coming price is lower than price thresholds, and its edge gain of performance that brings sensory perceptual system is then employed this user, until sensory perceptual system has been employed the user of predetermined number greater than corresponding edge usefulness threshold value.
Both practicality can be guaranteed based on the real online incentive mechanism of bidding, the authenticity of bidding can be guaranteed again, can be by the situation of market control thereby avoid.Owing to considering receiving portion competitive bidding user in observation user's competitive bidding stage, reduced the probability of recruiting less than cellphone subscriber's quantity of being scheduled to based on the real online incentive mechanism of bidding.
Be the authenticity of bidding based on the real online incentive mechanism (TOIM) of bidding such as Figure 11.Two user u that select at random
362And u
400Allow submission and their inconsistent bidding price of true cost, two users' income when having described different bidding price among the figure.
The below introduces parameters to the impact of sensory perceptual system usefulness:
Fig. 5-Figure 10 showed comprehensively among the present invention based on the auction mechanism (TBA) of threshold value with based on real online incentive mechanism (TOIM) Algorithm Performance of bidding, algorithm greed mechanism (NAIVE) as a comparison is a basic greedy on-line Algorithm, its operating mechanism is that system is when whenever receiving a user's competitive bidding scheme, as long as the edge gain of performance that this user brings is non-negative, system just employs this user.
Fig. 5 is that systematic parameter α is on the impact of usefulness.Parameter alpha is a balance parameters, has determined to have the cellphone subscriber who how much employs from front k competitive bidding user.Show among the figure, when sensory perceptual system wanted to employ 40 users, sensory perceptual system usefulness reduced along with the increase of α, and this is because larger α, represent more to employ the user to be in the situation that there is not good edge gain of performance to employ as guidance.
Fig. 6 has showed that under time restriction, sensory perceptual system usefulness increases along with the increase of alternative total number of users n.This is that sensory perceptual system can obtain the information of more overall user's competitive biddings because of more selectable user, therefore can make better decision-making.
Fig. 7 has showed that the workload of perception task is on the impact of sensory perceptual system usefulness.Target employs number m to reflect the workload of perception task, and when alternative total number of users fixedly the time, along with m increases, the edge gain of employing more user to obtain reduces, this meet time imitate can function character.
Fig. 8 has showed the impact of parameter lambda on sensory perceptual system usefulness.λ is controlling the gradient of successively decreasing of sensory perceptual system usefulness objective function edge gain, and its setting depends on the domain knowledge of specific perception task.
Fig. 9 and Figure 10 have showed when parameter τ changes, the comparison of incentive mechanism under online incentive mechanism and the line, incentive mechanism under a kind of typical line of Local Search mechanism (LSB) representative among the figure, the curve of Fig. 9 represents the ratio curve of three kinds of online incentive mechanisms and Local Search mechanism (LSB), ratio is larger, illustrates that corresponding online incentive mechanism is more near optimum solution.When τ is too small, require the very strict optimum gain according to incentive mechanism under the line of online incentive mechanism to carry out user selection, this number of users that can cause sensory perceptual system to employ does not reach predetermined number, as shown in figure 10.When τ was fully large, the system senses system can employ the user of predetermined number, and therefore along with τ increases, the usefulness proportional curve descends.
The above only is preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the technology of the present invention principle; can also make some improvement and modification, these improve and modification also should be considered as protection scope of the present invention.
Claims (8)
1. the perception data acquisition methods based on online incentive mechanism is characterized in that, described method comprises the steps:
S1: sensory perceptual system sends to perception task the cellphone subscriber in target perception zone;
S2: if described cellphone subscriber is interested in receiving described perception task, according to described cellphone subscriber's Efficiency Function, submit a competitive bidding scheme to described sensory perceptual system, described competitive bidding scheme comprises bidding price and perception plan; Otherwise, then ignore described perception task;
S3: described sensory perceptual system utilizes the online incentive mechanism based on the Efficiency Function of described sensory perceptual system according to the described competitive bidding scheme that receives, and determines whether adopt described competitive bidding scheme, if so, metes out rewards then for described cellphone subscriber; Otherwise, then refuse to mete out rewards to described intelligence cellphone subscriber;
S4: described cellphone subscriber receives the decision that described sensory perceptual system is adopted, and then carries out described perception task, and perception data is sent to described sensory perceptual system.
2. perception data acquisition methods according to claim 1 is characterized in that, described bidding price refers to that described user is ready to participate in the needed minimum price of described perception task.
3. perception data acquisition methods according to claim 1 is characterized in that, the described cellphone subscriber's of step S2 Efficiency Function is calculated as follows:
Wherein, c
iTrue cost for user i; p
iPay the remuneration of the user i that is employed for sensory perceptual system; u
iEfficiency Function for user i; The user set of T for being employed.
