Available Bandwidth Estimation

1
Available Bandwidth Estimation

• Manish Jain
• Networking and Telecom Group
• CoC, Georgia Tech

2
Outline

• Introduction and definitions
• Estimation methodologies
• Train of Packet Pairs(TOPP)
• Self Loading Periodic Streams (SLoPS)
• Packet Train Gap Model
• Open Issues

3
Definition

• Available Bandwidth unutilized capacity

• Varies with time
• ui utilization of link i in time interval t (
  0 lt ui lt 1 )
• Available bandwidth in link i
• Available bandwidth in path (Avail-bw)
• Tight link minimum avail-bw link

4
Available Bandwidthtime varying metric
t
A(t)
T
t

• t defines sampling/averaging timescale
• Average avail-bw in t
• Does not tell how avail-bw varies
• Variation range gives more information

5
Why do we care ?

• ssthresh in TCP
• Streaming applications
• SLA verification
• Overlay routing
• End-to-end admission control

6
Measuring per-hop available bandwidth

• Can be measured at each link from interface
  utilization data using SNMP
• MRTG graphs 5-minute averages
• But users do not normally have access to SNMP
  data
• And MRTG graphs give only per-hop avail-bandwidth

7
Measuring path Available Bandwidth

• Blast path with UDP packets
• Intrusive
• Carter Crovella cprobe (Infocom 1996)
• Packet train dispersion does not measure
  available bandwidth (Dovrolis et.al. Infocom01)
• Measure throughput of large TCP transfer
• TCP throughput depends on network buffer
• Ribeiro et.al. Delphi (ITC00)
• Correct estimation when queuing occurs only at
  single link
• Assumes that cross traffic can be modelled by MWM
  model

8
A New End-to-end probing and analysis method for
estimating bandwidth bottlenecks

• B. Melander et al, In Global Internet Symposium,
  2000

9
Introduction

• In FCFS queue, output rate is function of input
  rate and cross-traffic rate

Oj-1
Oj
Oj1
Cj1
Cj
Cj1-Mj gt Cj-Mj-1
Mj-1
Mj

• In one hop
• In two hop

10
Key IdeaTOPP

• o sending rate
• f receiving rate
• where i is number links with different available
  bandwidth
• For i1
• b11/Ctight
• a11-Atight/Ctight

Break points
11
Algorithm

• Algorithm
• Send n probe pairs with a minimum rate
• Record receive rate at receiver
• Increment rate by fixed d and repeat
• Measure available bandwidth from the relation of
  o/f vs o
• Avail-bw and capacity of other links can be
  measured
• if links in ascending order of avail-bw
• In practice, break points may be hard to identify

12
End-to-end Available Bandwidth Measurement
Methodology, Dynamics and Relation with TCP
Throughput

• M. Jain and C. Dovrolis, In IEEE/ACM TON, August
  2003

13
Key idea SLoPS

• Examine One-Way Delay (OWD) variations of a fixed
  rate stream
• Relate rate to avail-bw
• OWD Di Tarrive-T Tarrive - Tsend
  Clock_Offset(S,R)
• SLoPS uses relative OWDs, DDi Di1 Di-1
  (independent of clock offset)
• With a stationary fluid model for the cross
  traffic, and FIFO queues
• If R gt min Ai, then DDi gt 0 for I 1N
• Else DDi 0 for for I 1N

R
R
R
S
send
14
Illustration of SLoPS

• Periodic Stream K packets, size L bytes, rate R
  L/T
• If RgtA, OWDs gradually increase due to
  self-loading of stream

15
Trend in real data

• For some rate R
• Increasing trend in OWDs ? R gt Avail-bw
• No trend in OWDs ? R lt Avail-bw

16
Iterative algorithm in SLoPS

• At sender Send periodic stream n with rate Rn
  
• At receiver Measure OWDs Di for i1K
• At receiver Notify sender of trend in OWDs
• At sender If trend is -
• increasing (i.e. Rn gtA ) ? repeat with Rn1 lt
  Rn
• non-increasing (i.e. Rn ltA ) ? repeat with
  Rn1gtRn
• Selection of Rn1 Rate adjustment algorithm
• Terminate if Rn1 Rn lt ?
• ? resolution of final estimate

