CN103533502A - Method and system for preventing fraudulent auction in group intelligent perception system - Google Patents
Method and system for preventing fraudulent auction in group intelligent perception system Download PDFInfo
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Abstract
The invention discloses a method and a system for preventing fraudulent auction in a group intelligent perception system. The method comprises the following steps that each intelligent mobile phone user registers in an auction part platform, and the platform sends all perception task lists and auction modes to the user; each intelligent mobile phone user makes a bid document and submits the bid document to the auction part platform; the platform selects a group of intelligent mobile phone users according to the bid documents submitted by all the intelligent mobile phone users, so that the group of user can finish all the perception tasks, the sum of quoted price is the smallest, and meanwhile, the platform calculates the payment which should be paid to each selected intelligent mobile phone user and informs the selected users of starting executing corresponding perception tasks; each selected intelligent mobile phone user executes the corresponding perception tasks and feeds a result to the platform; the platform pays corresponding payment to each participant user according to the calculated payment. The auction method which can efficiently finish the perception tasks and can prevent cheat is realized.
Description
Technical field
The present invention relates to auction system and system that the selfish user of excitation in a kind of gunz sensory perceptual system participates in and contributes, particularly relate to anti-deception auction system and system in a kind of gunz sensory perceptual system.
Background technology
In recent years, along with the continuous reduction of the price of the development of smart mobile phone manufacturing technology, smart mobile phone had become modern's requisite part of living.Different from traditional digital communication mobile phone, smart mobile phone can provide diversified service for user, such as access, navigation etc.By means of smart mobile phone integrated increasing transducer, as accelerometer, electronic compass, thermometer, global positioning system (GPS), the gunz sensory perceptual system that smart mobile phone forms has led a kind of very promising novel Data Collection and shared pattern.Fig. 1 is the Application Scenarios-Example figure of current gunz sensory perceptual system.Such gunz sensory perceptual system is different from traditional wireless sensor network, and it has removed the trouble of planned network topology and on-premise network from, network that neither a kind of special use.The gunz sensory perceptual system that smart mobile phone forms also has many intrinsic advantages.Because smart mobile phone is carried by people and along with people moves, it can form wide node coverage and dense node coverage density easily.On the other hand, because the various transducer most of times of installing on smart mobile phone are idle, gunz sensory perceptual system can better utilize these idle resources, and a lot of potential application and service are provided.
Yet will form the gunz sensory perceptual system consisting of a large amount of smart mobile phones still has many basic problems urgently to be resolved hurrily.In gunz sensory perceptual system, a most basic problem is exactly how to encourage smart phone user, thereby makes them be ready to participate in gunz perception.Owing to participating in the resource that needs to consume smart mobile phone self in gunz sensory perceptual system, such as battery, CPU time etc., any the smart phone user of considering number one is all unwilling to contribute the resource of oneself to come for other people service.Such characteristic of smart phone user is called as selfishness.Consider selfishness, must give the loss that the certain compensation of smart phone user makes up them, they just can be ready to participate in gunz sensing network.
