{"title":"NQ/ATP:数据中心网络中大规模聚合查询的体系结构支持","authors":"Yixi Chen, Wenfei Wu, Shan-Hsiang Shen, Ying Zhang","doi":"10.1109/IWQoS54832.2022.9812906","DOIUrl":null,"url":null,"abstract":"Network queries become increasingly challenging for online service providers with massive network devices and massive network queries due to the tradeoff between system scale and query granularity. We re-architect the traditional three-tier architecture, i.e., data collection, data storage, and data query, for aggregate queries, and build a system named NQ/ATP. NQ/ATP offloads the aggregation operation in network queries onto network switches, which accelerates the query execution and frees up network resources. NQ/ATP further devises a route learning mechanism, query hierarchy load balancing policy, and hierarchy clustering mechanism to save forwarding table entries on switches, which better supports massive queries. The evaluation shows that NQ/ATP can support network aggregate queries with higher capacity, less traffic volume, finer granularity, and better scalability than traditional three-tier polling architectures. The three optimizations can effectively reduce the forwarding table usage by up to 97.55%.","PeriodicalId":353365,"journal":{"name":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NQ/ATP: Architectural Support for Massive Aggregate Queries in Data Center Networks\",\"authors\":\"Yixi Chen, Wenfei Wu, Shan-Hsiang Shen, Ying Zhang\",\"doi\":\"10.1109/IWQoS54832.2022.9812906\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network queries become increasingly challenging for online service providers with massive network devices and massive network queries due to the tradeoff between system scale and query granularity. We re-architect the traditional three-tier architecture, i.e., data collection, data storage, and data query, for aggregate queries, and build a system named NQ/ATP. NQ/ATP offloads the aggregation operation in network queries onto network switches, which accelerates the query execution and frees up network resources. NQ/ATP further devises a route learning mechanism, query hierarchy load balancing policy, and hierarchy clustering mechanism to save forwarding table entries on switches, which better supports massive queries. The evaluation shows that NQ/ATP can support network aggregate queries with higher capacity, less traffic volume, finer granularity, and better scalability than traditional three-tier polling architectures. The three optimizations can effectively reduce the forwarding table usage by up to 97.55%.\",\"PeriodicalId\":353365,\"journal\":{\"name\":\"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWQoS54832.2022.9812906\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS54832.2022.9812906","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
NQ/ATP: Architectural Support for Massive Aggregate Queries in Data Center Networks
Network queries become increasingly challenging for online service providers with massive network devices and massive network queries due to the tradeoff between system scale and query granularity. We re-architect the traditional three-tier architecture, i.e., data collection, data storage, and data query, for aggregate queries, and build a system named NQ/ATP. NQ/ATP offloads the aggregation operation in network queries onto network switches, which accelerates the query execution and frees up network resources. NQ/ATP further devises a route learning mechanism, query hierarchy load balancing policy, and hierarchy clustering mechanism to save forwarding table entries on switches, which better supports massive queries. The evaluation shows that NQ/ATP can support network aggregate queries with higher capacity, less traffic volume, finer granularity, and better scalability than traditional three-tier polling architectures. The three optimizations can effectively reduce the forwarding table usage by up to 97.55%.