Concurrent multipath transfer using SCTP multihoming over independent end-to-end paths

被引:451
|
作者
Iyengar, Janardhan R. [1 ]
Amer, Paul D.
Stewart, Randall
机构
[1] Univ Delaware, Dept Comp & Informat Sci, Protocol Engn Lab, Newark, DE 19716 USA
[2] Cisco Syst, Internet Technol Div, Columbia, SC 29206 USA
关键词
end-to-end; load balancing; load sharing; multipath; SCTP; transport layer;
D O I
10.1109/TNET.2006.882843
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Concurrent multipath transfer (CMT) uses the Stream Control Transmission Protocol's (SCTP) multihoming feature to distribute data across multiple end-to-end paths in a multihomed SCTP association. We identify three negative side-effects of reordering introduced by CMT that must be managed before efficient parallel transfer can be achieved: (1) unnecessary fast retransmissions by a sender; (2) overly conservative congestion window (cwnd) growth at a sender; and (3) increased ack traffic due to fewer delayed acks by a receiver. We propose three algorithms which augment and/or modify current SCTP to counter these side-effects. Presented with several choices as to where a sender should direct retransmissions of lost data, we propose five retransmission policies for CMT. We demonstrate spurious retransmissions in CMT with all five policies and propose changes to CMT to allow the different policies. CMT is evaluated against AppStripe, which is an idealized application that stripes data over multiple paths using multiple SCTP associations. The different CMT retransmission policies are then evaluated with varied constrained receive buffer sizes. In this foundation work, we operate under the strong assumption that the bottleneck queues on the end-to-end paths used in CMT are independent.
引用
收藏
页码:951 / 964
页数:14
相关论文
共 50 条
  • [41] Myanmar Text-to-Speech Synthesis Using End-to-End Model
    Qin, Qinglai
    Yang, Jian
    Li, Peiying
    2020 4TH INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING AND INFORMATION RETRIEVAL, NLPIR 2020, 2020, : 6 - 11
  • [42] End-to-end speech recognition using lattice-free MMI
    Hadian, Hossein
    Sameti, Hossein
    Povey, Daniel
    Khudanpur, Sanjeev
    19TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2018), VOLS 1-6: SPEECH RESEARCH FOR EMERGING MARKETS IN MULTILINGUAL SOCIETIES, 2018, : 12 - 16
  • [43] END-TO-END SPEECH SUMMARIZATION USING RESTRICTED SELF-ATTENTION
    Sharma, Roshan
    Palaskar, Shruti
    Black, Alan W.
    Metze, Florian
    2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2022, : 8072 - 8076
  • [44] Class mapping for end-to-end guaranteed service with minimum price over DiffServ networks
    Lee, DB
    Song, HJ
    Lee, I
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2006, E89B (02) : 460 - 471
  • [45] A novel end-to-end architecture for H.264 video streaming over the Internet
    Argyriou, A
    TELECOMMUNICATION SYSTEMS, 2005, 28 (02) : 133 - 150
  • [46] A Novel End-to-End Architecture for H.264 Video Streaming over the Internet
    Antonios Argyriou
    Telecommunication Systems, 2005, 28 : 133 - 150
  • [47] Fast Retransmission for Concurrent Multipath Transfer (CMT) over Vehicular Networks
    Huang, Chung-Ming
    Lin, Ming-Sian
    IEEE COMMUNICATIONS LETTERS, 2011, 15 (04) : 386 - 388
  • [48] Using End-to-end Multitask Model for Simultaneous Language Identification and Phoneme Recognition
    Sun, Linjia
    2022 16TH IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP2022), VOL 1, 2022, : 46 - 50
  • [49] RECOGNIZING LONG-FORM SPEECH USING STREAMING END-TO-END MODELS
    Narayanan, Arun
    Prabhavalkar, Rohit
    Chiu, Chung-Cheng
    Rybach, David
    Sainath, Tara N.
    Strohman, Trevor
    2019 IEEE AUTOMATIC SPEECH RECOGNITION AND UNDERSTANDING WORKSHOP (ASRU 2019), 2019, : 920 - 927
  • [50] Image Shadow Removal Using End-To-End Deep Convolutional Neural Networks
    Fan, Hui
    Han, Meng
    Li, Jinjiang
    APPLIED SCIENCES-BASEL, 2019, 9 (05):