scholarly journals The User Participation Incentive Mechanism of Mobile Crowdsensing Network Based on User Threshold

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Hua Su ◽  
Qianqian Wu ◽  
Xuemei Sun ◽  
Ning Zhang
Keyword(s):  
Large Scale ◽  
Incentive Mechanism ◽  
User Participation ◽  
Task Completion ◽  
Processing Efficiency ◽  
Mobile Crowdsensing ◽  
Budget Control ◽  
Experiment Validation ◽  
Incentive Strategies ◽  
Incentive Strategy

Mobile crowdsensing (MCS) network means completing large-scale and complex sensing tasks in virtue of the mobile devices of ordinary users. Therefore, sufficient user participation plays a basic role in MCS. On the basis of studying and analyzing the strategy of user participation incentive mechanism, this paper proposes the user threshold-based cognition incentive strategy against the shortcomings of existing incentive strategies, such as task processing efficiency and budget control. The user threshold and the budget of processing subtasks are set at the very beginning. The platform selects the user set with the lowest threshold, and the best user for processing tasks according to users’ budget. The incentive cost of the corresponding users is calculated based on the user threshold at last. In conclusion, through the experiment validation and comparison with the existing user participation incentive mechanism, it was found that the user threshold-based incentive strategy is advantageous in improving the proportion of task completion and reducing the platform’s budget cost.

scholarly journals A Blockchain-Based Location Privacy Protection Incentive Mechanism in Crowd Sensing Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3894 ◽  
Author(s):  
Bing Jia ◽  
Tao Zhou ◽  
Wuyungerile Li ◽  
Zhenchang Liu ◽  
Jiantao Zhang
Keyword(s):  
Cloud Computing ◽  
Privacy Protection ◽  
Large Scale ◽  
Location Privacy ◽  
Incentive Mechanism ◽  
User Participation ◽  
Crowd Sensing ◽  
The Incentive Mechanism ◽  
Crowd Sensing Networks ◽  
Location Privacy Protection

Crowd sensing is a perception mode that recruits mobile device users to complete tasks such as data collection and cloud computing. For the cloud computing platform, crowd sensing can not only enable users to collaborate to complete large-scale awareness tasks but also provide users for types, social attributes, and other information for the cloud platform. In order to improve the effectiveness of crowd sensing, many incentive mechanisms have been proposed. Common incentives are monetary reward, entertainment & gamification, social relation, and virtual credit. However, there are rare incentives based on privacy protection basically. In this paper, we proposed a mixed incentive mechanism which combined privacy protection and virtual credit called a blockchain-based location privacy protection incentive mechanism in crowd sensing networks. Its network structure can be divided into three parts which are intelligence crowd sensing networks, confusion mechanism, and blockchain. We conducted the experiments in the campus environment and the results shows that the incentive mechanism proposed in this paper has the efficacious effect in stimulating user participation.

Topic-aware Incentive Mechanism for Task Diffusion in Mobile Crowdsourcing through Social Network

2022 ◽  
Vol 22 (1) ◽  
pp. 1-23
Author(s):  
Jia Xu ◽  
Yuanhang Zhou ◽  
Gongyu Chen ◽  
Yuqing Ding ◽  
Dejun Yang ◽  
...  
Keyword(s):  
Social Network ◽  
Diffusion Model ◽  
Large Scale ◽  
Incentive Mechanism ◽  
Estimation Algorithm ◽  
Task Completion ◽  
Incentive Mechanisms ◽  
Mobile Crowdsourcing ◽  
Real World Datasets ◽  
Budget Feasible

