Network and Protocol Mechanisms:

How well do they collaborate?

Ageliki Tsioliaridou

What we investigate

• Transport Protocols come at various versions - some aggressive some conservative

• Network mechanisms differ in sophistication regarding the scheduling, forwarding and dropping policy

We claim that

• Evaluation of a new mechanism cannot be investigated alone; that is, one has to study its impact on the different mechanisms.

• A protocol may lack the sophistication needed to exploit the potential of a new network mechanism, and vice versa

• the chicken or the egg

More specifically

• We select two widely used network mechanisms (DT and RED); we also introduce a new mechanism, namely Fr-RED; and we discuss the potential of another mechanism which we will develop soon

• We monitor the interaction of these mechanisms with the congestion control mechanisms of Tahoe, Reno, NewReno and Vegas

1st scenarioMany flows compete for low bandwidth. The contention level is high. Congestion event is persistent2nd scenarioA small number of flows occupy the transmission channel. The contention level is low. Congestion event is transient3rd scenarioSome flows co-exist in the communication channel and suddenly some other flows enter the link 4th scenario Some flows co-exist in the communication channel and suddenly some of them finish their task and leave the channel

Experiments

Topology: dumbbell

1st scenario

Topology:dumbbellbw_1=0.1Mbps, bw_2=1Mbps, bw_3=0.1Mbps

Remarks that have to be highlighted:1. If the protocol is Vegas or Tahoe, the combination with

drop give us better results in throughput2. If the protocol is Reno or Newreno, the combination

with red give us better results not only in goodput but also in throughput

3. When the router’s algorithm is drop, the performance of Vegas in goodput is higher than the other three

TCP Tahoe

goodput throughput

tahoe

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows

(bps

)

DropTail

Red

tahoe

100000

110000

120000

130000

140000

150000

160000

170000

180000

50 60 70 80 90 100 110 120

number_of_flows(b

ps)

DropTail

Red

TCP Vegas

goodput throughput

vegas

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows(b

ps)

DropTail

Red

vegas

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows

(bps

)

DropTail

Red

TCP Reno

goodput throughput

reno

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows

(bps

)

DropTail

Red

reno

0

50000

100000

150000

number_of_flows(b

ps)

DropTail

Red

TCP NewReno

goodput throughput

nr

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows

(bps

)

DropTail

Red

nr

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows

(bps

)

DropTail

Red

goodput throughput

DropTail

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows

(bps

) tahoe

reno

nr

vegas

Droptail

020000400006000080000

100000120000140000160000180000

50 60 70 80 90 100 110 120

number_of_flows

(bps

) tahoe

reno

nr

vegas

DropTail

2nd scenario

Topology:dumbbell

bw_1=1Mbps, bw_2=50Mbps, bw_3=10Mbps

Remarks that have to be highlighted:

1. If the protocol is Tahoe the combination with drop give us better results

2. If the transport protocol is Vegas the value of goodput doesn’t get influence from the router’s algorithm, and it is higher than the value of other three protocols.

TCP Tahoe

goodput throughput

tahoe

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

10 20 30 40 50 60

number_of_flows(b

ps)

droptail

red

tahoe

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

10 20 30 40 50 60

number_of_flows

(bps

)

droptail

red

TCP Vegas

vegas

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

10 20 30 40 50 60

number_of_flows

(bps

)

droptail

red

vegas

1000000

2000000

3000000

4000000

5000000

6000000

7000000

10 20 30 40 50 60

number_of_flows(b

ps)

droptail

red

goodput throughput

goodput throughput

red

0

2000000

4000000

6000000

10 20 30 40 50 60number_of_flows

(bps

) tahoe

reno

nr

vegas

red

1000000

2000000

3000000

4000000

5000000

6000000

7000000

10 20 30 40 50 60

number_of_flows(b

ps)

tahoe

reno

nr

vegas

RED

3nd scenario

Topology:dumbbell

bw_1=1Mbps, bw_2=50Mbps, bw_3=10Mbps

Remarks that have to be highlighted:

• The combination of Vegas and Drop Tail algorithm gives us the worst value in fairness

• When of the transport protocol is Tahoe, the Drop Tail algorithm performs better in goodput

• If the transport protocol is Vegas it gives the best value in goodput

Fairness

droptail

0,600000,650000,700000,750000,800000,850000,900000,950001,00000

10-100

20-100

30-100

40-100

50-100

60-100

tahoe

reno

nr

vegas

TCP Tahoe

tahoe

3000000

35000004000000

45000005000000

5500000

60000006500000

7000000

10-100

20-100

30-100

40-100

50-100

60-100

number_of_flows

(bps

)

droptail

red

goodput

goodput throughput

goodput throughput

TCP Vegas

red

3000000

3500000

4000000

4500000

5000000

5500000

6000000

6500000

7000000

10-100 20-100 30-100 40-100 50-100 60-100

number_of_flows

(bps)

tahoe

reno

nr

vegas

red

3000000

3500000

4000000

4500000

5000000

5500000

6000000

6500000

7000000

10-100 20-100 30-100 40-100 50-100 60-100

number_of_flows

(bp

s)