Existing gunz sensory perceptual system is divided into two large classes conventionally.The first kind is not considered the selfishness of smart phone user conventionally.They suppose that smart phone user participates in and contribute the resource of oneself voluntarily.The system of this class considers emphatically how to build a platform conventionally to be organized and coordinates all smart mobile phones and effectively complete some perception tasks.The problem that this platform will solve comprises collects data, deal with data etc.For example, task is wanted the appropriate suitable smart phone user of giving, and avoids repeating some task.In addition, from being dispersed in the data of collecting different positions, may need platform to carry out the information that some statistics were processed and therefrom extracted in some polymerizations.Equations of The Second Kind system has considered that the user in reality is only in the situation that give the resource that certain return just can be ready contribution oneself.The smart phone user of all participations can obtain certain return.After introducing price mechanism, the reward of each participating user of how to confirm is also a basic problem.In order to select efficiently smart mobile phone to complete the task of gunz perception, conventionally introduce the mechanism of auction and determine the reward of paying each user.Each smart phone user can complete specific task (task is conventionally relevant with geographical location information), and for completing acceptable lowest price of these task reports.Fig. 2 is the schematic diagram of auction mechanism in current gunz sensory perceptual system.First, smart phone user is registered in system platform, and system is pushed to all registration smart phone users by the list of perception task.Then, the smart phone user that each was registered is submitted the bidding documents of an auction to, indicates perception task list and the quotation accordingly thereof that oneself can complete.Then, the bidding documents that system is submitted to according to all smart phone users is selected one group of winner and calculates the reward of paying each smart phone user of electing, and notifies corresponding smart phone user.Then, the smart phone user being selected completes corresponding perception task, and the result obtaining is sent to system platform.Finally, platform is paid each selected smart phone user out and is recompensed accordingly
Yet in using the process of auction mechanism, owing to relating to the quotation of smart phone user self, selfish smart phone user may have deceptive practices, thereby maximizes the income of oneself.Due to the existence of deceptive practices, platform is difficult to select and can efficiently completes the user of perception task, and it is also larger to complete the reward that perception task will pay.In order to prevent user's deceptive practices, need to formulate reasonably reward and pay decision-making, make to utilize deception also cannot obtain higher income, thereby avoid the appearance of deceptive practices.
Summary of the invention
The deficiency existing for overcoming above-mentioned prior art, the present invention's object is to provide anti-deception auction system and the system in a kind of gunz sensory perceptual system, realize a kind of perception task that can efficiently complete and can prevent again the auction system of cheating, consider the geographic restriction of perception task and smart mobile phone simultaneously, and made the Least-cost of perception task.
For reaching above-mentioned and other object, the present invention proposes the anti-deception auction system in a kind of gunz sensory perceptual system, comprises the steps:
Step 1, each smart phone user is in the registration of auction side's platform, and this side's of auction platform is all perception task list Γ={ τ
1, τ
2..., τ
nand auction pattern be pushed to each smart phone user;
Step 2, each smart phone user goes out a bidding documents and is submitted to this side's of auction platform, and bidding documents is indicated particular task and the quotation accordingly that can complete;
Step 3, the bidding documents that this side's of auction platform is submitted to according to all smart phone users, select one group of smart phone user W, make this group user can complete all perception tasks, and quotation sum is minimum, meanwhile, this side's of auction platform calculates pay the reward of each selected smart phone user, and notifies selected user to start to carry out corresponding perception task;
Step 4, selected smart phone user is carried out corresponding perception task, and result is returned to this side's of auction platform;
Step 5, the side's of auction platform, according to the reward of calculating in step 3, is paid the smart phone user of each participation and is returned accordingly.
Further, in step 3, this side's of auction platform adopts approximate method to carry out greedy selection user, and the 1+ln (n) that the true cost sum that makes to select user is no more than optimal value doubly, and wherein n is the maximum of each smart phone user perception task number that can complete.
Further, in step 3, select the step of smart phone user also to comprise the steps:
Step 3.1, the side's of auction platform obtains each smart phone user and to platform, submits the bidding documents that participates in auction to, comprises the task s that can complete for it
idescription and corresponding quotation b
i, suppose that all perception task set are Γ;
Step 3.2, is initialized as respectively empty set by the set Γ ' of the perception task that represents the set W of selected smart phone user out and distributed;
Step 3.3, whether the perception task Γ ' that judgement has distributed has covered all perception tasks, if equated, forwards step 3.9 to;
Step 3.4, deletes and all for completing perception task, does not have the contributive selecteed user that also do not have;
Step 3.5, calculates the sequence index b that each does not also have selecteed smart phone user
i/ | s
i-Γ ' |, and sort according to order from small to large;
Step 3.6, selects to come top smart phone user j, is added in set W and goes, and makes W ← W ∪ j, upgrades the perception task set Γ ' having distributed and makes Γ ' ← Γ ' ∪ s
j;
Step 3.7 deletes smart phone user j from all unallocated user lists;
Step 3.8, forwards step 3.3 to;
Step 3.9, finishes.