Crowdsourcing has become an efficient paradigm to utilize human intelligence to perform tasks that are challenging for machines. Many incentive mechanisms for crowdsourcing systems have been proposed. However, most of existing incentive mechanisms assume that there are sufficient participants to perform crowdsourcing tasks. In large-scale crowdsourcing scenarios, this assumption may be not applicable. To address this issue, we diffuse the crowdsourcing tasks in social network to increase the number of participants. To make the task diffusion more applicable to crowdsourcing system, we enhance the classic Independent Cascade model so the influence is strongly connected with both the types and topics of tasks. Based on the tailored task diffusion model, we formulate the Budget Feasible Task Diffusion ( BFTD ) problem for maximizing the value function of platform with constrained budget. We design a parameter estimation algorithm based on Expectation Maximization algorithm to estimate the parameters in proposed task diffusion model. Benefitting from the submodular property of the objective function, we apply the budget-feasible incentive mechanism, which satisfies desirable properties of computational efficiency, individual rationality, budget-feasible, truthfulness, and guaranteed approximation, to stimulate the task diffusers. The simulation results based on two real-world datasets show that our incentive mechanism can improve the number of active users and the task completion rate by 9.8% and 11%, on average.

scholarly journals INVESTIGATION OF THE PROCESS OF DOUBLE-SIDED GRINDING OF TORCHES OF PUSHERS WITH DIFFERENT DIAMETRERS

2018 ◽  
pp. 86-93
Author(s):  
Oleksandr Lytvyn ◽  
Kalchenko Dmytro Kalchenko
Keyword(s):  
Large Scale ◽  
Maximum Diameter ◽  
Grinding Wheel ◽  
Universal Method ◽  
Grinding Wheels ◽  
Processing Efficiency ◽  
Agricultural Engineering ◽  
Grinding Machines ◽  
Precision Of Processing ◽  
Different Diameters

Urgency of the research. In machine tools, automotive, agricultural engineering, manufacturing, where it is necessary to ensure high accuracy of surfaces of parts with different diameters of faces, it is required to adhere to high requirements for the quality of geometric sizes, roughness and accuracy of molding. Target setting. Grinding of end surfaces of parts with different diameters of faces, is carried out on two-sided end-grinding machines. The specific gravity of grinding in the total complexity of mechanical processing is constantly increasing and at the present stage it is about 30 % in the machine tool industry, in the automotive industry more than 38% of the total complexity of processing. Actual scientific researches and issues analysis. On the two-sided end-grinding machines of the Saturn company (Germany) the processing of round ends of parts is done with a circular feed to the processing area. Abrasive wheels are used without calibrating plots, which requires a lot of processing to obtain the required precision, which reduces the productivity of grinding. The disadvantage of the method is that the processing of parts with different face diameters is not considered. Uninvestigated parts of general matters defining. It is necessary to improve the processing efficiency of parts by developing the methods of two-sided polishing of the ends of pushers with different diameters oriented grinding wheels with and with-out calibrating sections, and also the rotation or without rotation of the workpiece on the calibration section, at least one revo-lution. The research objective. Improving the accuracy of finishing the end surfaces of parts of various diameters with grinding wheels, is achieved by the fact that the shaping of the ends of the smaller diameter is performed by the maximum diameter of the flat end of one circle, and the shaping of the end face of a larger diameter – the calibration section of the second circle, the length of which is equal to the diameter of the larger end and filled with diamond pencil, which moves along a radius, which coincides with the radius of the location of the axes of the parts in the feed drum. The statement of basic materials. In order to ensure the processing of parts in one pass and the necessary precision of processing, in large-scale and mass production, a grinding method oriented circles with calibrated sections with one-sided arrangement of ends of one diameter is used. The calibration sections are then made of different lengths, depending on the diameter, respectively, larger and smaller. Conclusions. The universal method of practical application of model of accuracy of shaping of ends of parts of different diameters, oriented grinding circles with and without calibration plots has been suggested. The presented method simplifies the grinding of the grinding wheel. It does not require special editing and allows to use regular editing.

