CN105825333A - Crowdsourcing service system based on anonymous places of cloud platform and task distribution method - Google Patents

Crowdsourcing service system based on anonymous places of cloud platform and task distribution method Download PDF

Info

Publication number
CN105825333A
CN105825333A CN201610144236.1A CN201610144236A CN105825333A CN 105825333 A CN105825333 A CN 105825333A CN 201610144236 A CN201610144236 A CN 201610144236A CN 105825333 A CN105825333 A CN 105825333A
Authority
CN
China
Prior art keywords
participant
task
cloud platform
distributed
user
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
CN201610144236.1A
Other languages
Chinese (zh)
Inventor
孙雁飞
亓晋
周永生
王堃
陈思光
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing Post and Telecommunication University
Nanjing University of Posts and Telecommunications
Original Assignee
Nanjing Post and Telecommunication University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing Post and Telecommunication University filed Critical Nanjing Post and Telecommunication University
Priority to CN201610144236.1A priority Critical patent/CN105825333A/en
Publication of CN105825333A publication Critical patent/CN105825333A/en
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Economics (AREA)
  • Operations Research (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Educational Administration (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a crowdsourcing service system based on anonymous places of a cloud platform. The system comprises the cloud platform, a configuration file library, a metadatabase and a content analysis background, wherein the metadatabase comprises a professional field concept map, WiKi and Dbpedia keywords and FAQ keywords, and the content analysis background comprises a load balancer, a task distribution server, a participant module, a field expert module and a user data storage server. According to the invention, participants participate in tasks on the premises that the participants do not like to share concrete places, crowdsourcing tasks can be distributed in high efficiency, the utilization rate of labor resources is improved, and response time of task distribution is shortened.