Further, in step 3, the step of calculating the reward of each selected smart phone user also comprises the steps:
Active user is rejected from all smart phone user lists;
According to selecting the method for smart phone user, avidly select user, until find a critical user, while making this critical user selected, this user is to the contribution of system (| Γ-Γ ' |) by non-zero vanishing, and the reward of paying this user just equals this critical user sequence index at that time and is multiplied by the contribution for system before critical user does not have to select of this smart phone user | Γ-Γ " |.
Further, the bidding documents that each smart phone user is submitted to is two tuple (s
i, b
i), wherein
represent the perception task that this user can complete, s
iby the geographical position of smart phone user and the geographical position attribute of each perception task, determined b
irepresent that user completes the quotation of these tasks.
For achieving the above object, the present invention also provides the anti-deception auction system in a kind of gunz sensory perceptual system, at least comprises:
Initialization module, makes each smart phone user in the registration of auction side's platform, and this side's of auction platform is all perception task list Γ={ τ
1, τ
2..., τ
nand auction pattern be pushed to each smart phone user;
Bid auction module, makes each smart phone user go out a bidding documents and be submitted to platform, and this bidding documents is indicated particular task and the quotation accordingly that can complete;
Select user and reward computing module, the bidding documents of submitting to according to all users, select one group of smart phone user W, make this group user can complete all perception tasks, and quotation sum is minimum, calculate and pay the reward of each selected smart phone user simultaneously, and notify selected user to start to carry out corresponding perception task;
Tasks carrying feedback module, makes selected smart phone user carry out corresponding perception task, and result is returned to auction side's platform;
Reward payment module, the reward of selecting user and reward computing module to calculate according to this, pays the smart phone user of each participation and returns accordingly.
Further, this selection user and reward computing module comprise:
Select line module, adopt one group of smart phone user W of selection of approximate method greed, doubly, wherein n is the maximum of each smart phone user perception task number that can complete to the 1+ln (n) that the true cost sum that makes to select user is no more than optimal value;
Reward computing module, for calculating the reward of each selecteed smart phone user.
Further, this selection line module also comprises:
Auction bidding documents acquisition module, obtains each smart phone user and to auction side's platform, submits the bidding documents that participates in auction to, comprises the task s that can complete for it
idescription and corresponding quotation b
i, suppose that all perception task set are Γ;
Set initialization module, is initialized as respectively empty set by the set Γ ' of the perception task that represents the set W of selected smart phone user out and distributed;
Judge module, whether the perception task Γ ' that judgement has distributed has covered all perception tasks;
Removing module is deleted and all for completing perception task, is not had the contributive selecteed user that also do not have when the determination result is NO;
Order module, calculates the sequence index b that each does not also have selecteed smart phone user
i/ | s
i-Γ ' |, and sort according to order from small to large;
Update module is selected to come top smart phone user j, is added in set W and goes, and makes W ← W ∪ j, upgrades the perception task set Γ ' having distributed and makes Γ ' ← Γ ' ∪ s
j, and this smart phone user j is deleted from all unallocated user lists.
Further, when this reward computing module calculates the reward of each selecteed smart phone user, first this user is rejected from all smart phone user lists, then according to the method for this selection line module, avidly select user, until find a critical user, while making this critical user selected, this user to the contribution of system (| Γ-Γ ' |) by non-zero vanishing, the reward of paying this user just equals this critical user sequence index at that time and is multiplied by the contribution for system before critical user does not have selection of this smart phone user | Γ-Γ " |.
Further, the bidding documents that each smart phone user is submitted to is two tuple (s
i, b
i), wherein
represent the perception task that this user can complete, s
iby the geographical position of smart phone user and the geographical position attribute of each perception task, determined b
irepresent that user completes the quotation of these tasks.
