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, 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 four 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) for loss retransmission, which compensates the lost packets once actual loss exceeds the estimation, and (3) a parallel coding architecture, which leverages multi-core, shared memory and kernel-bypass DPDK. Prototype and evaluation show that Sphinx outperforms TCP and other coding solutions significantly in microbenchmarks across all four requirements, and improves the performance of applications such as video streaming and block data transfer.

[1]  Injong Rhee,et al.  CUBIC: a new TCP-friendly high-speed TCP variant , 2008, OPSR.

[2]  K. K. Ramakrishnan,et al.  LT-TCP: End-to-End Framework to Improve TCP Performance over Networks with Lossy Channels , 2005, IWQoS.

[3]  T. V. Lakshman,et al.  The performance of TCP/IP for networks with high bandwidth-delay products and random loss , 1997, TNET.

[4]  K. K. Ramakrishnan,et al.  OpenNetVM: A Platform for High Performance Network Service Chains , 2016, HotMiddlebox@SIGCOMM.

[5]  Michael Luby,et al.  LT codes , 2002, The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings..

[6]  Jing Zhu,et al.  Towards full virtualization of SDN infrastructure , 2018, Comput. Networks.

[7]  Rose Qingyang Hu,et al.  Key elements to enable millimeter wave communications for 5G wireless systems , 2014, IEEE Wireless Communications.

[8]  F. Moore,et al.  Polynomial Codes Over Certain Finite Fields , 2017 .

[9]  Kai Xu,et al.  Improving TCP performance in integrated wireless communications networks , 2005, Comput. Networks.

[10]  Shancang Li,et al.  5G Internet of Things: A survey , 2018, J. Ind. Inf. Integr..

[11]  Diagonal recurrence relations for the Stirling numbers of the first kind , 2013, 1310.5920.

[12]  Bin Wang,et al.  LOS: A High Performance and Compatible User-level Network Operating System , 2017, APNet.

[13]  Sally Floyd,et al.  TCP Selective Acknowledgment Options , 1996, RFC.

[14]  K. K. Ramakrishnan,et al.  D-LiTE: A platform for evaluating DASH performance over a simulated LTE network , 2016, 2016 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN).

[15]  KeeHyun Park,et al.  A High-Performance Implementation of an IoT System Using DPDK , 2018 .

[16]  Fan Yang,et al.  The QUIC Transport Protocol: Design and Internet-Scale Deployment , 2017, SIGCOMM.

[17]  Dan Li,et al.  Quick NAT: High performance NAT system on commodity platforms , 2017, 2017 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN).

[18]  Joong Bum Rhim,et al.  Fountain Codes , 2010 .

[19]  Yunghsiang Sam Han,et al.  Novel Polynomial Basis and Its Application to Reed-Solomon Erasure Codes , 2014, 2014 IEEE 55th Annual Symposium on Foundations of Computer Science.

[20]  Larry L. Peterson,et al.  TCP Vegas: End to End Congestion Avoidance on a Global Internet , 1995, IEEE J. Sel. Areas Commun..

[21]  Sally Floyd,et al.  TCP Selective Acknowledgement Options , 1996 .

[22]  Ayman I. Kayssi,et al.  SDN for QUIC: an enhanced architecture with improved connection establishment , 2018, SAC.

[23]  Mingwei Xu,et al.  LTTP: An LT-Code Based Transport Protocol for Many-to-One Communication in Data Centers , 2014, IEEE Journal on Selected Areas in Communications.

[24]  Sally Floyd,et al.  The NewReno Modification to TCP's Fast Recovery Algorithm , 2004, RFC.

[25]  K. K. Ramakrishnan,et al.  NetVM: High Performance and Flexible Networking Using Virtualization on Commodity Platforms , 2014, IEEE Transactions on Network and Service Management.

[26]  Abdul Hameed,et al.  Adaptive video-aware forward error correction code allocation for reliable video transmission , 2018, Signal Image Video Process..