{"title":"Research of semantic caching for LDQ in mobile network","authors":"Zhichao Li, Pilian He, Ming Lei","doi":"10.1109/ICEBE.2005.104","DOIUrl":null,"url":null,"abstract":"Location-dependent query is becoming very popular in mobile environments. To improve system performance, many semantic cache models are proposed. In this paper, we first define a new structure of semantic segments index. Then we analyze the detailed query processing and FAR algorithm. For overcoming the shortage of predicting future location in FAR, we propose a new improved algorithm (RBF-FAR) as replacement policy, which use RBFNN to predicate next location instead of velocity in FAR. Using this new replacement policy, we propose a new model for LDQ semantic cache. The experiment results show that new model, on the basis of RBF-FAR, is more flexible and effective at reducing average response time network-load used in LDQ than FAR model","PeriodicalId":118472,"journal":{"name":"IEEE International Conference on e-Business Engineering (ICEBE'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on e-Business Engineering (ICEBE'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEBE.2005.104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Location-dependent query is becoming very popular in mobile environments. To improve system performance, many semantic cache models are proposed. In this paper, we first define a new structure of semantic segments index. Then we analyze the detailed query processing and FAR algorithm. For overcoming the shortage of predicting future location in FAR, we propose a new improved algorithm (RBF-FAR) as replacement policy, which use RBFNN to predicate next location instead of velocity in FAR. Using this new replacement policy, we propose a new model for LDQ semantic cache. The experiment results show that new model, on the basis of RBF-FAR, is more flexible and effective at reducing average response time network-load used in LDQ than FAR model