{"title":"基于边缘计算的无线区块链网络资源交易与矿工竞争","authors":"Yuchen Zhou, Jian Chen, Lu Lyu, Bingtao He","doi":"10.23919/jcc.ea.2020-0701.202302","DOIUrl":null,"url":null,"abstract":"To promote the application of edge computing in wireless blockchain networks, this paper presents a business ecosystem, where edge computing is introduced to assist blockchain users in implementing the mining process. This paper exploits resource trading and miner competition to enable secure and efficient transactions in the presented business ecosystem. The resource trading problem is formulated as a Stackelberg game between miner candidates and edge computing servers, where computing, caching, and communication resources are jointly optimized to maximize the potential profit. Partial offloading is introduced to further enhance the system performance when compared with the existing work. We analyze the existence and uniqueness of the Nash equilibrium and Stackelberg equilibrium. Based on the optimization result, winners are selected from the set of miner candidates by bidding and constitute the mining network. Simulation results demonstrate that the proposal is able to improve the social welfare of blockchain miners, thus stimulating more blockchain users to join the mining network.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"1 1","pages":"187-201"},"PeriodicalIF":3.1000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Resource trading and miner competition in wireless blockchain networks with edge computing\",\"authors\":\"Yuchen Zhou, Jian Chen, Lu Lyu, Bingtao He\",\"doi\":\"10.23919/jcc.ea.2020-0701.202302\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To promote the application of edge computing in wireless blockchain networks, this paper presents a business ecosystem, where edge computing is introduced to assist blockchain users in implementing the mining process. This paper exploits resource trading and miner competition to enable secure and efficient transactions in the presented business ecosystem. The resource trading problem is formulated as a Stackelberg game between miner candidates and edge computing servers, where computing, caching, and communication resources are jointly optimized to maximize the potential profit. Partial offloading is introduced to further enhance the system performance when compared with the existing work. We analyze the existence and uniqueness of the Nash equilibrium and Stackelberg equilibrium. Based on the optimization result, winners are selected from the set of miner candidates by bidding and constitute the mining network. Simulation results demonstrate that the proposal is able to improve the social welfare of blockchain miners, thus stimulating more blockchain users to join the mining network.\",\"PeriodicalId\":9814,\"journal\":{\"name\":\"China Communications\",\"volume\":\"1 1\",\"pages\":\"187-201\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"China Communications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.23919/jcc.ea.2020-0701.202302\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Communications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.23919/jcc.ea.2020-0701.202302","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
Resource trading and miner competition in wireless blockchain networks with edge computing
To promote the application of edge computing in wireless blockchain networks, this paper presents a business ecosystem, where edge computing is introduced to assist blockchain users in implementing the mining process. This paper exploits resource trading and miner competition to enable secure and efficient transactions in the presented business ecosystem. The resource trading problem is formulated as a Stackelberg game between miner candidates and edge computing servers, where computing, caching, and communication resources are jointly optimized to maximize the potential profit. Partial offloading is introduced to further enhance the system performance when compared with the existing work. We analyze the existence and uniqueness of the Nash equilibrium and Stackelberg equilibrium. Based on the optimization result, winners are selected from the set of miner candidates by bidding and constitute the mining network. Simulation results demonstrate that the proposal is able to improve the social welfare of blockchain miners, thus stimulating more blockchain users to join the mining network.
期刊介绍:
China Communications (ISSN 1673-5447) is an English-language monthly journal cosponsored by the China Institute of Communications (CIC) and IEEE Communications Society (IEEE ComSoc). It is aimed at readers in industry, universities, research and development organizations, and government agencies in the field of Information and Communications Technologies (ICTs) worldwide.
The journal's main objective is to promote academic exchange in the ICTs sector and publish high-quality papers to contribute to the global ICTs industry. It provides instant access to the latest articles and papers, presenting leading-edge research achievements, tutorial overviews, and descriptions of significant practical applications of technology.
China Communications has been indexed in SCIE (Science Citation Index-Expanded) since January 2007. Additionally, all articles have been available in the IEEE Xplore digital library since January 2013.