{"title":"Squeezing the Most Out of Congestion Window for Self-Clocked Rate Adaptation Algorithm in a 5G Environment","authors":"Haider Dhia Zubaydi, A. Jagmagji, S. Molnár","doi":"10.1109/ConTEL58387.2023.10199010","DOIUrl":null,"url":null,"abstract":"The congestion problem arises in current networking paradigms. Researchers seek different approaches to address this issue by proposing algorithms to control or avoid congestion. One of the primary approaches to handling efficient congestion is specifying the amount of data to be transmitted during a period, referred to as the congestion window (cwnd). This paper aims to optimize the congestion window modification by assessing and utilizing the Self-Clocked Rate Adaptation for Multimedia (SCReAM) algorithm's parameters. Our results indicate that we increased the average congestion window by 164.6% in the classic mode and 67.64% in the L4S/ECN mode.","PeriodicalId":311611,"journal":{"name":"2023 17th International Conference on Telecommunications (ConTEL)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 17th International Conference on Telecommunications (ConTEL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ConTEL58387.2023.10199010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The congestion problem arises in current networking paradigms. Researchers seek different approaches to address this issue by proposing algorithms to control or avoid congestion. One of the primary approaches to handling efficient congestion is specifying the amount of data to be transmitted during a period, referred to as the congestion window (cwnd). This paper aims to optimize the congestion window modification by assessing and utilizing the Self-Clocked Rate Adaptation for Multimedia (SCReAM) algorithm's parameters. Our results indicate that we increased the average congestion window by 164.6% in the classic mode and 67.64% in the L4S/ECN mode.
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