tahoe

reno

nr

vegas

droptail

3000000

3500000

4000000

4500000

5000000

5500000

6000000

6500000

7000000

10-100 20-100 30-100 40-100 50-100 60-100

number_of_flows

(bps)

tahoe

reno

nr

vegas

droptail

3000000

3500000

4000000

4500000

5000000

5500000

6000000

6500000

7000000

10-100 20-100 30-100 40-100 50-100 60-100

number_of_flows

(bps)

tahoe

reno

nr

vegas

4th scenario

Topology:dumbbellbw_1=1Mbps, bw_2=50Mbps, bw_3=10Mbps

Remarks that have to be highlighted:• When the transport protocol is Reno, the Drop

algorithm results better in fairness• When of the transport protocol is Tahoe, the drop

algorithm perfumes better in goodput• If the transport protocol is Vegas the value of goodput

is higher than the value of other three protocols.

TCP Reno

fairness

reno

0,0000

0,2000

0,4000

0,6000

0,8000

1,0000

100-50 100-40 100-30 100-20 100-10

number_of_flows

droptail

red

tahoe

200000030000004000000500000060000007000000

100-50

100-40

100-30

100-20

100-10

droptail

red

TCP Tahoe

goodput

goodput throughput

goodput throughput

droptail

20000002500000300000035000004000000450000050000005500000600000065000007000000

100-50 100-40 100-30 100-20 100-10

number_of_flows

tahoe

reno

nr

vegas

red

2000000

3000000

4000000

5000000

6000000

7000000

100-50 100-40 100-30 100-20 100-10

number_of_flows

tahoe

reno

nr

vegas

droptail

20000002500000300000035000004000000450000050000005500000600000065000007000000

100-50 100-40 100-30 100-20 100-10

number_of_flows

tahoe

reno

nr

vegas

red

2000000

3000000

4000000

5000000

6000000

7000000

100-50 100-40 100-30 100-20 100-10

number_of_flows

tahoe

reno

nr

vegas

Random Early Drop (RED)

A router that implements RED uses two threshold values to mark positions in the queue: Tmin and Tmax

AvgLen

TminTmax2* Tmax

A drop event is characterize either as FORCED drop nor as UNFORCED drop

DROP LOGIC

1.If avg > 2* maxthresh , this is a FORCED drop

2.If Tmin < avg < 2*maxthresh, this may be an UNFORCED drop. The drop probability changes from 0 to max_p as the avg varies from Tmin to Tmax and from max_p to 1 as the avg varies from Tmax to twice Tmax (max_p=1/linterm)

3.If (q+1) > hard q limit, this is a FORCED drop

RED drop principle:

FORCED dropThe victim is either the arriving packet (default) or the front

packet of the queue or any packet of packet (random)UNFORCED dropThe victim is the arriving packet

fr-RED drop principle :

FORCED dropThe victim is the arriving packetUNFORCED dropThe victim is the front packet of the queue

Our goal is:

To indicate senders faster that the congestion is going to happen The TCP congestion mechanism of senders will be triggered faster

Experiments

Topology: dumbbell

scenario

bw_1=bw_2=bw_3=1Mbps

TCP Tahoe

fairness

0,5000

0,6000

0,7000

0,8000

0,9000

1,0000

3 4 5 6 7 8 9 10

number_of_flows

tahoe

tahoefr

throughput

100000

110000

120000

130000

140000

3 4 5 6 7 8 9 10

number_of_flows

(bps

) tahoe

tahoefr

goodput

100000

110000

120000

130000

140000

3 4 5 6 7 8 9 10

number_of_flows

(bps

) tahoe

tahoefr

Buffer_size (bs):100Link_delay:7msTmax:3*bs/4=75Tmin:Tmax/3=25

TCP Tahoe

fairness

0,5000

0,6000

0,7000

0,8000

0,9000

1,0000

3 4 5 6 7 8 9 10

number_of_flows

tahoe

tahoefr

fairness

0,5000

0,6000

0,7000

0,8000

0,9000

1,0000

3 4 5 6 7 8 9 10

number_of_flows

tahoe

tahoefr

goodput

100000

105000

110000

115000

120000

125000

130000

135000

140000

3 4 5 6 7 8 9 10

tahoe

tahoefr

throughput

100000

105000

110000

115000

120000

125000

130000

135000

140000

3 4 5 6 7 8 9 10

number_of_flows

(bp

s)

tahoe

tahoefr

Buffer_size (bs):100 Buffer_size (bs):200

goodput

100000105000110000115000120000125000130000135000140000

3 4 5 6 7 8 9 10

number_of_flows

(bp

s)

tahoe

tahoefr

throughput

100000105000110000115000120000125000130000135000

3 4 5 6 7 8 9 10

number_of_flows

(bp

s)

tahoe

tahoefr

The concept of a new network mechanism:

When congestion is going to happen rearrange the order of the packets at the queue

The concept of a new congestion control mechanism:

The sender should adjust its rate, depending on the reordering of the incoming packets at the receiver.

Future work

• Evaluation of fr-red at high-speed networks• Implementation of the new concept of

congestion avoidance mechanism