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Improving TCP Performance in a Differentiated Services Network: Investigations and Solutions. Kaleelazhicathu R R Kumar Centre for Internet Research School Of Computing National University of Singapore. Outline. Introduction Motivation Background TCP DiffServ TCP in DiffServ : Issues

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improving tcp performance in a differentiated services network investigations and solutions

Improving TCP Performance in a Differentiated Services Network:Investigations and Solutions

Kaleelazhicathu R R Kumar

Centre for Internet Research

School Of Computing

National University of Singapore

outline
Outline
  • Introduction
    • Motivation
  • Background
    • TCP
    • DiffServ
    • TCP in DiffServ : Issues
  • Related work
  • Research Objective
  • Thesis Contribution
  • Memory-Based Marker (MBM)
  • Memory-Based Three Color Marker (MBTCM)
  • TSWTCM vs. MBTCM : A Comparison
  • Congestion-Aware Traffic Conditioner (CATC)
  • Linux Implementation of MBM
  • Areas for Deployment
  • Conclusion
introduction motivation
Introduction: Motivation
  • An exponential growth in traffic resulted in deterioration of QoS.
  • Over provisioning of networks could be a solution.
  • A better solution: An intelligent network service with better resource allocation and management methods.
  • DiffServ has emerged as a solution for providing QoS by service differentiation.
  • Recent measurements have shown TCP flows being in majority (95% approx. of byte share).
  • Inherent limitations of TCP is a hurdle for providing better QoS.
background transmission control protocol tcp
Background: Transmission Control Protocol (TCP)
  • De facto Transport layer Protocol
    • Common applications like Telnet,FTP and HTTP uses TCP
  • Provides a connection oriented,reliable,

byte stream service to the application.

  • Control mechanisms
    • Slow start, Congestion Avoidance, Fast Retransmit and Recovery
    • Flow Control
differentiated services
Differentiated Services
  • Provides QoS for aggregate flows using different per hop forwarding behaviours at the core routers
  • Scalable
  • The philosophy: simpler at the core (AQM), complex at the edges
  • Per-Hop behaviours
    • Expedited forwarding: Deterministic QoS
    • Assured forwarding: Statistical QoS
  • RIO-based schemes proposed for AQM.
differentiated services1
Differentiated Services
  • Basic building blocks of DiffServ
    • Classifier
    • Traffic Conditioner
      • Token Bucket (TB), Time Sliding Window (TSW)
        • Meter
        • Marker
        • Shaper/Dropper
differentiated services2
Differentiated Services

Meter

Packets

Forward

Classifier

Marker

Shaper/

Dropper

Drop

Logical View of a Packet Classifier and Traffic Conditioner

tcp in diffserv issues
TCP in DiffServ: Issues
  • TCP flows are much more sensitive to transient congestion.
    • Bias against connections with long Round Trip Time (RTT)
      • Reason:Long RTT flows takes longer time to ramp up.
    • Bias against connections with smaller window sizes
      • Reason: Smaller windows mean smaller throughput
    • Protection from unruly traffic like UDP traffic.
      • Reason: UDP traffic has no rate control mechanism and hence kills TCP traffic.
  • DiffServ issues
    • Bandwidth assurance affected by size of target rate.
    • Markers sensitive to its own parameters.
    • Absence of Edge-to-Edge feedback.
    • Existing markers fail to track TCP dynamics
related work
Related Work
  • Clark et al came up with the RIO scheme.
  • Nandy et al identified the factors affecting bandwidth assurance.
  • Kalyanaraman et al proposes a TCP-Friendly component.
  • Kalyanaraman et al also proposed an edge-to-edge feedback architecture based on ECN and ICMP messages.
  • Sahu et al studied the influence of token bucket parameters on providing assured service.
  • Feng et al proposed an adaptive marker.
research objective
Research Objective
  • Markers, one of the building blocks of a traffic

conditioner play a major role for resource allocation

in a DiffServ network.

  • Design an Intelligent Marker
    • Least sensitive to both the marker and TCP parameters
    • Should be transparent to end hosts.
    • Maintain optimum marking
    • Tracks the TCP dynamics
    • Minimize synchronizations.
    • Be fair to different target sizes.
    • Be congestion aware.
  • Design an Edge-to-Edge feedback architecure
    • An early indication of congestion in a network helps to prioritize the packets in advance.
thesis contribution
Thesis Contribution
  • Two Approaches
    • Memory-Based
      • Memory-Based Marker (MBM)
        • Reduces influence of TCP’s limitations
      • Memory-Based Three Color Marker (MBTCM)
        • Suitable for DiffServ with AF PHB
    • Feedback-based
      • Congestion-aware Traffic Conditioner
        • Provides edge-to-edge feedback to the marker
memory based marker mbm
Memory-Based Marker (MBM)
  • Tracks TCP dynamics.
  • Transparent to end hosts.
  • Maintain optimum marking.
  • Fairness
  • Less sensitive to its own parameters.
memory based marker
Memory-Based Marker?
  • During the period when TCP flows experience

congestion, either or both of the following occurs:

a) The cwnd reduces reducing the value of W

b) The RTT increases

causing a decrease in throughput or rate of flow.

