SRED: Stabilized RED

T. Ott, T.V. Lakshman, L. Wong

Presented by

King-Shan Lui

Diff. With RED

• SRED estimates number of active flows

• Misbehaving flows can be identified without keeping per-flow state

• Drop probabilities are adjusted according to number of active flows

• No computation of average queue length

• Assume TCP flows

Main Idea

• Number of active flows number of different flows in the buffer

• A misbehaving flow has a lot of packets in the buffer

• When a packet arrives, compare it with a packet arrived before. If they belong to the same flow, a hit occurs.

Zombie List

• A list of M recently seen flows, zombies

• Longer memory than the buffer alone

• Information for each zombie: – Count: number of packets of this zombie

received– timestamp: arrival time of the most recently

received packet

Zombie List Operations

• Zombie list is not full– Insert the flow with count = 0, timestamp = ta

• Zombie list is full– Randomly pick a zombie

• Hit: count += 1, timestamp = ta

• No hit: with prob. p that the zombie is replaced

• The arrived packet may be dropped no matter there was a hit or not

Hits & Number of Active Flows

• Zombie list loses memory once every M/p packets

• Few active flows more hits

• Misbehaving flows cause more hits than well-behaved flows

Hit Frequency

• P(t) – hit frequency around the time of the tth packet arrives at the buffer

• Hit(t) = 1 when hit; Hit(t) = 0, otherwise

• P(t) = (1 – )P(t – 1) + *Hit(t)

• Proposition: P(t)-1 is a good estimate for the effective number of active flows

Proposition Argument

• P(arrival packet belongs to flow i) = i

• P(Hit(t)=1) = i2

• 1/N i2 1

• Symmetric case: N flows, i = 1/N

– P(t) = 1/N (exact estimate)

• Asymmetric case: infinite flows, i = 2-i

– P(t) = 3/16 (effective number of active flows)

Simple Stabilized RED

• Target buffer occupation – QTarget buffer occupation – Q00

• Set a drop probability – pSet a drop probability – p

• Square root law: congestion window of each flow, cwnd p-1/2

• Sum of N congestion windows – N * p-1/2

• Q0 = N*p-1/2 p = (N/Q0)2

• p is proportional to N2

• Buffer capacity – B

• Current buffer size – q

• pzap = psred(q) *

• psred(q) = pmax if 1/3*B q < B

= ¼ * pmax if 1/6*B q < 1/3*B

= 0 if 0 q < 1/6*B

Simple Stablized RED (cont.)

2(256*P(t))

11,min

psred(q)

• Depends on current q, not history of q

• Three levels psred

q

pmax

B

1

B3

1B

6

1

• Ratio 4: halving the

congestion windows

pzap

• When number of flows 256

pzap ~ psred/65356 * (number of flows)2

• When number of flows > 256

pzap = psred

• Avoid pzap becomes too large

• pzap depends on q and P(t)

Full SRED

)(

)(1**

tP

tHit

(256*P(t))

11,minpp

2sredzap

Increase the drop probabilities of

misbehaving flows

Simulation Results

Simulation Results

• SRED stablilizes the buffer occupancy when N 256 as q is independent of N

• q increases slightly when N = 1000

• Buffer occupation almost never decreases below B/6– could narrow the band where psred(q) = pmax/4

Contributions

• SRED provides a mechanism to estimate number of active flows and identify misbehaving flows

• SRED controls buffer occupancy by adjusting drop probabilities using estimated number of active flows

Remaining Issues

• Many parameters to be tuned: psred, pmax, , M, p, magic 256.

• Extra storage: Zombie list vs. per-flow state– M ~ 1000 > 256