{"title":"设置与不准确的oracle对账","authors":"Mark Bilinski, Ryan Gabrys","doi":"10.1109/ICCNC.2017.7876279","DOIUrl":null,"url":null,"abstract":"In this work, we consider a variant of the set reconciliation problem where the estimate for the size of the symmetric difference may be inaccurate. Given this setup, we propose a new method to reconciling sets of data and we then compare our method to the Invertible Bloom Filter approach proposed by Eppstein et al. [2].","PeriodicalId":135028,"journal":{"name":"2017 International Conference on Computing, Networking and Communications (ICNC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Set reconciliation with an inaccurate oracle\",\"authors\":\"Mark Bilinski, Ryan Gabrys\",\"doi\":\"10.1109/ICCNC.2017.7876279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we consider a variant of the set reconciliation problem where the estimate for the size of the symmetric difference may be inaccurate. Given this setup, we propose a new method to reconciling sets of data and we then compare our method to the Invertible Bloom Filter approach proposed by Eppstein et al. [2].\",\"PeriodicalId\":135028,\"journal\":{\"name\":\"2017 International Conference on Computing, Networking and Communications (ICNC)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Computing, Networking and Communications (ICNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCNC.2017.7876279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computing, Networking and Communications (ICNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCNC.2017.7876279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this work, we consider a variant of the set reconciliation problem where the estimate for the size of the symmetric difference may be inaccurate. Given this setup, we propose a new method to reconciling sets of data and we then compare our method to the Invertible Bloom Filter approach proposed by Eppstein et al. [2].