{"title":"FIFO indexes for decomposable problems","authors":"Cheng Sheng, Yufei Tao","doi":"10.1145/1989284.1989291","DOIUrl":null,"url":null,"abstract":"This paper studies first-in-first-out (FIFO) indexes, each of which manages a dataset where objects are deleted in the same order as their insertions. We give a technique that converts a static data structure to a FIFO index for all decomposable problems, provided that the static structure can be constructed efficiently. We present FIFO access methods to solve several problems including half-plane search, nearest neighbor search, and extreme-point search. All of our structures consume linear space, and have optimal or near-optimal query cost.","PeriodicalId":92118,"journal":{"name":"Proceedings of the ... ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems","volume":"78 1","pages":"25-35"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1989284.1989291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper studies first-in-first-out (FIFO) indexes, each of which manages a dataset where objects are deleted in the same order as their insertions. We give a technique that converts a static data structure to a FIFO index for all decomposable problems, provided that the static structure can be constructed efficiently. We present FIFO access methods to solve several problems including half-plane search, nearest neighbor search, and extreme-point search. All of our structures consume linear space, and have optimal or near-optimal query cost.