Wenliang Du, Jing Jia, M. Mangal, Mummoorthy Murugesan
{"title":"Uncheatable grid computing","authors":"Wenliang Du, Jing Jia, M. Mangal, Mummoorthy Murugesan","doi":"10.1109/ICDCS.2004.1281562","DOIUrl":null,"url":null,"abstract":"Grid computing is a type of distributed computing that has shown promising applications in many fields. A great concern in grid computing is the cheating problem described in the following: a participant is given D = {x/sub 1/,...,x/sub n/}, it needs to compute f(x) for all x/spl isin/D and return the results of interest to the supervisor. How does the supervisor efficiently ensure that the participant has computed f(x) for all the inputs in D, rather than a subset of it? If participants get paid for conducting the task, there are incentives for cheating. We propose a novel scheme to achieve the uncheatable grid computing. Our scheme uses a sampling technique and the Merkle-tree based commitment technique to achieve efficient and viable uncheatable grid computing.","PeriodicalId":348300,"journal":{"name":"24th International Conference on Distributed Computing Systems, 2004. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"169","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"24th International Conference on Distributed Computing Systems, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2004.1281562","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 169
Abstract
Grid computing is a type of distributed computing that has shown promising applications in many fields. A great concern in grid computing is the cheating problem described in the following: a participant is given D = {x/sub 1/,...,x/sub n/}, it needs to compute f(x) for all x/spl isin/D and return the results of interest to the supervisor. How does the supervisor efficiently ensure that the participant has computed f(x) for all the inputs in D, rather than a subset of it? If participants get paid for conducting the task, there are incentives for cheating. We propose a novel scheme to achieve the uncheatable grid computing. Our scheme uses a sampling technique and the Merkle-tree based commitment technique to achieve efficient and viable uncheatable grid computing.