Protocols for Fast Delivery of Large Data Volumes. Latency-Bandwidth tradeoff in Internet. TCP, Parallel TCP, Overlay Networks

1. Protocols for Fast Delivery of
Large Data Volumes
CS4482 High Performance Networking
Dilum Bandara
Dilum.Bandara@uom.lk
Some slides extracted from Dr. Dan Massey’s CS557 class at Colorado
State University

2. High Data Volume Applications
 High definition video streaming
 Ultra high-definition video
 Sensor networks
 Video surveillance
 Radar networks
 Array of Radio telescopes
 Data transfer between grids/clouds
 Data transfer from CERN
 Virtual reality
 Holographic 3D display
Some applications require ordered delivery others don’t
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Source: NAIC/Arecibo Obs/NSF
Source: www.idrshare.com

3. Latency Bandwidth Tradeoff
 Bandwidth is increasing
 10-100 Gbps networks
 Latency is not reducing
 Speed-of-light limitation
 Small transfers are latency limited
 telnet, ssh, chat messages, small file transfer
 Large transfers are still bandwidth limited
 Bulk transfer of files
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4. Bulk Transfer
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Source: N. Tolia et al., “An Architecture for Internet Data Transfer,” NSDI ‘06, 2006

5. TCP Design Assumptions
 Low physical link error rates
 Packet loss = congestion signal
 No packet reordering at network (IP) level
 Packet reordering = congestion signal
 These design assumptions are challenged today
 Parallel networking hardware
 Packet reordering
 Dedicated links or reservations
 No congestion
 Bulk transfers
 Streaming not needed 5

6. Parallel TCP
 Create many parallel TCP connections to
aggregate bandwidth
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Source: www.codeproject.com/Articles/28788/Distributed-Computing-in-Small-and-Medium-Sized-Of

7. Parallel TCP (Cont.)
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N
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Bottleneck capacity c
AIMD connection
Xi = send rate
Source: E. Altman, “Parallel TCP Sockets: Simple Model, Throughput and Validation,” IEEE Infocom, 2006

8. Parallel TCP – Pros & Cons
 Pros
 Aggregated bandwidth
 More resilient to network layer packet losses
 Only one stream would may experience timeout
 More aggressive behavior
 Slow-start is faster, k x MSS
 Recovery is faster compared to single stream with giant
window
 Only one stream may experience loss
 Multiplicative decrease is effectively 1/(2k) rather than 1/2
 Can work around max TCP buffer size limitations
 k x buffer size
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9. Parallel TCP – Pros & Cons (Cont.)
 Cons
 Ideally, each connection should use a different path
 Exploits TCP’s fairness
 Can become unfair to other flows
 Requires changes to applications to support parallel
streams
 May perform worse if loss is due to congestion
 May add to congestion
 Selecting optimum buffer size & number of streams is
hard
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10. Parallel TCP Performance
10
Source: www.codeproject.com/Articles/28788/
Distributed-Computing-in-Small-and-Medium-
Sized-Of

11. Scalable TCP (SCTP)
 Modifies congestion control algorithm
 Each packet loss decreases congestion window
by a factor of 1/8 instead of Standard TCP's ½
congestion window
 When packet loss stops, rate is ramped by
adding one packet every 100 successful ACKs
 Standard TCP – increase by inverse of congestion
window  very large windows take a long time to
recover
11

12. TCP friendly Rate Adaptation Based
On Loss (TRABOL)
 UDP
 Fast, best effort, insensitive to congestion
 TCP
 Slow, reliable, sensitive to congestion
 TRABOL
 Fast, best effort, sensitive to congestion
 Depends on end application/user feedback
 End application/user specifies 2 rates
 Target Rate (TR)
 Minimum Rate (MR)
 Congestion control is similar to TCP
 AIMD 12

13. TRABOL (Cont.)
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Source: A. Trimmer et al.,
“Performance of High-
Bandwidth TRABOL Protocol
for Radar Data Streaming,”
IEEE Region 5 TPS
Conference, 2006.

14. TRABOL Performance
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15. Application aWare Overlay Networks
(AWON)
 Packets are marked based on application requirements
 Drop packets in an application-aware manner
 Multicast nodes send aggregated requests to source
nodes
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Source: T. Banka et al., “An Architecture and a Programming Interface for Application-Aware Data
Dissemination Using Overlay Networks,” COMSWARE '07, 2007.

16. Application-Specific Data Sample
Selection
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17. Content-Based Packet Marking
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ADU – Application Data Unit

18. On-The-Fly Data Selection
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• Compensation for lost packets
• Select a packet from a higher rate

19. AWON Performance
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Measurements on PlanetLab

20. Other Solutions
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Source: http://cloudcomputingseminar.wordpress.com/2012/06/16/unit-2-grid-computing/
• XTP – Xpress Transport Protocol - Fast & light weight
• RBUDP – Reliable Blast UDP - high-bandwidth, reliable
• Tsunami – Improvement of RBUDP