Compared with prior art, anti-deception auction system and system in a kind of gunz sensory perceptual system of the present invention, realize a kind of perception task that can efficiently complete and can prevent again the auction system of cheating, consider the geographic restriction of perception task and smart mobile phone simultaneously, and made the Least-cost of perception task.
Accompanying drawing explanation
Fig. 1 is the Application Scenarios-Example figure of current gunz sensory perceptual system;
Fig. 2 is the schematic diagram of auction mechanism in current gunz sensory perceptual system;
Fig. 3 is the flow chart of steps of the anti-deception auction system in a kind of gunz sensory perceptual system of the present invention;
Fig. 4 is the flow chart of steps of platform selecting smart phone user in the side's of auction in preferred embodiment of the present invention;
Fig. 5 is the system architecture diagram of the anti-deception auction system in a kind of gunz sensory perceptual system of the present invention;
Fig. 6 is the module diagram of selecting user and reward computing module in preferred embodiment of the present invention.
Embodiment
Below, by specific instantiation accompanying drawings embodiments of the present invention, those skilled in the art can understand other advantage of the present invention and effect easily by content disclosed in the present specification.The present invention also can be implemented or be applied by other different instantiation, and the every details in this specification also can be based on different viewpoints and application, carries out various modifications and change not deviating under spirit of the present invention.
Fig. 3 is the flow chart of steps of the anti-deception auction system in a kind of gunz sensory perceptual system of the present invention.As shown in Figure 3, the anti-deception auction system in a kind of gunz sensory perceptual system of the present invention, the gunz sensory perceptual system that is applied to be comprised of smart mobile phone, comprises the steps:
Owing to selecting a part of smart phone user, the true cost sum minimum that makes them complete all perception tasks is NP-complete problem, in the present invention, adopt a kind of approximate method to select user, and the 1+ln (n) that the true cost sum that makes to select user is no more than optimal value doubly, wherein n is the maximum of each smart phone user perception task number that can complete.The selection of the approximation method greed of the employing in the present invention is for the highest smart phone user of system " cost performance ".The perception task set that the user who supposes to have selected can complete is Γ ', " performance " represents the perception task number (getting rid of the perception task having distributed) that this smart phone user can complete so, with | Γ-Γ ' | represent, " price " is exactly this user's quotation, uses b
irepresent.The sequence index that present some smart phone users are corresponding is b
i/ | Γ-Γ ' |.The selection of greed is for the user of sequence index minimum, until complete all perception tasks.Especially, if certain does not also have selecteed smart phone user to become 0(for the contribution of system | Γ-Γ ' |=0), this user just can not be selected more so.
In step 303, when the side's of auction platform calculates the reward of each selecteed smart phone user, first this user is rejected from all smart phone user lists, then according to the method in step 303, avidly select user, until find a critical user, while making this critical user selected, this user to the contribution of system (| Γ-Γ ' |) by non-zero vanishing; The reward of paying so this user just equals this critical user sequence index at that time and is multiplied by the contribution for system before critical user does not have selection of this smart phone user | Γ-Γ " |.
Fig. 4 is the flow chart of steps of platform selecting smart phone user in the side's of auction in preferred embodiment of the present invention.As shown in Figure 4, auction side's platform selecting smart phone user step of preferred embodiment of the present invention, comprises the steps:
Step (1), system initialization, the side's of auction platform obtains each smart phone user and to platform, submits the bidding documents that participates in auction to, comprises the task s that can complete for it
idescription and corresponding quotation b
i, suppose that all perception task set are Γ;
Step (2), is initialized as respectively empty set by the set Γ ' of the perception task that represents the set W of selected smart phone user out and distributed;
Step (3), judgement distributed whether perception task Γ ' has covered all perception tasks (judges Γ '=Γ?), if equated, forward step (9) to;
Step (4), deletes and all for completing perception task, does not have the contributive selecteed user that also do not have;
Step (5), calculates the sequence index b that each does not also have selecteed smart phone user
i/ | s
i-Γ ' |, and sort according to order from small to large;
Step (6), selects to come top smart phone user j, is added in set W and goes, and makes W ← W ∪ j, upgrades the perception task set Γ ' having distributed and makes Γ ' ← Γ ' ∪ s
j;
Step (7).Smart phone user j is deleted from all unallocated user lists;
Step (8), forwards step (3) to;
Step (9), finishes.
