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An Empirical Study of MPQUIC Schedulers in Mobile Wireless Networks

Published: 01 December 2022 Publication History

Abstract

Multipath QUIC (MPQUIC), an emerging multipath transport protocol (MTP) that inherits the advantages of the canonical multipath TCP (MPTCP) and the widespread QUIC, potentially plays a vital role in 5G and beyond. MPQUIC can exploit multiple networks (e.g., Wi-Fi, LTE, 5G) on a mobile device to boost the quality of services while efficiently utilizing network resources. In MPQUIC, the scheduler, which is in charge of concurrently scheduling data transmission in several paths, largely impacts the protocols’ performance, especially in dynamic environments. In fact, in the literature, a considerable number of MTP schedulers for MPQUIC have been proposed. Unfortunately, their performances have been primarily evaluated in static networks without (or simply) considering mobile ones. Hence, this work attempts to investigate the performance of MPQUIC schedulers in the mobile context, aiming to fill the literature gap. Specifically, we implement and assess the performance of five MPQUIC schedulers in various mobility patterns using the Mininet-WiFi emulator. More importantly, we introduce q-ReLeS, an extension of an MPTCP scheduler called ReLeS for MPQUIC. The experimental results show that q-ReLeS reduces the download time from to compared to the others. Besides, the empirical investigation demonstrates that mobility and velocity patterns substantially impact the performance of MPQUIC schedulers.

References

[1]
Q. De Coninck and O. Bonaventure. 2017. Multipath QUIC: Design and Evaluation. In Proc. ACM CoNEXT. 160–166.
[2]
Pingping Dong, Jingyun Xie, Wensheng Tang, Naixue Xiong, Hua Zhong, and Athanasios V. Vasilakos. 2019. Performance Evaluation of Multipath TCP Scheduling Algorithms. IEEE Access 7(2019), 29818–29825.
[3]
Alan Ford et al.2020. TCP Extensions for Multipath Operation with Multiple Addresses. RFC 8684.
[4]
Adam Langley et al.2017. The QUIC Transport Protocol: Design and Internet-Scale Deployment. In Proc. ACM SIGCOMM. 183–196.
[5]
Hongjia Wu et al.2020. Peekaboo: Learning-Based Multipath Scheduling for Dynamic Heterogeneous Environments. IEEE Journal on Selected Areas in Communications 38, 10(2020), 2295–2310.
[6]
S. Ferlin et al.2016. BLEST: Blocking Estimation-based MPTCP Scheduler for Heterogeneous Networks. In Proc. IEEE/IFIP Networking. 431–439.
[7]
Ramon dos Reis Fontes and Christian Esteve Rothenberg. 2016. Mininet-WiFi: A Platform for Hybrid Physical-Virtual Software-Defined Wireless Networking Research. In Proc. ACM SIGCOMM. 607–608.
[8]
Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, and Sergey Levine. 2016. Continuous Deep Q-Learning with Model-Based Acceleration. In Proc. ICML. 2829–2838.
[9]
Xiaoyan Hong, Mario Gerla, Guangyu Pei, and Ching-Chuan Chiang. 1999. A Group Mobility Model for Ad Hoc Wireless Networks. In Proc. the 2nd ACM International Workshop on Modeling, Analysis and Simulation of Wireless and Mobile Systems(MSWiM ’99). 53–60.
[10]
W.-j. Hsu, T. Spyropoulos, K. Psounis, and A. Helmy. 2007. Modeling Time-Variant User Mobility in Wireless Mobile Networks. In Proc. IEEE INFOCOM. 758–766.
[11]
David B. Johnson and David A. Maltz. 1996. Dynamic Source Routing in Ad Hoc Wireless Networks. 153–181.
[12]
Young-Bae Ko and Nitin H. Vaidya. 1998. Location-Aided Routing in Mobile Ad Hoc Networks. In Proc. ACM MOBICOM. 66–75.
[13]
B. Liang and Z.J. Haas. 2003. Predictive distance-based mobility management for multidimensional PCS networks. IEEE/ACM Transactions on Networking 11, 5 (2003), 718–732.
[14]
Christoph Paasch, Sebastien Barre, 2014. Multipath TCP implementation in the Linux kernel.
[15]
Injong Rhee, Minsu Shin, Seongik Hong, Kyunghan Lee, Seong Joon Kim, and Song Chong. 2011. On the Levy-Walk Nature of Human Mobility. IEEE/ACM Transactions on Networking 19, 3 (2011), 630–643.
[16]
E.M. Royer, P.M. Melliar-Smith, and L.E. Moser. 2001. An analysis of the optimum node density for ad hoc mobile networks. In Proc. IEEE ICC. 857–861.
[17]
Miguel Sánchez and Pietro Manzoni. 2001. ANEJOS: A Java Based Simulator for Ad Hoc Networks. Future Gener. Comput. Syst. 17, 5 (2001), 573–583.
[18]
Muge Sayit, Erdem Karayer, Chi-Dung Phung, Stefano Secci, and Selma Boumerdassi. 2019. Numerical evaluation of MPTCP schedulers in terms of throughput and reliability. In International Workshop on RNDM. 1–6.
[19]
Yeon sup Lim et al.2016. ECF: An MPTCP path scheduler to manage heterogeneous paths. In Proc. ACM CoNEXT. 147–159.
[20]
Viswanath Tolety. 1999. Load Reduction in Ad Hoc Networks Using Mobile Servers. In Master’s thesis, Colorado School of Mines.
[21]
Hongjia Wu, Giuseppe Caso, Simone Ferlin, Özgü Alay, and Anna Brunstrom. 2001. Multipath Scheduling for 5G Networks: Evaluation and Outlook. IEEE Communications Magazine 59, 4 (2001), 44–50.
[22]
Han Zhang, Wenzhong Li, Shaohua Gao, Xiaoliang Wang, and Baoliu Ye. 2019. ReLeS: A Neural Adaptive Multipath Scheduler based on Deep Reinforcement Learning. In Proc. IEEE INFOCOM. 1648–1656.

