Sphinx: A transport protocol for high-speed and lossy mobile networks

Modern mobile wireless networks have been demonstrated to be high-speed but lossy, while mobile applications have more strict requirements including reliability, low latency, goodput guarantee, bandwidth efficiency, and computation efficiency. Such a complicated combination of requirements and condi...

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Vydáno v:Computer networks (Amsterdam, Netherlands : 1999) Ročník 195; s. 108193
Hlavní autoři: Li, Junfeng, Li, Dan, Wu, Wenfei, Ramakrishnan, K.K., Geng, Jinkun, Wang, Fanzhao, Zheng, Kai
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 04.08.2021
Elsevier Sequoia S.A
Témata:
Applications programs
Coding
Compensation
Computation
Computer architecture
Decoding
Forward error correction
High speed
Latency
Lossy mobile networks
Microprocessors
Mobile computing
Network latency
Networks
Proactive and reactive hybrid protocol
Prototypes
Redundancy
Reliability
Software
Transport protocol
Transportation
Video transmission
Wireless communication systems
Wireless networks
Forward error correction
Proactive and reactive hybrid protocol
Lossy mobile networks
Transport protocol
ISSN:1389-1286, 1872-7069
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Popis
Shrnutí:Modern mobile wireless networks have been demonstrated to be high-speed but lossy, while mobile applications have more strict requirements including reliability, low latency, goodput guarantee, bandwidth efficiency, and computation efficiency. Such a complicated combination of requirements and conditions in networks pushes the pressure to transport layer protocol design. We analyze and argue that few of existing network transport layer solutions are able to handle all these requirements. We design and implement Sphinx to satisfy the five requirements in high-speed and lossy networks. Sphinx has (1) a proactive coding-based method named semi-random LT codes for loss recovery, which estimates packet loss rate and adjusts the redundancy level accordingly, (2) a reactive retransmission method named Instantaneous Compensation Mechanism (ICM), which retransmits precisely and timely once decoding failure occurs, and (3) a parallel coding architecture, which speeds up coding process by leveraging multi-core, shared memory and kernel-bypass Data Plane Development Kit (DPDK). Prototype and evaluation show that Sphinx outperforms TCP schemes and other coding solutions significantly in microbenchmarks across all five requirements, and improves the performance of the video streaming application.
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ISSN:1389-1286
1872-7069
DOI:10.1016/j.comnet.2021.108193