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 IssuesAnd Performance”. Sigcomm 2001.

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.

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:

ii

ii

r

Cr

Router scheduling mechanisms

• Fair Queueing has “stolen bandwidth” problem.• Example: suppose two types of flows; r2 > r1; and

= 0.

• Type 1 flow is admitted if r1(n1+n2) < C; type 2 flow is admitted if r1n1 + r2n2 < C.

• When r1(n1+n2) = C, type 1 flows experience no loss; type 2 flows’ loss ratio is (r2 – r1)/ r2

Best-Effort (TCP) Traffic

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

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

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

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.

Thrashing

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

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.

Traffic Sources

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.

Longer Probing Time

• In-band dropping

• Lower loss ratio and lower utilization

High Load – In-band Dropping

• 400% offered load; 75% blocking prob.

• High loss

• Slow-start probing does better

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

High Load - Marking

Heterogeneous Traffic

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

• MBAC has similar behavoir

Multi-hop

Loss Probability

Multi-hop – Blocking Probability

Sharing FIFO Queue with TCP

• Two lower curves are for = 0.04 and 0.05

• TCP prevents AC traffic to be admitted

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.