Description

Mass-rent service system based on cloud platform anonymity place and method for allocating tasks
Technical field
The present invention relates to secret protection field, particularly to mass-rent service system based on cloud platform anonymity place and method for allocating tasks.
Background technology
In recent years, mass-rent has been developed as the production model of a kind of distributed problem solving and business.In mass-rent pattern, task is assigned to people on network and completes, and so can be substantially reduced the production cost of company.Distributed mobile quorum-sensing system becomes a valuable model already, and various novel application are set up on mobile network and mini-plant.But, this trend brings lot of challenges, needs the mutual exchange managing between application program and colony including mass-rent platform.One of major function of this platform is space tasks distribution, distributes perception task to participant according to their position, and task distribution becomes extremely important, but the most most of participant is reluctant to share the exact geographic location of oneself due to privacy concern.Therefore it provides disclosure satisfy that the mass-rent service system that participant requires is particularly important, it may have highly important realistic meaning.In existing technology, the not effective workaround to participant's anonymity place, space tasks distribution there is also problems in addition, and on the one hand incentive mechanism imperfection causes relatively low human resources utilization to lead, and on the other hand the response time of task distribution is long.
In reality, there is the task mass-rent method of Intelligent Service Oriented business engine, service platform calculates service factor and the income coefficient of each service node, and the distribution target of task is weighed according to the competitive bidding factor and service factor, assigning the task to the destination node of correspondence, the ultimate yield being finally provided to service node is disadvantageous in that as excitation, this technology: the task for mass-rent pattern is distributed, its incentive mechanism imperfection, causes relatively low human resources utilization to lead；Also have task optimum allocation method and system thereof in a kind of mass-rent, whole process is in the case of bid based on the transaction value set by mass-rent and user, meeting each task for completing the requirement of task number, it is disadvantageous in that, the response time that the method is distributed for task is long.
Summary of the invention
For method for allocating tasks in existing mass-rent, solving the privacy concern in participant's anonymity place, the task in mass-rent is distributed by the present invention efficiently, it is achieved improves human resources utilization and leads and the response time of shortening task distribution.
Mass-rent service system based on cloud platform anonymity place, including cloud platform, configuration file storehouse, metadatabase and content analysis backstage, described metadatabase includes professional field concept map, Wiki and Dbpedia key word and FAQ key word；Described content analysis backstage includes load balance device, task distribution server, participant's module, domain expert's module and user data storage server；Wherein, load balance device is for receiving the analysis request from cloud platform, and analysis request is divided into multiple distributed task scheduling ask, and is sent to task distribution server；Participant's module obtains task from described task distribution server, stores the result into described user data storage server after completing task, and described participant is labeled with key word；Configuration file storehouse and metadatabase are fed back and are updated by user data storage server；The result that task is distributed by domain expert's module by the knowledge of self exercises supervision, and bad result is returned described participant.
Described cloud platform includes the immature content that network service resource and user generate.
The present invention also provides for the method for allocating tasks of a kind of mass-rent service system based on cloud platform anonymity place, comprises the following steps:
Step 1, user find the resource relevant to oneself problem in the network service resource of platform, without the resource that can directly utilize, then generate immature content, and user sends analysis request for described immature content to content analysis backstage；
Step 2, described analysis request are loaded static organ and are divided into the distributed task scheduling of a lot of fraction to ask, and distributed task scheduling request is transferred to task distribution server, are optimized distributed task scheduling request according to place；
Participant in step 3, participant's module obtains respective task from described task distribution server, stores the result into described user data storage server after completing task, and described participant is labeled with key word；
The result that task is distributed by step 4, domain expert's module by the knowledge of self exercises supervision, and bad result is returned described participant；
Configuration file storehouse and metadatabase are fed back and are updated by step 5, user data storage server.
The process that is optimized of distributed task scheduling request according to place is by described in step 2:
In step 201, the anonymous region of calculating, the barycenter in all places is as desired distance d of participanti,j,
d i , j = d i s t ( ∫ z ∈ a i zf i ( z ) d z , l j )
Wherein aiFor the anonymous region in the Z of region, ljIt is the position of target j, fiZ () is aiThe probability density function of each participant in region, function dist is the Euclidean distance between any two points；
Step 202, find the participant-target of optimum cost benefit to and be each assigned to the other side, for a participant pi(i ∈ 1,2 ..., n}) and task object tj(j ∈ 1,2 ..., and m}), task is distributed to the cost benefit of the other side and is designated as∈ is minimum nonnegative number
φ i , j ( 1 ) = d i , j min ( 1 - u j + , 1 k j ) + ∈
WhereinIt it is the vector at target zone internal object j, it is desirable to the vector of target zone internal object k；
Step 203, iteration participant-target is to rear, select the participant-target of optimum cost benefit to and update current target search scope, traveling through all targets until the distance budget meeting target search scope or all of participant exhausts, the cost benefit computing formula of each task becomes:
φ i , j ( 2 ) = d i , j b i + | x i , j - 1 | min ( 1 - u j + , 1 k j ) + ∈
Wherein biIt is the distance budget of participant i, xI, jIt it is the j task of participant i.
The present invention participates in completing of task on the premise of participant is unwilling to share definite place, and the task in mass-rent can be distributed efficiently in addition, improves human resources utilization and leads and the response time of shortening task distribution.
Accompanying drawing explanation
Fig. 1 is mass-rent service system structural representation based on cloud platform anonymity place.
Detailed description of the invention
In order to make the purpose of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.
As shown in Figure 1, mass-rent service system based on cloud platform anonymity place includes cloud platform, configuration file storehouse, metadatabase and content analysis backstage, cloud platform has the immature content that network service resource and user generate, configuration file is event process and history, metadata includes professional field concept map, Wiki and Dbpedia key word and FAQ key word, and content analysis backstage includes load balance device, task distribution server, participant's module, domain expert's module and user data storage server.
As a example by education and study, education and study user carries out the relevant knowledge search of paper in cloud platform, obtains jejune result, and metadata carries out keyword label to result, and configuration file carries out data record to network service platform.User is to the application service of content analysis backstage, content analysis backstage is balanced loading to this request and obtains Distributed Services request, Distributed Services request distributes to suitable participant through task distributor, participant completes task on the premise of not sharing place, participant completes the result of task and is stored in user data storage server, and the metadata result to obtaining carries out keyword label.Now result is exercised supervision by domain expert, if there is not meeting the result that user requires, then returns to participant.Configuration file and metadata are fed back and update by user data storage server, and configuration file and metadata obtain up-to-date data.If user can apply for service again to result is dissatisfied.
Technological means disclosed in the present invention program is not limited only to the technological means disclosed in above-mentioned embodiment, also includes the technical scheme being made up of above technical characteristic combination in any.

