SACRIO - An Active Buffer Mangement Scheme for

Differentiaed Services Networks

Saikrishnan Gopalakrishnan Cisco Systems

Narasimha Reddy Texas A & M University

Outline

• Introduction

• Statement of Problem

• SACRIO - Approach and Implementation

• Results

• Summary

Introduction

• Diff-serv network - Markers and Droppers

• Scalable -- no per-flow state maintained in core routers

• RIO - RED with IN/OUT

• 3-drop precedence mechanism R/Y/G

Introduction(contd)

Introduction ( contd..)

• RIO - Core router recognizes IN/OUT

• Uses RED as buffer management

• Maintenance of per-flow state details are pushed to the edge routers

• IN/OUT packets are aggregated

Problems and Observation

• The achieved rates of flows with higher bandwidth < their target rates

• UDP will get unfair advantage when aggregated with TCP flows

• Lower the link’s apparent excess bandwidth closer the achieved rate with ideal target

Statement of Problem

• Achieved rates different from contract rates

• Difficulty in sharing excess bandwidth

• Can we do better without per-flow state?

Basic Ideas of SACRIO

• How to make the link function with no apparent excess bandwidth?– Apply Local Remarking of packets– IN and IN2 packets close to link capacity

• Convert OUT/IN into OUT/IN2/IN within the router

• Convert IN2 OUT on the output link

• How to do OUT IN2 conversion?

Local Remarking

Local Remarking

SACRIO ( Contd..)

• Allow a target rate of OUT packets per flow– Convert packets into IN2 below this rate

• If Per-flow state is maintained, this can be done accurately

• Sampling and Caching to segregate the flows whose OUTi > target

– Employ fixed amount of state transparently

Sampling and Caching

• Use fixed amount of transparent state

• Much like caches in memory systems– Transparent to the user/architecture– Improves performance– Allows scalable deployment of state– More state, more service– Provided service - a function of state and taffic

Sampling and Caching(contd)

• Sample flows to see if state needs to be maintained– State management policy

• Sampling allows scalability

• Cached flows can be regulated accurately– Resource management policy

• Provide aggregated service for other flows

Basis of SACRIO

• Local remarking of packets

• Employment of fixed amount of transparent state

SACRIO in Detail

Cost of SACRIO

• Per-packet handling cost = O(1)– Cached flows require an addition, division at

the end of observation period, computation of OUT to IN2 conversion probability

– Counters of total IN and OUT packets– Can be further reduced through sampling

• Memory cost = O(p), p = the state in the cache

SACRIO and 3-color markers

• 3-color markers are employed at the edge– Have no information of resource consumption

within the network

• SACRIO employed inside the network, locally at each router

3-color marking & SACRIO

SACRIO Performance

• SACRIO does not explicitly drop packets that are not converted into IN2– Local resource management policy controls

this

• Different state management policies, resource management policies achieve different goals.

Performance goals

• Curtail per-flow OUT BW to preset limit • Curtail per-flow OUT BW to fair share of

excess BW ( C - IN)/ n– Requires estimation of n, the # of flows– Can we use the cache to estimate n– Cache hit ratios could provide an idea

Estimating # of flows

• If flows are equal rate, n = K/h– K = cache size, h = hit ratio

• Traffic is not uniform across flows

• Caches capture high-rate flows

• Estimate1 N’ = n(pinned) + m/h’

• Estimate 2 N’’= (OUT/OUT(pinned) +1) N’

Simulations

UDP zero reservation

0

1

2

3

4

5

6

7

UDP 0.1 0.5 1 2

Reserved rate in Mbps

Ac

hie

ve

d T

hro

ug

hp

ut

in M

bp

s

Ideal RatePlain RIOSACRIO with 5statesSACRIO with 10statesSCARIO with 40 states3-color edge marker

UDP non-zero reservation

0

1

2

3

4

5

6

7

UDP 0.1 0 1 2

Reserved rate in Mbps

Ach

ieve

d T

hro

ug

hp

ut

in M

bp

s

Ideal

Plain RIO

SACRIO with 5 states

SACRIO with 10 states

SACRIO with 40 states

Link with different loads

0

1

2

3

4

5

6

7

25% 50% 75% 90%

Percentage of total link capacity that is reserved

UD

P r

ate

s in

Mb

ps

Ideal rate

RIO

SACRIO with 10 states

RTT bias reduction

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 0.1 0.5 1 2Reserved rate in Mbps

(ma

x-m

in)/

targ

et

Plain RIO

SACRIO with 5 states

SACRIO with 40 states

Multiple Routers

Additive property

0

1

2

3

4

5

6

7

UDP 0.1 0.5 1 2

Reserved Rate in Mbps

Ac

hie

ve

d T

hro

ug

hp

ut

in M

bp

s

Ideal Rate

Plain RIO

SACRIO with 2 routers

SACRIO with 3 routers

Complex Topology

Complex Topology

0

1

2

3

4

5

6

UDP(0) 0.1 0.4 0.5 1 2

Reserved Rate in Mbps

Ac

hie

ve

d T

hro

ug

hp

ut

in M

bp

s Ideal Rate

Plain RIO

SACRIO with 1 state

SACRIO with 3 states

When # of flows is not known

0

1

2

3

4

5

6

7

UDP(0) 0.1 0.5 1 2

Reserved Rate in Mbps

Ac

hie

ve

d t

hro

ug

hp

ut

in M

bp

s

Ideal Rate

Plain RIO

SACRIO - num of flows known

SACRIO - Estimate 1

SACRIO - Estimate 2

Effects of Under and over estimation of alpha

0

1

2

3

4

5

6

7

UDP(0) 0.1 0.5 1 2

Reserved Rate in Mbps

Ac

hie

ve

d R

ate

in

Mb

ps

Ideal rate

RIO

Underestimate alpha ( 50% oforiginal alpha)

Overestimate alpha (200% oforiginal alpha)

Effects of OP and RTT

3.6

3.65

3.7

3.75

3.8

3.85

3.9

3.95

4

4.05

0 1 2 3 4 5 6 7

Observation periods ( X times RTT )

Th

rou

gh

pu

t in

Mb

ps

RTT 8ms

RTT 16ms

RTT 64ms

SACRIO Scalability

• Seems to work with ns-2 simulations

• Do caches work in real networks?

• Analyzed Network traces at NLANR

SACRIO Scalability

SACRIO Scalability

Conclusion

• SACRIO employs Local remarking and limited transparent state

• SACRIO shown to curtail per-flow OUT BW consumption

• SACRIO is scalable based on analysis of internet traffic

• SACRIO is additive -better performance with more deployment

Future Work

• Build a Linux-based prototype router with limited state

• Demonstrate and verify the costs associated with fixed amount of state

• Use sampling and caching for other purposes such as traffic monitoring