Cited By

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  • (2024)Reproducible Wireless Experiments in a Containerized Environment with Hardware Access2024 IEEE 49th Conference on Local Computer Networks (LCN)10.1109/LCN60385.2024.10639643(1-7)Online publication date: 8-Oct-2024
  • (2024)MuLeS: A Multi-Client Learning-Based MPQUIC Scheduler2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454897(656-661)Online publication date: 6-Jan-2024
  • (2024)FQ-SAT: A fuzzy Q-learning-based MPQUIC scheduler for data transmission optimizationComputer Communications10.1016/j.comcom.2024.107924226-227(107924)Online publication date: Oct-2024

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cover image ACM Other conferences
SoICT '22: Proceedings of the 11th International Symposium on Information and Communication Technology
December 2022
474 pages
ISBN:9781450397254
DOI:10.1145/3568562
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2022

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Author Tags

  1. MPQUIC
  2. mobile wireless network
  3. mobility model
  4. multipath scheduler

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  • Research-article
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  • Refereed limited

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  • JSPS KAKENHI

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SoICT 2022

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Overall Acceptance Rate 147 of 318 submissions, 46%

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Cited By

View all
  • (2024)Reproducible Wireless Experiments in a Containerized Environment with Hardware Access2024 IEEE 49th Conference on Local Computer Networks (LCN)10.1109/LCN60385.2024.10639643(1-7)Online publication date: 8-Oct-2024
  • (2024)MuLeS: A Multi-Client Learning-Based MPQUIC Scheduler2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454897(656-661)Online publication date: 6-Jan-2024
  • (2024)FQ-SAT: A fuzzy Q-learning-based MPQUIC scheduler for data transmission optimizationComputer Communications10.1016/j.comcom.2024.107924226-227(107924)Online publication date: Oct-2024
  • (2023)An Accuracy Study of Emulation Daemons for IEEE 802.11 Networks2023 IEEE 48th Conference on Local Computer Networks (LCN)10.1109/LCN58197.2023.10223345(1-9)Online publication date: 2-Oct-2023

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