  • The TCP window size W and the round trip time RTT are related to the throughput by the equation:

BW = ¾*(MSS*W)/(RTT) where W is expressed in

number of segments.

  • Any variation in W or RTT is reflected as subsequent changes in BW, i.e., in our case, the avg_rate.
  • The parameter previous average rate (par) is compared with the present average rate to track any change in the rate of flow and thus indirectly extract the variations in RTT or W.
mbm algorithm
MBM Algorithm

else if avg_rate > cir

then

mp= mp + (par – avg_rate)/avg_rate;

par=avg_rate;

mark the packet using:

cp 11 w.p. mp

cp 00 w.p. (1-mp)

  • For each packet arrival

If avg_rate  cir

then

mp=mp+(1-avg_rate/cir)+

(par- avg_rate)/avg_rate;

par = avg_rate;

mark the packet using:

cp 11 w.p. mp

cp 00 w.p. (1-mp)

mbm algo cont d
MBM Algo. Cont’d..
  • where,

avg_rate= the rate estimate upon each packet arrival

mp = marking probability (1)

cir = committed information rate (i.e., the target rate)

par = previous average rate

cp denotes ‘codepoint’ and w.p. denotes ‘with

probability’.

mbm algo explained
MBM Algo. Explained
  • In the expression for the marking probability mp,
    • (par – avgrate)/avgrate tracks the variations in RTT and window size (W) and thus increases or decreases the marking probability according to the changes in the flow rate.
    • (1- avgrate)/cir constantly compares the average rate observed with the target rate to keep the rate closer to the target.
experiments
Experiments
  • We used FTP bulk data transfer for the TCP traffic in all our experiments.
  • NS (2.1b7a) simulator on Red Hat 7.0
  • Modified Nortel’s DiffServ module for our architecture implementation.
  • Core routers use RIO like mechanism
  • We conducted simulation studies for:
    • Assured service for aggregates with different target rates.
    • Effect of different RTTs
    • Effect of different window sizes
    • Protection from best effort UDP flows
    • Effect of UDP flows with target rates.
results
Results

Achieved Rates (Ra) for different Target Rates (Rt).

results1
Results..

Achieved Rates (Ra) for different RTT values

Achieved Rates (Ra) for different window sizes

results2
Results..

Achieved Rates in presence of BE UDP and TCP

Achieved Rates in presence of AS UDP and BE TCP

inference
Inference
  • MBM
    • Achieves transparency from the end hosts, simplicity, and least sensitivity to parameters of both TCP as well as its own parameters.
    • helps in achieving the target rate, with a better fairness in terms of sharing the excess bandwidth among flows.
    • provides the TCP flows, a greater degree of insulation

from differences in RTT and window sizes.

    • The overall link utilization also seems to be much better.
memory based three color marker mbtcm
Memory-Based Three Color Marker(MBTCM)
  • An Extension of MBM suitable for DiffServ

with AF PHB.

  • Solves some issues in MBM.
  • an improvement over TSWTCM
mbtcm algorithm
MBTCM Algorithm

else if (avg_rate cir) &&

(avg_rate pir)

then

mp= mp + (par –

avg_rate)/avg_rate –

(avg_rate-cir)/pir;

par=avg_rate;

mark the packet using:

cp 11 w.p. mp

cp 00 (red) w.p. (1-mp)

else

cp 00 w.p 1

  • For each packet arrival

If avg_rate  cir

then

mp=mp+(1-avg_rate/cir)+

(par- avg_rate)/avg_rate;

par = avg_rate;

mark the packet using:

cp 10 (green) w.p. mp

cp 11 (yellow) w.p. (1-mp)

mbtcm algo explained
MBTCM Algo. Explained
  • ·(avg_rate-cir)/pir acts as the reduction factor for reducing the probability as the avg_rate increases towards pir. This component is particularly useful when the traffic stream has a constant avg_rate (e.g., UDP traffic) and is above cir. In such a scenario, mp doesn’t remain constant but reduces to zero.
results3
Results…

Achieved Rates (Ra) for different Target Rates (Rt).

results4
Results..

Achieved Rates (Ra) for different window sizes

Achieved Rates in presence of BE UDP and TCP

tswtcm vs mbtcm a comparison
TSWTCM vs. MBTCM: A Comparison
  • TSWTCM
    • 3 color TSW-TC based marker
    • Marking based on two parameters- Committed Target Rate (CTR), and Peak Target Rate (PTR).
results5
Results..

Achieved Rates (Ra) for different Target Rates (Rt).

results6
Results..

Achieved Rates (Ra) for different window sizes.

