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A Decentralized Prediction Market Platform Based on Blockchain and Masternode Technologies

A Decentralized Prediction Market Platform Based on Blockchain and Masternode Technologies

作     者:Zhen Wang Zhen Wang

作者机构:School of Computer Science and EngineeringHuizhou University46 Yanda RoadHuizhouChina 

出 版 物:《China Communications》 (中国通信(英文版))

年 卷 期:2020年第17卷第9期

页      面:25-33页

核心收录:

学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

基  金:supported by the Doctoral Research Fund of Huizhou University(2018JB007) the Blue Fire Plan Foundation of China(CXZJHZ201704) 

主  题:prediction market decentralization blockchain masternode mobile edged computing 

摘      要:Prediction market can help to trade the outcome of events,which is very useful for risk hedging,especially when people are making business ***,the traditional prediction market is centralized,which means the platform is completely controlled by just one person or *** centralization has bad influence on the platform to obtaining trust from massive *** it is important for the prediction market industry to decentralize the traditional platform into a decentralized one,and get its control from few person and give it back to a lot of people in the prediction market *** is a very promising technology to make it true as it is a popular decentralizing ***,existing blockchain technologies like Bitcoin or Ethernum bring about new problems like high energy consumption,expensive fee,and very low system capacity,which is not suitable for the current prediction *** solve these problems,we propose to combine masternode technology together with blockchain to serve as a decentralized node,and each masternode is deployed and running on an edge server in mobile edge *** network of masternodes serves together as the decentralized prediction market *** we know,it is not easy to run a *** the number of masternodes is much less than the number of complete nodes of the *** a result,it is easier to reach the consensus among these *** analysis and experimental results show that our proposed method is useful.

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