Fig. 5 is the system architecture diagram of the anti-deception auction system in a kind of gunz sensory perceptual system of the present invention.As shown in Figure 5, the anti-deception auction system in a kind of gunz sensory perceptual system of the present invention, at least comprises: initialization module 50, bid auction module 51, selection user and reward computing module 52, tasks carrying feedback module 53 and reward payment module 54.
Wherein initialization module 50 makes each smart phone user in the registration of auction side's platform, reports their existence, and the side's of auction platform is all perception task list Γ={ τ
1, τ
2..., τ
nand auction pattern be pushed to each smart phone user; Bid auction module 51 makes each smart phone user bid auction, make each smart phone user go out a bidding documents and be submitted to platform, bidding documents is indicated particular task and the quotation accordingly that can complete, and each smart phone user is submitted two tuple (s to
i, b
i), wherein
represent the perception task that this user can complete, s
iby the geographical position of smart phone user and the geographical position attribute of each perception task, determined b
irepresent that user completes the quotation of these tasks; The bidding documents of selecting user and reward computing module 52 to submit to according to all users, select one group of smart phone user W, make this group user can complete all perception tasks, and quotation sum is minimum, calculate and pay the reward of each selected smart phone user simultaneously, and notify selected user to start to carry out corresponding perception task; Tasks carrying feedback module 53 makes selected smart phone user carry out corresponding perception task, and result is returned to auction side's platform; Reward payment module 54, according to the reward of selecting user and reward computing module 52 to calculate, is paid the smart phone user of each participation and is returned accordingly.
Fig. 6 is the module diagram of selecting user and reward computing module in preferred embodiment of the present invention.In preferred embodiment of the present invention, select user and reward computing module 52 further to comprise and select line module 520 and reward computing module 521.
Wherein, select line module 520 to adopt one group of smart phone user W of selection of approximate method greed, doubly, wherein n is the maximum of each smart phone user perception task number that can complete to the 1+ln (n) that the true cost sum that makes to select user is no more than optimal value.Specifically, select line module 520 to comprise auction bidding documents acquisition module 5201, set initialization module 5202, judge module 5203, removing module 5204, order module 5205, update module 5206, auction bidding documents acquisition module 5201 obtains each smart phone user and to auction side's platform, submits the bidding documents that participates in auction to, comprises the task s that can complete for it
idescription and corresponding quotation b
i, suppose that all perception task set are Γ; Set initialization module 5202 is initialized as respectively empty set by the set Γ ' of the perception task that represents the set W of selected smart phone user out and distributed; Judge module 5203 judgement distributed whether perception task Γ ' has covered all perception tasks (judges Γ '=Γ?); Removing module 5204 is deleted when the determination result is NO all does not have the contributive selecteed user that also do not have for completing perception task; Order module 5205 is calculated each does not also have the sequence index b of selecteed smart phone user
i/ | s
i-Γ ' |, and sort according to order from small to large; Update module 5206 is selected to come top smart phone user j, is added in set W and goes, and makes W ← W ∪ j, upgrades the perception task set Γ ' having distributed and makes Γ ' ← Γ ' ∪ s
j, and smart phone user j is deleted from all unallocated user lists.
Reward computing module 521 is for calculating the reward of each selecteed smart phone user, specifically, when reward computing module 521 calculates the reward of each selecteed smart phone user, first this user is rejected from all smart phone user lists, then according to selecting the method for line module 520 avidly to select user, until find a critical user, while making this critical user selected, this user to the contribution of system (| Γ-Γ ' |) by non-zero vanishing; The reward of paying so this user just equals this critical user sequence index at that time and is multiplied by the contribution for system before critical user does not have selection of this smart phone user | Γ-Γ " |.
