scholarly journals An Incentive Mechanism in Mobile Crowdsourcing Based on Multi-Attribute Reverse Auctions

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3453 ◽  
Author(s):  
Ying Hu ◽  
Yingjie Wang ◽  
Yingshu Li ◽  
Xiangrong Tong
Keyword(s):  
Incentive Mechanism ◽  
Budget Balance ◽  
Selection Algorithm ◽  
Reverse Auction ◽  
Mobile Crowdsourcing ◽  
Trust Degree ◽  
Worker Selection ◽  
Bidding Price ◽  
Good Reputation

In order to avoid malicious competition and select high quality crowd workers to improve the utility of crowdsourcing system, this paper proposes an incentive mechanism based on the combination of reverse auction and multi-attribute auction in mobile crowdsourcing. The proposed online incentive mechanism includes two algorithms. One is the crowd worker selection algorithm based on multi-attribute reverse auction that adopts dynamic threshold to make an online decision for whether accept a crowd worker according to its attributes. Another is the payment determination algorithm which determines payment for a crowd worker based on its reputation and quality of sensing data, that is, a crowd worker can get payment equal to the bidding price before performing task only if his reputation reaches good reputation threshold, otherwise he will get payment based on his data sensing quality. We prove that our proposed online incentive mechanism has the properties of computational efficiency, individual rationality, budget-balance, truthfulness and honesty. Through simulations, the efficiency of our proposed online incentive mechanism is verified which can improve the efficiency, adaptability and trust degree of the mobile crowdsourcing system.

A worker-selection incentive mechanism for optimizing platform-centric mobile crowdsourcing systems

2020 ◽  
Vol 171 ◽  
pp. 107144 ◽  
Author(s):  
Yingjie Wang ◽  
Yang Gao ◽  
Yingshu Li ◽  
Xiangrong Tong
Keyword(s):  
Incentive Mechanism ◽  
Mobile Crowdsourcing ◽  
Worker Selection

scholarly journals Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Sajeeb Saha ◽  
Md. Ahsan Habib ◽  
Tamal Adhikary ◽  
Md. Abdur Razzaque ◽  
Md. Mustafizur Rahman ◽  
...  
Keyword(s):  
Mobile Device ◽  
Quality Of Experience ◽  
Incentive Mechanism ◽  
Mobile Device Cloud

A Relay Selection Algorithm Based on User Trust Degree for D2D Communications

2021 ◽  
Author(s):  
Xiaobin Li ◽  
Haoran Liu
Keyword(s):  
Success Rate ◽  
Social Relationship ◽  
Relay Node ◽  
D2d Communications ◽  
Relay Nodes ◽  
Trust Degree ◽  
Relay Communication ◽  
Relay Selection Algorithm ◽  
User Trust

Abstract The emergence of 5G has promoted the rapid development of the Internet of Things(IOT), the dramatic increasing of mobile equipment has led to the increasing shortage of spectrum resources, D2D(Device-to-Device) communication technology is widely concerned for its ability to improve the utilization of spectrum resources. In order to expand the communication scope, relay nodes are introduced into D2D communications, as the third party of D2D relay communication, the quality of relay nodes directly affects the quality of communication process. In order to make more users willing to participate in relay communication, social relationship is introduced into D2D relay communication, However, as an explicit relationship between people, the function of social relationship in D2D communication is limited by the mobility of users and the variability of communication scenarios. In order to find a more reli­able relay node and upgrade the connection success rate of D2D relay communication, implicit social relationship between the users need to be mined. Aiming at that, user trust degree (UTD) is established in this paper. By combining the explicit relationship which is called the social connectivity degree with the implicit social relationship called the interest similarity degree, and considering the user’s movement, a relay selection algorithm is presented to help sender find a relay node with a deeper user trust, which can increase the user’s willingness to participate in D2D relay communication and upgrade the success rate of communication connection, so this algorithm can ensure the security of the relay node and can improve the throughput performance. Simulation results show that this algorithm can increase the success rate of connection, improve the overall throughput of the system and improve the user's communication expe­rience.

scholarly journals IMPACT OF SERVICE QUALITY, TRUST, AND CUSTOMER SATISFACTION ON CUSTOMER LOYALTY IN PT MEGA MANUNGGAL PROPERTY TBK

2019 ◽  
Vol 6 (1) ◽  
pp. 33-42
Author(s):  
Maria Anna Stefanie ◽  
Badikenita Sitepu
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Customer Loyalty ◽  
Primary Data ◽  
Distribution Method ◽  
Good Reputation ◽  
Customer Trust ◽  
The Impact

In order to compete, survive, and grow the company is required to provide a good quality services to meet the needs and desires of its customers. Companies must be able to maintain a good reputation in the eyes of its customers. A good quality services will tend to give more satisfaction to the customers who use the services of the company. With emphasis on good service it will build a long-term profitable relationships with customers while also achieving customer loyalty. Therefore, this study is aiming to determine the importance of the impact of service quality, trust and customer satisfaction at PT Mega Manunggal Tbk Property in an effort to improve customer loyalty which will affect the company's survival. A questionnaire distribution method chosen in this study is to collect primary data. Completed questionnaires designed and distributed or disseminated to all customers. SPSS for windows has been used to process the primary data.Thefindings showed that there is a significant relationship between service quality and customer loyalty, meaning that if the quality of service increases, customer loyalty will also increase.There is a significant influence between customer trust and customerloyalty,meaning that if the customer trust increases, customer loyalty will also increase.