Claims (4)

1. mass-rent service system based on cloud platform anonymity place, including cloud platform, configuration file storehouse, metadatabase and content analysis backstage, it is characterised in that described metadatabase includes professional field concept map, Wiki and Dbpedia key word and FAQ key word；Described content analysis backstage includes load balance device, task distribution server, participant's module, domain expert's module and user data storage server；Wherein,
Load balance device is for receiving the analysis request from cloud platform, and analysis request is divided into multiple distributed task scheduling ask, and is sent to task distribution server；
In participant's module, each participant obtains task from described task distribution server, stores the result into described user data storage server after completing task, and described participant is labeled with key word；
Configuration file storehouse and metadatabase are fed back and are updated by user data storage server；
The result that task is distributed by domain expert's module by the knowledge of self exercises supervision, and the result not meeting user's requirement is returned to described participant.
Mass-rent service system based on cloud platform anonymity place the most according to claim 1, it is characterised in that: described cloud platform includes the immature content that network service resource and user generate.
3. utilize the method for allocating tasks of mass-rent service system described in claim 1, it is characterised in that comprise the following steps,
Step 1, user find the resource relevant to oneself problem in the network service resource of platform, without the resource that can directly utilize, then generate immature content, and user sends analysis request for described immature content to content analysis backstage；
Step 2, described analysis request are loaded static organ and are divided into the distributed task scheduling of a lot of fraction to ask, and distributed task scheduling request is transferred to task distribution server, are optimized distributed task scheduling request according to place；
Participant in step 3, participant's module obtains respective task from described task distribution server, stores the result into described user data storage server after completing task, and described participant is labeled with key word；
The result that task is distributed by step 4, domain expert's module by the knowledge of self exercises supervision, and will not meet the result described participant of return that user requires, the result meeting user's requirement submits to user；
Configuration file storehouse and metadatabase are fed back and are updated by step 5, user data storage server.
Method for allocating tasks the most according to claim 3, it is characterised in that: the process that is optimized of distributed task scheduling request according to place is by described in step 2:
In step 201, the anonymous region of calculating, the barycenter in all places is as desired distance d of participanti,j,
d i , j = d i s t ( ∫ z ∈ a i zf i ( z ) d z , l j )
Wherein aiFor the anonymous region in the Z of region, ljIt is the position of target j, fiZ () is aiThe probability density function of each participant in region, function dist is the Euclidean distance between any two points；
Step 202, find the participant-target of optimum cost benefit to and be each assigned to the other side, for a participant pi(i ∈ 1,2 ..., n}) and task object tj(j ∈ 1,2 ..., and m}), task is distributed to the cost benefit of the other side and is designated as∈ is minimum nonnegative number
WhereinIt it is the vector at target zone internal object j, it is desirable to the vector of target zone internal object k；
Step 203, iteration participant-target to rear, select the participant-target of optimum cost benefit to and update current target search scope, travel through all targets until the distance budget meeting target search scope or all of participant exhausts,
The cost benefit computing formula of each task becomes:
Wherein biIt is the distance budget of participant i, xI, jIt it is the j task of participant i.
CN201610144236.1A 2016-03-14 2016-03-14 Crowdsourcing service system based on anonymous places of cloud platform and task distribution method Withdrawn CN105825333A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610144236.1A CN105825333A (en) 2016-03-14 2016-03-14 Crowdsourcing service system based on anonymous places of cloud platform and task distribution method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610144236.1A CN105825333A (en) 2016-03-14 2016-03-14 Crowdsourcing service system based on anonymous places of cloud platform and task distribution method

Publications (1)

Publication Number Publication Date
CN105825333A true CN105825333A (en) 2016-08-03

Family

ID=56987269

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610144236.1A Withdrawn CN105825333A (en) 2016-03-14 2016-03-14 Crowdsourcing service system based on anonymous places of cloud platform and task distribution method

Country Status (1)

