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Multipath TCP: Analysis, Design, and Implementation
Open accessAbstract
Multipath TCP (MP-TCP) has the potential to greatly improve application performance by using multiple paths transparently. We propose a fluid model for a large class of MP-TCP algorithms and identify design criteria that guarantee the existence, uniqueness, and stability of system equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss the implications of these properties on the behavior of existing algorithms and motivate our algorithm Balia (balanced linked adaptation), which generalizes existing algorithms and strikes a good balance among TCP-friendliness, responsiveness, and window oscillation. We have implemented Balia in the Linux kernel. We use our prototype to compare the new algorithm to existing MP-TCP algorithms.
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Cited by
Energy-Efficient Adaptive Resource Management for Real-Time Vehicular Cloud Services
Shojafar, M., Cordeschi, N., & Baccarelli, E. (2019) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2016.2551747 · Cited by 339
Zhang, W., Zhang, Z., Zeadally, S., Chao, H.-C., & Leung, V. C. M. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2897001 · Cited by 114
Metadata
- Authors
- Peng, Q., Walid, A., Hwang, J., & Low, S. H.
- Venue
- IEEE/ACM Transactions on Networking
- Published
- 2016-02
- Volume
- 24
- Issue
- 1
- Pages
- 596-609
- ISSN
- 1063-6692 (ISSN-L)
- 1558-2566
- OpenAlex
- W2007309295
- Cited by
- 293
- References
- 0
- FWCI
- 20.42
- Type
- journal article
- Language
- en
- Open access
- green
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- The paper
- Peng, Q., Walid, A., Hwang, J., & Low, S. H. (2016). Multipath TCP: Analysis, Design, and Implementation. IEEE/ACM Transactions on Networking. https://doi.org/10.1109/tnet.2014.2379698
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
