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Incentive mechanism design for edge‐cloud collaboration in mobile crowd sensing
Author(s) -
Li Zhuo,
Zhang Lihan,
Chen Xin
Publication year - 2021
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.4105
Subject(s) - stackelberg competition , cloud computing , server , computer science , incentive , game theory , enhanced data rates for gsm evolution , mechanism design , non cooperative game , double auction , distributed computing , microeconomics , computer network , artificial intelligence , economics , operating system , common value auction
In this article, we propose a pricing‐based incentive mechanism for edge‐cloud collaboration (PIM‐EC) in mobile crowd sensing. In PIM‐EC, data can be exchanged among different regions with the support of edge‐cloud servers, which improves the data efficiency. For the utility conflicts between mobile sensing users and cloud servers in the traditional one‐stage game, we design a two‐stage game which includes the bargaining game between users and edge‐cloud servers, as well as a data trading game among different edge‐cloud servers deployed in different regions. For the first stage game, based on Stackelberg game model and Rubinstein bargaining model, we design a finite‐period dynamic bargaining algorithm. For the second stage game, based on the optimal auction mechanism and using the augmented Lagrange multiplier method, a quasi‐Newton iterative pricing algorithm is proposed. We investigate the performance of PIM‐EC through simulations. Compared with SWMA and IMC‐SS, the social welfare of PIM‐EC is increased by 41% and 29%, respectively.