Endpoint Admission Control

1
Endpoint Admission Control

• WebTP Presentation
• 9/26/00
• Presented by Ye Xia

Reference L. Breslau, E. W. Knightly, S.
Shenkar, I. Stoica, H. Zhang, Endpoint
Admission Control Architectural Issues And
Performance. Sigcomm 2001.
2
Why Endpoint?

• Aim of admission control (AC) provide QOS to
  real-time flows
• IntServ has per-flow and router-based AC
  requires hop-by-hop signalling (RSVP) each
  router keeps per-flow state scalability problem.
• DiffServ lacks AC providing QOS to each flow is
  not a primary concern but more scalable.
• Hope endpoint AC can combine the strength of
  both.

3
Algorithm

• Admission decision based on loss only
• Probing phase each flow (at the end host) probes
  the network for loss or marking ratio (say, for 5
  seconds)
• If the ratio is below a threshold, ?, flow is
  admitted.
• Loss model

4
Router scheduling mechanisms

• Fair Queueing has stolen bandwidth problem.
• Example suppose two types of flows r2 gt r1 and
  ? 0.
• Type 1 flow is admitted if r1(n1n2) lt C type 2
  flow is admitted if r1n1 r2n2 lt C.
• When r1(n1n2) C, type 1 flows experience no
  loss type 2 flows loss ratio is (r2 r1)/ r2

5
Best-Effort (TCP) Traffic

• Need to isolate TCP traffic and AC traffic.
  Consider what happens when
• TCP traffic source is idle
• TCP induces loss

6
Architecture Choice

• Priority queues
• High priority for AC traffic
• Low priority for TCP traffic
• Probe traffic may take intermediate priority
• FIFO queueing for AC traffic
• AC traffic is rate-limited and served at that
  rate.
• non-work conserving scheduler

7
Probing Algorithms

• Difficulty in sampling loss/mark ratio
• Out-of-band probing
• probing traffic takes lower priority than regular
  data traffic
• Probing traffic has higher loss
• ECN marking
• marking rate higher than dropping rate
• Router simulates a virtual queue drained at 90
  capacity
• Problem cannot relate specified threshold, ?,
  with actual loss ratio

8
Slow-Start Probing

• Thrashing when many flows waiting for admission,
  probing traffic overloads the link.
• Cause flow of rate r probes at rate r.
• Solution slow-start probing. Gradually ramp up
  rate of probing traffic.

9
Thrashing

• Utilization collapses for both in-band and
  out-band probing
• For in-band probing, data loss ratio increases as
  well

10
Simulation Models

• Leaky-bucket constrained traffic sources
• On-off sources and movie traces
• Poisson arrival of flows exponential holding
  time with mean 300s.
• Interfering TCP traffic needs not to be
  simulated.
• ? 0, .01, .02, .03, .04, .05, .1, .15, .2.
• Comparison with router-based AC.

11
Traffic Sources
12
Basic Scenario

• Offered load 20 blocking prob.
• Loss rate competitive with MBAC
• ? is meaningful only for in-band drop. Other
  probing algo. reduce utilization.
• For in-band drop, 0.4 loss rate when ? 0.
• For out-band marking, low loss ratio can be
  achieve after probing for 5 seconds.

13
Longer Probing Time

• In-band dropping
• Lower loss ratio and lower utilization

14
High Load In-band Dropping

• 400 offered load 75 blocking prob.
• High loss
• Slow-start probing does better

15
High Load Out-band Probing

• All algorithms are similar
• Probing traffic does not cause extra loss to data
  traffic
• Slow-start probing has higher utilization and
  loss ratio

16
High Load - Marking
17
Heterogeneous Traffic

• Large flow has 4 times the peak rate and higher
  blocking probability
• MBAC has similar behavoir

18
Multi-hop
Loss Probability
19
Multi-hop Blocking Probability
20
Sharing FIFO Queue with TCP

• Two lower curves are for ? 0.04 and 0.05
• TCP prevents AC traffic to be admitted

21
Comments

• Quick conclusion on queueing/scheduling
• Reconcile scheduling with end-to-end measurement
• Probing time is long.
• can aggregate probing traffic
• What to probe?
• AC criteria needs to be expanded (not just loss)
• ? has no relationship with actual loss ratio
• WebTP has similar setup and similar issues.