A. Salam, C. Roseti, F. Zampognaro, Natale Patriciello
{"title":"基于ACK序列的TCP波估计的最佳工作点","authors":"A. Salam, C. Roseti, F. Zampognaro, Natale Patriciello","doi":"10.1109/ISNCC.2018.8531003","DOIUrl":null,"url":null,"abstract":"TCP Wave changes the typical TCP transmission paradigm by replacing the ACK-clocked sliding window with self-scheduled bursts. In response to bursts, unmodified TCP receivers generate ACK trains, which carry useful information about the end-to-end link characteristics. TCP Wave inspects ACK-train flow to measure the following parameters: (i) ACK train spread (namely ACK train dispersion) and (ii) RTT variations. The former is expected to provide the overall “service capacity”, meant as the maximum capacity allowed over the end-to-end path, while the latter is considered as a congestion indicator. The joint use of such measurements allows TCP Wave to fine-tune the transmission rate to accurately match current network resource availability in the bottleneck link. This paper analysis TCP Wave ACK train-based measurements on a broad set of simulated links compliant to characteristics of today's real networks. To this scope, a testbed with TCP Wave implementation on Linux OS is used to perform tests varying both bottleneck capacity and physical latency.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"TCP Wave estimation of the optimal operating point using ACK trains\",\"authors\":\"A. Salam, C. Roseti, F. Zampognaro, Natale Patriciello\",\"doi\":\"10.1109/ISNCC.2018.8531003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"TCP Wave changes the typical TCP transmission paradigm by replacing the ACK-clocked sliding window with self-scheduled bursts. In response to bursts, unmodified TCP receivers generate ACK trains, which carry useful information about the end-to-end link characteristics. TCP Wave inspects ACK-train flow to measure the following parameters: (i) ACK train spread (namely ACK train dispersion) and (ii) RTT variations. The former is expected to provide the overall “service capacity”, meant as the maximum capacity allowed over the end-to-end path, while the latter is considered as a congestion indicator. The joint use of such measurements allows TCP Wave to fine-tune the transmission rate to accurately match current network resource availability in the bottleneck link. This paper analysis TCP Wave ACK train-based measurements on a broad set of simulated links compliant to characteristics of today's real networks. To this scope, a testbed with TCP Wave implementation on Linux OS is used to perform tests varying both bottleneck capacity and physical latency.\",\"PeriodicalId\":313846,\"journal\":{\"name\":\"2018 International Symposium on Networks, Computers and Communications (ISNCC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Symposium on Networks, Computers and Communications (ISNCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISNCC.2018.8531003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISNCC.2018.8531003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TCP Wave estimation of the optimal operating point using ACK trains
TCP Wave changes the typical TCP transmission paradigm by replacing the ACK-clocked sliding window with self-scheduled bursts. In response to bursts, unmodified TCP receivers generate ACK trains, which carry useful information about the end-to-end link characteristics. TCP Wave inspects ACK-train flow to measure the following parameters: (i) ACK train spread (namely ACK train dispersion) and (ii) RTT variations. The former is expected to provide the overall “service capacity”, meant as the maximum capacity allowed over the end-to-end path, while the latter is considered as a congestion indicator. The joint use of such measurements allows TCP Wave to fine-tune the transmission rate to accurately match current network resource availability in the bottleneck link. This paper analysis TCP Wave ACK train-based measurements on a broad set of simulated links compliant to characteristics of today's real networks. To this scope, a testbed with TCP Wave implementation on Linux OS is used to perform tests varying both bottleneck capacity and physical latency.