In sum, anti-deception auction system and system in a kind of gunz sensory perceptual system of the present invention, realize a kind of perception task that can efficiently complete and can prevent again the auction system of cheating, consider the geographic restriction of perception task and smart mobile phone simultaneously, and made the Least-cost of perception task, the present invention is applicable to the gunz sensory perceptual system forming with smart mobile phone, and the results show by emulation experiment correctness of the present invention and superiority.
Compared with prior art, advantage of the present invention is as follows:
(1) the present invention can, so that each smart mobile phone is submitted the real price of oneself honestly to, avoid the deceptive practices of smart phone user.
(20 the present invention can complete all perception so that the side's of auction platform is selected some smart phone users, and the true cost sum of these smart phone users with optimal value, to compare be bounded, the reward altogether that platform is paid is also smaller.
(3) Greedy strategy that the present invention adopts is selected one group of user, and the complexity of selection algorithm is lower, is polynomial time.
Above-described embodiment is illustrative principle of the present invention and effect thereof only, but not for limiting the present invention.Any those skilled in the art all can, under spirit of the present invention and category, modify and change above-described embodiment.Therefore, the scope of the present invention, should be as listed in claims.
Claims (10)
1. the anti-deception auction system in gunz sensory perceptual system, comprises the steps:
Step 1, each smart phone user is in the registration of auction side's platform, and this side's of auction platform is all perception task list Γ={ τ
1, τ
2..., τ
nand auction pattern be pushed to each smart phone user;
Step 2, each smart phone user goes out a bidding documents and is submitted to this side's of auction platform, and bidding documents is indicated particular task and the quotation accordingly that can complete;
Step 3, the bidding documents that this side's of auction platform is submitted to according to all smart phone users, select one group of smart phone user W, make this group user can complete all perception tasks, and quotation sum is minimum, meanwhile, this side's of auction platform calculates pay the reward of each selected smart phone user, and notifies selected user to start to carry out corresponding perception task;
Step 4, selected smart phone user is carried out corresponding perception task, and result is returned to this side's of auction platform;
Step 5, the side's of auction platform, according to the reward of calculating in step 3, is paid the smart phone user of each participation and is returned accordingly.
2. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 1, it is characterized in that: in step 3, this side's of auction platform adopts approximate method to carry out greedy selection user, and the 1+ln (n) that the true cost sum that makes to select user is no more than optimal value doubly, wherein n is the maximum of each smart phone user perception task number that can complete.
3. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 2, is characterized in that, in step 3, selects the step of smart phone user also to comprise the steps:
Step 3.1, the side's of auction platform obtains each smart phone user and to platform, submits the bidding documents that participates in auction to, comprises the task s that can complete for it
idescription and corresponding quotation b
i, suppose that all perception task set are Γ;
Step 3.2, is initialized as respectively empty set by the set Γ ' of the perception task that represents the set W of selected smart phone user out and distributed;
Step 3.3, whether the perception task Γ ' that judgement has distributed has covered all perception tasks, if equated, forwards step 3.9 to;
Step 3.4, deletes and all for completing perception task, does not have the contributive selecteed user that also do not have;
Step 3.5, calculates the sequence index b that each does not also have selecteed smart phone user
i/ | s
i-Γ ' |, and sort according to order from small to large;
Step 3.6, selects to come top smart phone user j, is added in set W and goes, and makes W ← W ∪ j, upgrades the perception task set Γ ' having distributed and makes Γ ' ← Γ ' ∪ s
j;
Step 3.7 deletes smart phone user j from all unallocated user lists;
Step 3.8, forwards step 3.3 to;
Step 3.9, finishes.
4. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 3, is characterized in that, in step 3, the step of calculating the reward of each selected smart phone user also comprises the steps:
Active user is rejected from all smart phone user lists;
According to selecting the method for smart phone user, avidly select user, until find a critical user, while making this critical user selected, the contribution of this user to system | Γ-Γ ' | by non-zero vanishing, the reward of paying this user just equals this critical user sequence index at that time and is multiplied by the contribution for system before critical user does not have selection of this smart phone user | Γ-Γ " |.
5. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 1, is characterized in that: the bidding documents that each smart phone user is submitted to is two tuple (s
i, b
i), wherein
represent the perception task that this user can complete, s
iby the geographical position of smart phone user and the geographical position attribute of each perception task, determined b
irepresent that user completes the quotation of these tasks.
6. the anti-deception auction system in gunz sensory perceptual system, at least comprises:
Initialization module, makes each smart phone user in the registration of auction side's platform, and this side's of auction platform is all perception task list Γ={ τ
1, τ
2..., τ
nand auction pattern be pushed to each smart phone user;
Bid auction module, makes each smart phone user go out a bidding documents and be submitted to platform, and this bidding documents is indicated particular task and the quotation accordingly that can complete;
Select user and reward computing module, the bidding documents of submitting to according to all users, select one group of smart phone user W, make this group user can complete all perception tasks, and quotation sum is minimum, calculate and pay the reward of each selected smart phone user simultaneously, and notify selected user to start to carry out corresponding perception task;
Tasks carrying feedback module, makes selected smart phone user carry out corresponding perception task, and result is returned to auction side's platform;
Reward payment module, the reward of selecting user and reward computing module to calculate according to this, pays the smart phone user of each participation and returns accordingly.
7. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 6, is characterized in that, this selection user and reward computing module comprise:
Select line module, adopt one group of smart phone user W of selection of approximate method greed, doubly, wherein n is the maximum of each smart phone user perception task number that can complete to the 1+ln (n) that the true cost sum that makes to select user is no more than optimal value;
Reward computing module, for calculating the reward of each selecteed smart phone user.
8. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 7, is characterized in that, this selection line module also comprises:
Auction bidding documents acquisition module, obtains each smart phone user and to auction side's platform, submits the bidding documents that participates in auction to, comprises the task s that can complete for it
idescription and corresponding quotation b
i, suppose that all perception task set are Γ;
Set initialization module, is initialized as respectively empty set by the set Γ ' of the perception task that represents the set W of selected smart phone user out and distributed;
Judge module, whether the perception task Γ ' that judgement has distributed has covered all perception tasks;
Removing module is deleted and all for completing perception task, is not had the contributive selecteed user that also do not have when the determination result is NO;
Order module, calculates the sequence index b that each does not also have selecteed smart phone user
i/ | s
i-Γ ' |, and sort according to order from small to large;
Update module is selected to come top smart phone user j, is added in set W and goes, and makes W ← W ∪ j, upgrades the perception task set Γ ' having distributed and makes Γ ' ← Γ ' ∪ s
j, and this smart phone user j is deleted from all unallocated user lists.
9. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 8, it is characterized in that: when this reward computing module calculates the reward of each selecteed smart phone user, first this user is rejected from all smart phone user lists, then according to the method for this selection line module, avidly select user, until find a critical user, while making this critical user selected, the contribution of this user to system | Γ-Γ ' | by non-zero vanishing, the reward of paying this user just equals this critical user sequence index at that time and is multiplied by the contribution for system before critical user does not have selection of this smart phone user | Γ-Γ " |.
10. the anti-deception auction system in a kind of gunz sensory perceptual system as claimed in claim 6, is characterized in that: the bidding documents that each smart phone user is submitted to is two tuple (s
i, b
i), wherein
represent the perception task that this user can complete, s
iby the geographical position of smart phone user and the geographical position attribute of each perception task, determined b
irepresent that user completes the quotation of these tasks.
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| CN (1) | CN103533502B (en) |
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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 |
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