Edge-based Traffic Management Building Blocks

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Edge-based Traffic Management Building Blocks

• David Harrison, Yong Xia, Shiv Kalyanaraman,
• Rensselaer Polytechnic Institute
• shivkuma_at_ecse.rpi.edu
• http//www.ecse.rpi.edu/Homepages/shivkuma

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Overview

• Private Networks vs Public Networks
• QoS vs Congestion Control the middle ground ?
• Overlay Bandwidth Services
• Key deployment advantages
• A closed-loop QoS building block
• Services Better best-effort services, Assured
  services, Quasi-leased lines, App-level QoS

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Motivation Site-to-Site VPN Over a
Multi-Provider Internetwork
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Virtual ISP Network-level Overlay

• Avoid crossing ISP boundaries
• Each ISP will provide good service V-ISP can
  easily verify it
• Allocate/buy service across each ISP and compose
  them
• Network (IP)-level overlay

GPoP (core)
GPoP (core)
ISP 2
Proxy (edge)
Proxy (edge)
ISP 3
ISP 1
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Our Model Edge-based building blocks
I
E
Logical FIFO
B
I
E
E
I
New Closed-loop control !
Policy/ Bandwidth Broker
Model Inspired by diff-serv Aim further
interior simplification
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Closed-loop BB Bandwidth Sharing
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Queuing Behavior Without Closed-loop Control
Bottleneck queue
End system
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Queuing With Closed Loops

• Bottleneck management issues consolidated at
  edges
• Key Transparent and lossless loop schemes
• Potential
• Edge-based QoS services,
• Edge plays in application-level QoS, active
  networking..

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Closed-loop Building Block Reqts

• 1. Edge-to-edge overlay operation,
• 2. Robust stability
• 3. Bounded-buffer/zero-loss,
• 4. Minimal configuration/upgrades
  incremental deployment
• 5. Rate-based operation for bandwidth
  services
• Not available in any congestion control scheme
• Related work NETBLT, TCP Vegas, Mo/Walrand, ATM
  Rate/Credit approaches

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Queuing at One Router Arrival / Service Curves

• flow i at router j
• arrival curve Aij(t)
• service curve Sij(t)
• cumulative
• continuous
• non-decreasing
• if no loss, then

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Accumulation Series of Routers

• we have
• define accumulation
• which is a time-shifted, distributed sum of
  buffered bits of flow i at all routers 1 through J

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Accumulation (Contd)

• then

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Accumulation vs Queuing

• queue qij(t) -- num of bits of flow i queued in
  a fifo router j

• accumulation ai(t) -- num of bits of flow i
  queued in a set of fifo routers 1J

is the forward direction propagation delay.

• the collective queuing behavior of a series of
  fifo routers looks similar to that of one single
  fifo router

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Accumulation Physical Meaning
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Edge-based Control (EC) policy

• control objective keep
• if , no way to probe increase
  of available bw

• control algorithm

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EC schemes

• monaco
• accumulation estimation out-of-band / in-band
• congestion response additive inc/additive dec
  (aiad), etc
• vegas
• accumulation estimation in-band
• congestion response additive inc / additive dec
  (aiad)
• riviera
• accumulation estimation in-band
• congestion response additive inc /
  multiplicative dec
• using egress rate (aimd-er)

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Recall accumulation theory


time
1
j
j1
J
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Accumulation vs. Monaco Estimator


time
1
j
j1
J
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Accumulation vs. Monaco estimator
1
jf
Jf
jf1
djf
fi
data
µij
?i,j1
µi
?i
ctrl
Jb
jb1
jb
1
djb
ctrl
out-of-bd ctrl
classifier
fifo
in-band ctrl, data pkt
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ec monaco

• congestion estimation
• out-of-band and in-band control packets
• congestion response (AIAD)
• if qm lt a, cwnd(k1) cwnd(k) 1
• if qm gt ß, cwnd(k1) cwnd(k) 1 1 a lt ß
  3

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ec vegas

• congestion estimation
• define qv ( cwnd / rttp cwnd / rtt ) rttp
• where rttp is round trip propagation delay
  (basertt)
• congestion response
• if qv lt a, cwnd(k1) cwnd(k) 1
• if qv gt ß, cwnd(k1) cwnd(k) 1 1 a lt ß
  3

