Abstract
Delegation computing is a calculation protocol between non-cooperative participants, and its results are influenced by the participant’s choice of behavior. The goal of this paper is to solve the problem of high communication overhead in traditional delegation computing schemes. Combining the advantages of information theory and game theory, we propose a rational delegation computing scheme, which guarantees the correctness of the calculation results through the participant utility function. First, by analyzing the participant behavior strategy, we design the game model, which includes the participant set, information set, behavior strategy set and utility function. Second, according to the combination of Nash equilibrium and channel capacity limit in the game model, we construct a rational delegation computing scheme in this paper. Finally, we analyze and prove the scheme. When both the delegation party and computing party choose the honesty strategy, their utility reaches the maximum, that is, the global can reach the Nash equilibrium state, and the calculation efficiency has also been improved.
Y. Tian—Supported by organization x.
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Acknowledgement
We would like to thank the anonymous reviewers for their valuable suggestions. This work is supported by The National Natural Science Foundation of China (Grant No. 61662009, 61772008); Science and Technology Major Support Program of Guizhou Province (Grant No. 20183001); Guizhou provincial science and technology plan project (Grant No. [2017]5788); Ministry of Education - China Mobile Research Fund Project (Grant No. MCM20170401); Guizhou University Cultivation Project (Grant No. [2017]5788) Research on Block Data Fusion Analysis Theory and Security Management Model of Data Sharing Application No. U1836205 Research on Key Technologies of Blockchain for Big Data Applications Grant No. [2019]1098 for their helpful comments.
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Li, Q., Tian, Y. (2020). Rational Delegation Computing Using Information Theory and Game Theory Approach. In: Ro, Y., et al. MultiMedia Modeling. MMM 2020. Lecture Notes in Computer Science(), vol 11962. Springer, Cham. https://doi.org/10.1007/978-3-030-37734-2_54
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DOI: https://doi.org/10.1007/978-3-030-37734-2_54
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