Study on Incentive Mechanism of MRCTM Closed-Loop Supply Chain Based on the Uncertainty Quality

2010 ◽  
Vol 108-111 ◽  
pp. 341-346
Author(s):  
Huang Ling
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Conversion Factor ◽  
Incentive Mechanism ◽  
Incentive Payment ◽  
Closed Loop Supply Chain ◽  
Optimal Analysis ◽  
The Incentive Mechanism ◽  
Product Recycling

In this paper, the MRCTM model of closed-loop supply chain was investigated. An effective incentive mechanism that considered the uncertainty quality of product recycling was designed by the introduction of brand conversion factor. The author made an optimal analysis of the incentive mechanism. Moreover, the influence of different parameters, such as quality and brand to the fixed reward and the unit incentive payment was analyzed and some useful results were obtained.

scholarly journals Multi-Dimensional Incentive Mechanism in Mobile Crowdsourcing with Moral Hazard

2018 ◽  
Vol 17 (3) ◽  
pp. 604-616 ◽  
Author(s):  
Yanru Zhang ◽  
Yunan Gu ◽  
Miao Pan ◽  
Nguyen H. Tran ◽  
Zaher Dawy ◽  
...  
Keyword(s):  
Moral Hazard ◽  
Incentive Mechanism ◽  
Mobile Crowdsourcing

scholarly journals A Joint Constraint Incentive Mechanism Algorithm Utilizing Coverage and Reputation for Mobile Crowdsensing

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4478
Author(s):  
Jing Zhang ◽  
Xiaoxiao Yang ◽  
Xin Feng ◽  
Hongwei Yang ◽  
An Ren
Keyword(s):  
Information Quality ◽  
Stackelberg Game ◽  
Incentive Mechanism ◽  
Response Strategy ◽  
Mobile Users ◽  
Target Area ◽  
Mobile Crowdsensing ◽  
Sensing Data ◽  
Priority Order

Selection of the optimal users to maximize the quality of the collected sensing data within a certain budget range is a crucial issue that affects the effectiveness of mobile crowdsensing (MCS). The coverage of mobile users (MUs) in a target area is relevant to the accuracy of sensing data. Furthermore, the historical reputation of MUs can reflect their previous behavior. Therefore, this study proposes a coverage and reputation joint constraint incentive mechanism algorithm (CRJC-IMA) based on Stackelberg game theory for MCS. First, the location information and the historical reputation of mobile users are used to select the optimal users, and the information quality requirement will be satisfied consequently. Second, a two-stage Stackelberg game is applied to analyze the sensing level of the mobile users and obtain the optimal incentive mechanism of the server center (SC). The existence of the Nash equilibrium is analyzed and verified on the basis of the optimal response strategy of mobile users. In addition, mobile users will adjust the priority of the tasks in time series to enable the total utility of all their tasks to reach a maximum. Finally, the EM algorithm is used to evaluate the data quality of the task, and the historical reputation of each user will be updated accordingly. Simulation experiments show that the coverage of the CRJC-IMA is higher than that of the CTSIA. The utility of mobile users and SC is higher than that in STD algorithms. Furthermore, the utility of mobile users with the adjusted task priority is greater than that without a priority order.

A Network Selection Algorithm with Parallel Transmission Based on MADM

2014 ◽  
Vol 556-562 ◽  
pp. 4606-4611 ◽  
Author(s):  
Li Na Zhang ◽  
Qi Zhu
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Heterogeneous Wireless Networks ◽  
Network Selection ◽  
Selection Algorithm ◽  
Decision Matrix ◽  
Parallel Transmission ◽  
User Throughput ◽  
Selection Algorithms

At present, most of researches on network selection algorithms are focused on single access. To support seamless mobility and provide better quality of service in heterogeneous wireless networks, this paper proposes a network selection algorithm with parallel transmission based on MADM. In the algorithm, we firstly determine all available wireless networks and consider every subset of these networks as a network scheme. Then we obtain aggregation attributes of every scheme and determine the alternative network schemes. Finally, we build the decision matrix of multiple attributes and determine the optimal scheme by using GRA. Simulation results show that the proposed algorithm can obviously improve user quality of service, improve user throughput, reduce power consumption and price cost per bit.

Domain-Based Level Trust Manage Model

2011 ◽  
Vol 204-210 ◽  
pp. 83-87
Author(s):  
Xiao Xue Ma ◽  
Zi Xian Wang ◽  
Jing Bian ◽  
Fei Liu
Keyword(s):  
Quality Of Service ◽  
Service Provider ◽  
Domain Model ◽  
Human Society ◽  
Accurate Assessment ◽  
Trust Degree ◽  
Simulation Results ◽  
The Difference ◽  
Relationship Of

Draw on the trust relationship of human society, domain model and domain trust are introduced to build domain-based level trust manage model (DLTMM). In various domains, according to physical services characteristics of their own, entities abstract representative attribution. According to their preferences the service requester preferences comprehensive evaluate the service attributions, and to determines whether transaction; After trading, the service requester will calculate the difference degree of quality of service according to the actual quality of service and the claimed quality of service, and then judge the trust degree of service provider. The simulation results show that the model can more accurate assessment of the trust entity, to some extent effective against malicious attacks, which proves the validity and accuracy of the model.

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