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Vegas Accumulation Estimator

• the physical meaning of qv
• rtt rttp rttq rttq is queuing time
• qv ( cwnd / rttp cwnd / rtt ) rttp
• ( cwnd / rtt ) ( rtt rttp )
• ( cwnd / rtt ) rttq if rtt is typical
• sending rate rttq littles law
• packets backlogged littles law again

• so vegas maintains a ß number of packets queued
  inside the network
• it adjusts sending rate additively to achieve this

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Accumulation vs. Vegas estimator

• Backlogv

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Vegas vs. Monaco estimators

• Vegas accumulation estimator
• ingress-based
• round trip (forward data path and backward ack
  path)
• sensitive to ack path queuing delay
• sensitive to round trip propagation delay
  measurement error
• Monaco accumulation estimator
• egress-based
• one way (only forward data path)
• insensitive to ack path queuing delay
• no need to explicitly know one way propagation
  delay

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Riviera

• congestion estimation
• in-band techniques, similar as vegas
• congestion response

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Riviera stability and fairness

• lyapunov function

• each flow i maximizes ( utility penalty )

• proportionally fair

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Linear Network Topology
All links are 4ms, 100 Mbps. Iingress, Eegress,
UUDP, BBottleneck
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Stability and Fairness
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Utilization
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Utilization w/ Reverse Path Congestion
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Queue, Utilization w/ Basertt Errors
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Service Differentiation Loss-based or
Accumulation-based ?
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Overlay Edge-to-edge Bandwidth Services

• Idea Use the EC scheme as a closed-loop building
  block for a range of QoS services
• Basic Services no admission control
• Better best-effort services
• Denial-of-service attack isolation support
• Weighted proportional/priority services
• Advanced services edge-based admission control
• Assured service emulation
• Quasi-leased-line service
• Key no upgrades only configuration reqts

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Scalable Best-effort TCP Service
Without Overlay Scheme
With Overlay Scheme
Queue distribution to the edges gt can manage
more efficiently
CoV vs. No of Flows FRED at the core vs.
FRED at the edges with overlay control between
edges
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Scalable Best-effort TCP Service
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Edge-based Isolation of Denial of Service/Flooding
TCP starting at 0.0s
UDP flood starting at 5.0s
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Edge-based Assured Service Emulation

• Backoff Differentiation Policy
• Backoff little (bas) when below assurance (a),
• Backoff (bas) same as best effort when above
  assurance (a)
• Backoff differentiation quicker than increase
  differentiation
• Service could be potentially oversubscribed (like
  frame-relay)
• Unsatisfied assurances just use heavier weight.

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Bandwidth Assurances
Flow 1 with 4 Mbps assured 3 Mbps best effort
Flow 2 with 3 Mbps best effort
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Quasi-Leased Line (QLL)

• Assume admission control and route-pinning (MPLS
  LSPs).
• Provide bandwidth guarantee.
• Key No delay or jitter guarantees!
• Adaptation in O(RTT) timescales
• Average delay can be managed by limiting total
  and per-VL allocations (managed delay)
• Policy

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Quasi-Leased Line Example
Best-effort rate limit versus time
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Quasi-Leased Line Example (cont)
Bottleneck queue versus time
Requires more buffers larger max queue
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Quasi-Leased Line (cont.)
Worst-case queue vs Fraction of capacity for QLLs
Single bottleneck analysis
B/w-delay products
For b.5, q1 bw-rtt
Simulated QLL w/ edge-to-edge control.
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Current Work

• With bottlenecks consolidated at the edge
• What diff-serv PHBs or remote scheduler
  functionalities can be emulated from the edge ?
• What is the impact of congestion control
  properties and rate of convergence on attainable
  set of services ?
• Areas
• Control plane architecture for large-scale
  overlays
• Application-level QoS edge-to-end problem
• Dynamic (short-term) services
• Congestion-sensitive pricing congestion info at
  the edge
• Edge-based contracting/bidding frameworks

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Summary

• Private Networks vs Public Networks
• QoS vs Congestion Control vs Throwing bandwidth
• Edge-based Building Blocks Overlay services
• A closed-loop QoS building block EC framework
• Accumulation concept
• Monaco, Vegas, Riviera Schemes estimation issues
• Basic services, advanced services