4. perception data acquisition methods according to claim 1 is characterized in that, the Efficiency Function of the described sensory perceptual system of step S3 is calculated as follows:
Wherein, the user set of T for being employed, v (T)=∑
I ∈ Tv
i, v
iFor by the user i that the employed value to sensory perceptual system, υ (T) is the user that the employed value to sensory perceptual system; P (T)=∑
I ∈ Tp
i, p
iPay the remuneration of the user i that is employed for sensory perceptual system, P(T) pay the total remuneration of user that all are employed for sensory perceptual system; The logarithmic function item
React sensory perceptual system and employed cellphone subscriber's the edge usefulness of successively decreasing; Parameter lambda is used for controlling the gradient that edge usefulness is successively decreased.
5. each described perception data acquisition methods is characterized in that according to claim 1～4, and described online incentive mechanism is based on the auction mechanism of threshold value or based on the real online incentive mechanism of bidding.
6. perception data acquisition methods according to claim 5 is characterized in that, the method for described auction mechanism based on threshold value comprises the steps:
S311: employed cellphone subscriber's set T to be set to 0, obtain at random k sampled value according to binomial distribution B (n, 1/2);
S312: according to the competitive bidding scheme of front k candidate cellphone subscriber submission, utilize the inferior mould character of the Efficiency Function of described sensory perceptual system, calculate optimal edge gain of performance vector δ=SubmodMaxCardinality (Q, the m of described sensory perceptual system, and user's sequence i=k+1 is set u);
S313: if i＜n and | T|＜m then enters step S314; Otherwise, finish;
S314: if u
i(T) 〉=δ
| T|+1/ τ, then described sensory perceptual system determines to employ user i, user i is added among the set T that is employed the cellphone subscriber, and prop up the bidding price b that pays user i to user i
iThe remuneration p that equates number
iOtherwise refusal is employed user i;
S315: make i=i+1, return step S313;
Wherein, n is potential user's sum; M is for employing total number of users; K is cutoff value, utilizes edge usefulness threshold value to determine whether employ after k; δ is optimal edge gain of performance vector;
Q={b
1, b
2..., b
kBe that a front k candidate's cellphone subscriber submits the bidding price set to described sensory perceptual system; U is the Efficiency Function of described sensory perceptual system; u
i(T) user i is added to employed the cellphone subscriber to gather after the T, the edge gain of performance that described sensory perceptual system obtains; δ
| T|+1/ τ be the degree of approximation be τ edge usefulness threshold vector | the T|+1 item.
7. perception data acquisition methods according to claim 5 is characterized in that, described method based on the real online incentive mechanism of bidding comprises the steps:
S321: employed cellphone subscriber's set T to be set to 0,
With
Obtain at random k sampled value according to binomial distribution B (n, 1/2);
S322: according to the statistic of the bidding price of a front r candidate user, calculate described sensory perceptual system standardized payment, i.e. price thresholds threshold=CalThreshold (Q), and i=r+1 is set;
S323: if i＜k and | T|＜l then enters step S324; Otherwise, then enter step S326;
S324: if user's bidding price b
i＜threshold and threshold≤u
i(T)+b
i, then described sensory perceptual system determines to employ user i, and props up the remuneration p that pays the equal number of price thresholds threshold to user i
iOtherwise refusal is employed user i;
S325: make i=i+1, return step S323;
S326: according to a front k cellphone subscriber's competitive bidding scheme, utilize the inferior mould character of the Efficiency Function of described sensory perceptual system, calculate the optimal edge gain of performance vector of described sensory perceptual system, be δ=SubmodMaxCardinality (U (1:k), m, and j=m-|T| is set, index=1 u);
S327: if j＜n and | T|＜m then enters step S328; Otherwise, finish;
S328: if user's bidding price b
j≤ threshold and
, then described sensory perceptual system determines to employ user j, and props up the remuneration P that the standard metering threshold value threshold that pays paying equates number to user j
j, and make index=index+1; Otherwise refusal is employed user j;
S329: make j=j+1, return step S327;
Wherein, n is potential user's sum; L is the predetermined number of users of employing; M is for employing total number of users; α is balance parameters; R is cutoff value, utilizes price thresholds to determine whether employ between r and k; K is cutoff value, utilizes price thresholds and edge usefulness threshold value to determine whether employ after k; δ is optimal edge gain of performance vector; J=m-|T| will be employed the number of users sequence behind the cutoff value k;
Q={b
1, b
2..., b
rBe that a front r candidate's cellphone subscriber is to the bidding price set of described sensory perceptual system submission; U is the Efficiency Function of described sensory perceptual system; u
j(T) user j is added to employ after the user gathers the edge gain of performance that described sensory perceptual system obtains; Index is index optimal edge gain vector δ;
The expression degree of approximation is the index item of the edge usefulness threshold vector of τ.
8. perception data acquisition methods according to claim 7 is characterized in that, described price thresholds is the average of bidding price or the intermediate value of bidding price.
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