{"title":"几何网络中数据管理的近似算法","authors":"Dongmei Xing","doi":"10.1109/KAMW.2008.4810629","DOIUrl":null,"url":null,"abstract":"An approximate strategy is designed for the static data management in geometric network. If all parameters is given, a constant approximation ratio is achieved. Here, we suppose that the link cost don't satisfy triangle inequality, but the ratio of the maximum link cost to the minimum value is known.","PeriodicalId":375613,"journal":{"name":"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop","volume":"178 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Approximation Algorithms for Data management in Geometric Network\",\"authors\":\"Dongmei Xing\",\"doi\":\"10.1109/KAMW.2008.4810629\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approximate strategy is designed for the static data management in geometric network. If all parameters is given, a constant approximation ratio is achieved. Here, we suppose that the link cost don't satisfy triangle inequality, but the ratio of the maximum link cost to the minimum value is known.\",\"PeriodicalId\":375613,\"journal\":{\"name\":\"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop\",\"volume\":\"178 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KAMW.2008.4810629\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KAMW.2008.4810629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximation Algorithms for Data management in Geometric Network
An approximate strategy is designed for the static data management in geometric network. If all parameters is given, a constant approximation ratio is achieved. Here, we suppose that the link cost don't satisfy triangle inequality, but the ratio of the maximum link cost to the minimum value is known.