Country Link
CN (1) CN105825333A (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106651097A (en) * 2016-09-30 2017-05-10 深圳市华傲数据技术有限公司 Data collection method, data collection device and data collection server based on crowd sourcing
CN107360146A (en) * 2017-07-03 2017-11-17 深圳大学 One kind connects guaranteed secret protection space mass-rent task distribution system and method
CN107529655A (en) * 2017-08-29 2018-01-02 武汉大学 Space mission method of commerce, system and space flight mass-rent server based on mass-rent
CN108573337A (en) * 2017-03-10 2018-09-25 埃森哲环球解决方案有限公司 Operation distributes

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1851747A (en) * 2006-05-30 2006-10-25 杨云国 Network contest question solving method
CN104599084A (en) * 2015-02-12 2015-05-06 北京航空航天大学 Crowd calculation quality control method and device
CN105243501A (en) * 2015-10-13 2016-01-13 重庆大学 Spatial crowdsourcing network node position privacy protection method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1851747A (en) * 2006-05-30 2006-10-25 杨云国 Network contest question solving method
CN104599084A (en) * 2015-02-12 2015-05-06 北京航空航天大学 Crowd calculation quality control method and device
CN105243501A (en) * 2015-10-13 2016-01-13 重庆大学 Spatial crowdsourcing network node position privacy protection method

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106651097A (en) * 2016-09-30 2017-05-10 深圳市华傲数据技术有限公司 Data collection method, data collection device and data collection server based on crowd sourcing
CN108573337A (en) * 2017-03-10 2018-09-25 埃森哲环球解决方案有限公司 Operation distributes
CN107360146A (en) * 2017-07-03 2017-11-17 深圳大学 One kind connects guaranteed secret protection space mass-rent task distribution system and method
CN107360146B (en) * 2017-07-03 2021-03-26 深圳大学 Privacy protection space crowdsourcing task allocation system and method for receiving guarantee
CN107529655A (en) * 2017-08-29 2018-01-02 武汉大学 Space mission method of commerce, system and space flight mass-rent server based on mass-rent

Similar Documents

Publication Publication Date Title
Guo et al. Task allocation in spatial crowdsourcing: Current state and future directions
Wang et al. Truthful incentive mechanism with location privacy-preserving for mobile crowdsourcing systems
Xu et al. Incentive mechanism for multiple cooperative tasks with compatible users in mobile crowd sensing via online communities
Alsheikh et al. The accuracy-privacy trade-off of mobile crowdsensing
WO2019242331A1 (en) User behavior prediction method and apparatus, and behavior prediction model training method and apparatus
Borjigin et al. In broker we trust: A double-auction approach for resource allocation in NFV markets
Wu et al. Toward a real-time and budget-aware task package allocation in spatial crowdsourcing
US10891592B2 (en) Electronic job posting marketplace
Kaur et al. Deep‐Q learning‐based heterogeneous earliest finish time scheduling algorithm for scientific workflows in cloud
US20140358694A1 (en) Social media pricing engine
CN105825333A (en) Crowdsourcing service system based on anonymous places of cloud platform and task distribution method
CN106489165A (en) Future, the conversion of self-application was mated with selected content item
US20190057404A1 (en) Jobs forecasting
CN110008397A (en) A kind of recommended models training method and device
CN111008335A (en) Information processing method, device, equipment and storage medium
Gong Estimating participants for knowledge-intensive tasks in a network of crowdsourcing marketplaces
CN107710262A (en) The system and method being segmented using page script to the client session of website
CN109075987A (en) Optimize digital assembly analysis system
CN110720099A (en) System and method for providing recommendation based on seed supervised learning
CN108781223A (en) The data packet transfer optimization of data for content item selection
Ding et al. Truthful online double auctions for on-demand integrated ride-sourcing platforms
CN112862544A (en) Object information acquisition method and device and storage medium
CN110196949A (en) Information-pushing method, device, electronic equipment and computer-readable medium
Zhang et al. CAPR: context‐aware participant recruitment mechanism in mobile crowdsourcing
George et al. Hypervolume sen task scheduilng and multi objective deep auto encoder based resource allocation in cloud

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
WW01 Invention patent application withdrawn after publication
WW01 Invention patent application withdrawn after publication

Application publication date: 20160803