17
If things were black and white

• Grey region Rate R not clearly greater or
  smaller than Avail-bw during the duration of
  stream
• Rate R is within variation range of avail-bw

18
Big Picture

• Increasing trend ? R gt variation range of
  Avail-bw
• No trend ? R lt variation range of Avail-bw
• Grey trend ? R inside variation range

19
Rate adjustment algorithm

• Increasing trend
• Rmax R(n)
• R(n1) (Gmax Rmax)/2
• Non-increasing trend
• Rmin R(n)
• R(n1) (Gmax Rmin)/2
• Grey region R(n) gt Gmax
• Gmax R(n)
• R(n1) (Gmax Rmax )/2
• Grey region R(n) lt Gmin
• Gmin R(n)
• R(n1) (Gmin Rmin )/2

Grey region
Variation Range
Terminate if (Rmax Gmax) (Rmin Gmin) lt ?
20
How do we detect an increasing trend?

• Infer increasing trend when PCT or PDT trend ? 1.0

21
Verification approach

• Simulation
• Multi-hop topology
• Cross traffic Exponential and Pareto
  interarrivals
• Varying load conditions
• Experiment
• Paths from U-Delaware to Greek universities and
  U-Oregon
• MRTG graphs for most heavily used links in path
• Compare pathload measurements with avail-bw from
  MRTG graph of tight link
• In 5-min interval, pathload runs W times, each
  for qi secs 5-min average avail-bw R reported by
  pathload

22
Verification Simulation

• Effect of tight link load
• Pathload range versus avail-bw during simulation
  (average of 50 runs)
• 5 Hop, Ctight10Mbps, utilnon-tight.6
• Center of pathload range good estimate of
  average of avail-bw

23
Verification Experiment

• Tight link U-Ioannina to AUTH (C8.2Mbps),
  ?1Mbps

24
Avail-bw Variability versus stream length

• Relative variation index
• Longer probing stream observe lower variability
• However, longer streams can be more intrusive

25
Avail-bw variability versus traffic load

• Heavier link utilization leads to higher avail-bw
  variability

26
Evaluation and Characterization of Available
Bandwidth Techniques

• N. Hu et al, JSAC, August 2003

27
Packet Pair Model Single Hop

• In single hop path
• Competing traffic may be inserted between packet
  pair
• Packet pair gap at receiver is function of cross
  traffic

Gi
Input
q
Go
t
Case1 Go Gi q/C lt Gi
Go
t
m/C
Case2 Gom/CGb
t

• Assumption Fluid cross traffic
• In practice, CT is bursty
• Packet train will capture average

28
Packet Train Model Single Hop
Gi
Gb
Gi
t
t
Where Total numer of probing packets MKN

• Assumption
• Only increased gap sees CT
• Packet dispersion not affected by CT at
  post-tight link

29
IGI and PTR Algorithm

• Start by sending out packet train with minimum
  gap ( gB)
• If gap_at_receiver ! gap_at_sender
• Send another train with increased gap
• Else calculate available bandwidth
• IGI Use equation
• PTR Available Bandwidth Rate of last train
  measured at receiver

30
Summary Single Hop Model

• IGI
• Need to know the capacity of tight link
• Assume that tight link is same as narrow link
• PTR
• Same as TOPP
• Relation of amount of cross-traffic and
  dispersion
• May not hold in multi-hop path

31
Open Issues

• Integrate avail-bw estimation methodology with
  application
• Use data packets in place of probe packets
• Implement avail-bw estimation algorithm in
  network interface card
• Allow routers to do avail-bw estimation
• Can we make some short-term predictions of
  avail-bw?
• High bandwidth paths
• Time stamping packets
• MTU limitations

32
Pathchirp

• Uses exponentially spaced packet train
• Main idea
• Avail-bw gt Rk , if qk gt qk1
• Avail-bw lt Rk , otherwise
• Can be used when probe packets are close enough
• Identify excursions consecutive packets show
  increased queuing delays
• Per-packet avail-bw Ek
• Final estimate Expected value of Rk