Achieved Rates in presence of BE UDP and TCP

the comparison
The Comparison.
  • MBTCM
    • achieves the target rates for priority flows with optimum marking.
    • helps in achieving consistency of goodput in cases of flows with different window settings.
    • performs better than TSWTCM in terms of protection from BE UDP flows.
    • has an overall link utilization much better than TSWTCM.
congestion aware traffic conditioner catc
Congestion-aware Traffic Conditioner(CATC)
  • Congestion-aware
  • Least sensitive to the marker parameters.
  • Transparent to end hosts.
  • Maintain optimum marking.
edge to edge feedback architecture
Edge-to-Edge Feedback Architecture
  • Two edge routers
    • Control sender (CS) and control receiver (CR)
  • Upstream:
    • At CS:
      • CS sends control packets (CP) at regular interval of time, control packet interval (cpi).
      • CPs are given highest priority.
    • At Core:
      • Core routers maintain the status of drops of the best effort packets.
      • Information maintained as a status flag to a max. of cpi time.
      • CP’s congestion notification (CN) bit set or reset based on status flag.
    • At CR:
      • Responds to the incoming CP with a CN bit set by setting the congestion echo (CE) bit of the outgoing acknowledgement.
  • Downstream
    • At CS:
      • Maintains a parameter, congestion factor (cf).
      • Cf is set to 1 or 0 based on status of the CE bit in acknowledgement received
catc algorithm
CATC Algorithm

For each packet arrival

If avg_rate  cir

then

mp=mp+(1-

avg_rate/cir)*(1+

cf*(cir/cir_max));

mark the packet using :

cp 11 w.p. mp

cp 00 w.p. (1-mp)

else if avg_rate > cir

then

mp=mp+ (1- avg_rate/cir)*(1- cf*(cir/cir_max));

mark the packet using :

cp 11 w.p. mp

cp 00 w.p. (1-mp)

catc algo explained
CATC Algo. Explained
  • The effect on mp:
    • i)Flow component (1- avg_rate/cir) constantly compares the average rate observed with the target rate to keep the rate closer to the target.
    • ii)Network component cf*(cir/cir_max) provides a dynamic indication of congestion level status in the network. The marking probability increment is done in proportion to the target rate by multiplying cf with a weight factor cir/cir_max to mitigate the impact of the target rates.
results7
Results

Achieved Rates (Ra) for different Target Rates (Rt) -- under- and well-subscribed cases.

results8
Results..

Achieved Rates (Ra) for different Target Rates (Rt) -- over-subscribed cases

results9
Results..

Achieved Rates in presence of BE UDP and TCP

results10
Results..

Achieved Rates in presence of AS UDP and BE TCP

inference1
Inference
  • Achieves goodput close to the target rates.
  • Succeeds in taking the share of BE TCP and UDP flows in the worst case scenario.
  • The average link utilization pretty good.
  • The AS UDP flow gets its assured rate.
linux implementation of mbm
Linux Implementation of MBM
  • Incorporated with the existing traffic control functions of Linux.
  • Linux kernel version used was 2.2.14 , Redhat 6.2.
areas for deployment
Areas for Deployment
  • Marker anywhere (lack of sensitivity to marker parameters).
  • MPLS over DiffServ.
conclusion
Conclusion
  • transparency from the end hosts, simplicity, and least sensitivity to parameters of both TCP as well as marker parameters.
  • helps in achieving the target rate, with a better fairness in terms of sharing the excess bandwidth among flows.
  • provides the TCP flows, a greater degree of insulation from differences in RTT and window sizes.
  • overall link utilization also seems to be much better.
conclusion1
Conclusion…
  • Provides an architecture which is transparent to TCP sources and hence doesn’t require any modifications at the end hosts.
  • The edge-to-edge feedback control loop helps the marker to take proactive measures in maintaining the assured service effectively, especially during periods of congestion.
  • A single feedback control is used for an aggregated flow. Hence this architecture is scalable to any number of flows between the two edge gateways.
  • The architecture is adaptive to changes in load and network conditions.
  • The marking algorithm takes care of any bursts in the flows.
acknowledgement
Acknowledgement
  • Dr. Lillykutty Jacob
  • Prof. A.L.Ananda
  • NS Community
  • Rajesh,Boon Peng
  • Michael, Srijith, Yong Xiang
  • Saswat, Prashant, Sriram, RK
  • All my dear friends
  • My Family
  • God Almighty
papers published
Papers published

Conferences:

1. K.R.R.Kumar, A.L.Ananda, Lillykutty Jacob,“A Memory-Based Approach for a TCP-Friendly Traffic Conditioner in DiffServ Networks”, in Proc. of the 9th IEEE International Conference on Network Protocols (ICNP 2001), Riverside, California.

2. K.R.R.Kumar, A.L.Ananda, Lillykutty Jacob, “Using Edge-To-Edge Feedback Control to make Assured Service More Assured in DiffServ Networks”, in Proc. of the 26th Annual IEEE Conference on Local Computer Networks (LCN 2001), Tampa, Florida.

Journal:

1. K.R.Renjish Kumar, A.L.Ananda, Lillykutty Jacob,“TCP-Friendly Traffic Conditioning in DiffServ Networks : A Memory-Based Approach ”, accepted (invited paper) in Computer Networks, Elsevier Publications.

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