Semantic Synchronization in B2B Transactions

2010 ◽  
pp. 1518-1542
Author(s):  
Janina Fengel ◽  
Heiko Paulheim ◽  
Michael Rebstock
Keyword(s):  
Large Scale ◽  
Business Processes ◽  
User Participation ◽  
Ontology Matching ◽  
Ontological Engineering ◽  
Business Information Systems ◽  
Business Partners ◽  
Business Information ◽  
Mapping Technology

Despite the development of e-business standards, the integration of business processes and business information systems is still a non-trivial issue if business partners use different e-business standards for formatting and describing information to be processed. Since those standards can be understood as ontologies, ontological engineering technologies can be applied for processing, especially ontology matching for reconciling them. However, as e-business standards tend to be rather large-scale ontologies, scalability is a crucial requirement. To serve this demand, we present our ORBI Ontology Mediator. It is linked with our Malasco system for partition-based ontology matching with currently available matching systems, which so far do not scale well, if at all. In our case study we show how to provide dynamic semantic synchronization between business partners using different e-business standards without initial ramp-up effort, based on ontological mapping technology combined with interactive user participation.

scholarly journals Incentivizing for Truth Discovery in Edge-assisted Large-scale Mobile Crowdsensing

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 805
Author(s):  
Jia Xu ◽  
Shangshu Yang ◽  
Weifeng Lu ◽  
Lijie Xu ◽  
Dejun Yang
Keyword(s):  
Large Scale ◽  
Computationally Efficient ◽  
Reverse Auction ◽  
Mobile Crowdsensing ◽  
Computing Paradigm ◽  
Truth Discovery ◽  
Estimation Precision ◽  
Discovery Stage ◽  
Budget Feasible ◽  
Great Development

The recent development of human-carried mobile devices has promoted the great development of mobile crowdsensing systems. Most existing mobile crowdsensing systems depend on the crowdsensing service of the deep cloud. With the increasing scale and complexity, there is a tendency to enhance mobile crowdsensing with the edge computing paradigm to reduce latency and computational complexity, and improve the expandability and security. In this paper, we propose an integrated solution to stimulate the strategic users to contribute more for truth discovery in the edge-assisted mobile crowdsensing. We design an incentive mechanism consisting of truth discovery stage and budget feasible reverse auction stage. In truth discovery stage, we estimate the truth for each task in both deep cloud and edge cloud. In budget feasible reverse auction stage, we design a greedy algorithm to select the winners to maximize the quality function under the budget constraint. Through extensive simulations, we demonstrate that the proposed mechanism is computationally efficient, individually rational, truthful, budget feasible and constant approximate. Moreover, the proposed mechanism shows great superiority in terms of estimation precision and expandability.

scholarly journals An ANN-Based Approach for Real-Time Scheduling in Cloud Manufacturing

2020 ◽  
Vol 10 (7) ◽  
pp. 2491
Author(s):  
Shengkai Chen ◽  
Shuliang Fang ◽  
Renzhong Tang
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Large Scale ◽  
Cloud Manufacturing ◽  
Smart Manufacturing ◽  
Matching Task ◽  
Task Completion ◽  
Ann Model ◽  
Real Time Scheduling ◽  
Time Scheduling

The cloud manufacturing platform needs to allocate the endlessly emerging tasks to the resources scattered in different places for processing. However, this real-time scheduling problem in the cloud environment is more complicated than that in a traditional workshop because constraints, such as type matching, task precedence, resource occupation, and logistics duration, need to be met, and the internal manufacturing plan of providers must also be considered. Since the platform aggregates massive manufacturing resources to serve large-scale manufacturing tasks, the space of feasible solutions is huge, resulting in many conventional search algorithms no longer being applicable. In this paper, we considered resource allocation as the key procedure for real-time scheduling, and an ANN (Artificial Neural Network) based model is established to predict the task completion status for resource allocation among candidates. The trained ANN model has high prediction accuracy, and the ANN-based scheduling approach performs better than the preferred method in terms of the optimization objectives, including total cost, service satisfaction, and make-span. In addition, the proposed approach has potential in the application for smart manufacturing or Industry 4.0 because of its high response performance and good scalability.

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