{"title":"LHT: A Low-Maintenance Indexing Scheme over DHTs","authors":"Y. Tang, Shuigeng Zhou","doi":"10.1109/ICDCS.2008.61","DOIUrl":null,"url":null,"abstract":"DHT is a widely-used building block in P2P systems, and complex queries are gaining popularity in P2P applications. To support efficient query processing over DHTs, effective indexing structures are essential. Recently, a number of indexing schemes have been proposed. However, these schemes have focused on improving query efficiency, and as a trade-off, sacrificed maintenance efficiency - an important performance measure in the P2P context, where frequent data updating and high peer dynamism are typically incurred. In this paper, we propose LHT, a Low maintenance Hash Tree, for efficient data indexing over DHTs. LHT employs a novel naming function and a tree summarization strategy to gracefully distribute its index structure. It is adaptable to any DHT substrates, and is easy to be implemented and deployed. Experiments show that in comparison with the state-of-the-art indexing technique, LHT saves up to 75% (at least 50%) maintenance cost, and achieves better performance for exact-match queries and range queries.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 The 28th International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2008.61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
DHT is a widely-used building block in P2P systems, and complex queries are gaining popularity in P2P applications. To support efficient query processing over DHTs, effective indexing structures are essential. Recently, a number of indexing schemes have been proposed. However, these schemes have focused on improving query efficiency, and as a trade-off, sacrificed maintenance efficiency - an important performance measure in the P2P context, where frequent data updating and high peer dynamism are typically incurred. In this paper, we propose LHT, a Low maintenance Hash Tree, for efficient data indexing over DHTs. LHT employs a novel naming function and a tree summarization strategy to gracefully distribute its index structure. It is adaptable to any DHT substrates, and is easy to be implemented and deployed. Experiments show that in comparison with the state-of-the-art indexing technique, LHT saves up to 75% (at least 50%) maintenance cost, and achieves better performance for exact-match queries and range queries.