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Throughput Estimation for Short Lived TCP Cubic Flows

Published: 28 November 2016 Publication History

Abstract

Mobile devices are increasingly becoming the dominant device for Internet access. The network throughput achieved by a mobile device directly affects the performance and user experience. Throughput measurement techniques thus play an important role in predicting expected performance. Measurement techniques that require the transfer of large amounts of data can provide higher accuracy but incur large overhead. Further, since most mobile cellular plans impose usage quota, the overhead of such measurements over cellular networks can become quite high. Smaller data transfers have also been used to measure the throughput. Due to the conservative TCP slow start behaviour, however, these measurements often underestimate the achievable throughput. Considering these weaknesses in existing throughput measurement techniques, we propose a throughput estimation technique for TCP Cubic that uses 1 MB of data transfer to predict the throughput for prevalent large transfer sizes in mobile traffic such as 5 MB, 10 MB and 20 MB. Our evaluation shows that our approach can achieve high accuracy with low overhead, in predicting the achievable throughput.

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  • (2024)IoT Video Delivery Optimization through Machine Learning-Based Frame Resolution AdjustmentACM Transactions on Multimedia Computing, Communications, and Applications10.1145/366592920:9(1-24)Online publication date: 24-May-2024
  • (2023)Performance and improvements of TCP CUBIC in low-delay cellular networksComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.109609224:COnline publication date: 1-Apr-2023
  • (2021)A Survey on Client Throughput Prediction Algorithms in Wired and Wireless NetworksACM Computing Surveys10.1145/347720454:9(1-33)Online publication date: 8-Oct-2021
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  1. Throughput Estimation for Short Lived TCP Cubic Flows

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      cover image ACM Other conferences
      MOBIQUITOUS 2016: Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
      November 2016
      307 pages
      ISBN:9781450347501
      DOI:10.1145/2994374
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 28 November 2016

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      Author Tags

      1. Cellular Networks
      2. Mobile Devices
      3. Network Measurements
      4. TCP Cubic
      5. Throughput

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      • Research-article
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      MOBIQUITOUS 2016
      MOBIQUITOUS 2016: Computing, Networking and Services
      November 28 - December 1, 2016
      Hiroshima, Japan

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      MOBIQUITOUS 2016 Paper Acceptance Rate 26 of 87 submissions, 30%;
      Overall Acceptance Rate 26 of 87 submissions, 30%

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      Cited By

      View all
      • (2024)IoT Video Delivery Optimization through Machine Learning-Based Frame Resolution AdjustmentACM Transactions on Multimedia Computing, Communications, and Applications10.1145/366592920:9(1-24)Online publication date: 24-May-2024
      • (2023)Performance and improvements of TCP CUBIC in low-delay cellular networksComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.109609224:COnline publication date: 1-Apr-2023
      • (2021)A Survey on Client Throughput Prediction Algorithms in Wired and Wireless NetworksACM Computing Surveys10.1145/347720454:9(1-33)Online publication date: 8-Oct-2021
      • (2021)Predicting Throughput of Cloud Network Infrastructure Using Neural NetworksIEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFOCOMWKSHPS51825.2021.9484520(1-6)Online publication date: 10-May-2021
      • (2019)Useful Traffic Loss Rate Estimation Based on Network Layer MeasurementIEEE Access10.1109/ACCESS.2019.28939517(33289-33303)Online publication date: 2019
      • (2017)Viscous: An End to End Protocol for Ubiquitous Communication Over Internet of Everything2017 IEEE 42nd Conference on Local Computer Networks (LCN)10.1109/LCN.2017.79(312-320)Online publication date: Oct-2017

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