Packet Caches on Routers: The Implications of Universal Redundant

Traffic Elimination

Ashok Anand, Archit Gupta, Aditya AkellaUniversity of Wisconsin, Madison

Srinivasan SeshanCarnegie Mellon University

Scott Shenker University of California, Berkeley

1

Redundant Traffic in the Internet

• Lots of redundant traffic in the Internet

• Redundancy due to…– Identical objects– Partial content

match (e.g. page banners)

– Application-headers

– …2

Same content traversing same

set of links

Time TTime T + 5

Redundancy Elimination• Object-level caching

– Application layer approaches like Web proxy caches – Store static objects in local cache– [Summary Cache: SIGCOMM 98, Co-operative Caching: SOSP 99]

• Packet-level caching – [Spring et. al: SIGCOMM 00]– WAN Optimization Products: Riverbed, Peribit, Packeteer, ..

3

Packet-Cache Packet-Cache

Access linkInternet

Enterprise

Packet-level caching is better than object-level caching

Benefits of Redundancy Elimination– Reduces bandwidth usage cost– Reduces network congestion at access links – Higher throughputs– Reduces in transfer completion times

4

Towards Universal RE• However, existing RE approaches apply only to point

deployments– E.g. at stub network access links, or between branch offices

• They only benefit the system to which they are directly connected.

• Why not make RE a native network service that everyone can use?

5

Our Contribution• Universal redundancy elimination on routers is

beneficial

• Re-designing the routing protocol to be redundancy aware gives furthermore benefits

• Practical to implement redundancy elimination

6

Internet2

Universal Redundancy Elimination At All Routers

Total packets with universal RE= 12 (ignoring tiny packets)

Upstream router removes redundant bytes. Downstream router reconstructs full packet

7

Total packets w/o RE = 18

Wisconsin

BerkeleyCMU

33%

Packet cache at every router

Benefits of Universal Redundancy Elimination

• Subsumes benefits of point deployments• Also benefits Internet Service Providers

– Reduces total traffic carried better traffic engineering

– Better responsiveness to sudden overload (e.g. flash crowds)

• Re-design network protocols with redundancy elimination in mind Further enhance the benefits of universal RE

8

Redundancy-Aware Routing

Total packets with RE + routing= 10 (Further 20% benefit )

9

Total packets with RE = 12

Wisconsin

BerkeleyCMU

45%

ISP needs information of traffic similarity between CMU and Berkeley

ISP needs to compute redundancy-aware routes

Redundancy-Aware Routing• Intra-domain Routing for ISP• Every N minutes

– Each border router computes a redundancy profile for the first Ts of the N-minute interval

• Estimates how traffic is replicated across other border routers• High speed algorithm for computing profiles

– Centrally compute redundancy-aware routes• Route traffic for next N minutes on redundancy-aware

routes. • Redundancy elimination is applied hop-by-hop

10

CMU

Redundancy Profile Example

11

Internet2

Dataunique,pitsburgh= 30 KBDataunique,Berkeley= 30 KBDatashared= 20 KB

11

Wisconsin

Berkeley

TotalCMU= 50 KBTotalBerkeley= 50 KB

Centralized Route Computation• Linear Program• Objective: minimize the total

traffic footprint on ISP links• Traffic footprint on each link as

latency of link times total unique content carried by the link

• Compute narrow, deep trees which aggregate redundant traffic as much as possible

• Impose flow conservation and capacity constraints

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CentralizedPlatform

Route computation

Inter-domain Routing• ISP selects neighbor AS and the border router for each

destination• Goal: minimize impact of inter-domain traffic on intra-

domain links and peering links.• Challenges:

– Need to consider AS relationships, peering locations, route announcements

– Compute redundancy profiles across destination ASes

• Details in paper

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Trace-Based Evaluation

• Trace-based study– RE + Routing: Redundancy aware routing– RE: Shortest path routing with redundancy elimination– Baseline: Compared against shortest path routing without

redundancy elimination • Packet traces

– Collected at University of Wisconsin access link– Separately captured the outgoing traffic from separate group of

high volume Web servers in University of Wisconsin• Represents moderate-sized data center

• Rocketfuel ISP topologies• Results for intra-domain routing on Web server trace

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Benefits in Total Network Footprint

• Average redundancy of this Web server trace is 50% using 2GB cache

• ATT topology• 2GB cache per router• CDF of reduction in network

footprint across border routers of ATT

• RE gives reduction of 10-35%

• (RE + Routing) gives reduction of 20-45%

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0.1 0.2 0.3 0.40

0.2

0.4

0.6

0.8

1RE RE +Routing

Reduction in Network Footprint

Frac

tion

of B

orde

r Rou

ters

When is RE + Routing Beneficial?• Topology effect

– E.g., multiple multi-hop paths between pairs of border routers

• Redundancy profile– Lot of duplication across border routers

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Synthetic Trace Based Study

• Synthetic trace for covering wide-range of situations– Duplicates striped across border routers in ISP (inter-flow

redundancy)

– Low striping across border routers , but high redundancy with in traffic to a border router (intra-flow-redundancy)

– Understand topology effect

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Benefits in Total Network Footprint

• Synthetic trace, average redundancy = 50%

• ATT (7018) topology• Trace is assumed to enter at

Seattle • RE + Routing, is close to RE at

high intra-flow redundancy, 50% benefit

• RE has benefit of 8% at zero intra-flow redundancy

• RE + Routing, gets benefit of 26% at zero intra-flow redundancy.

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0 0.2 0.4 0.6 0.8 10

0.1

0.2

0.3

0.4

0.5

0.6RE RE+Routing

Intra-flow redundancy

Redu

ction

in N

etw

ork

Foot

prin

t

Benefits in Max Link Utilization

• Link capacities either 2.5 or 10 Gbps

• Comparison against traditional OSPF based traffic engineering (SP-MaxLoad)

• RE offers 1-25% lower maximum link load .

• RE + Routing offers 10-37% lower maximum link load.

Max link Utilization = 80%, for SP-MaxLoad19

(0.2,1.0) (0.5,0.5)0

0.050.1

0.150.2

0.250.3

0.350.4

RE RE + Routing

(Overall redundancy, Inter flow redundancy)

Redu

ction

inM

ax Li

nk U

tiliz

ation

Evaluation Summary• RE significantly reduces network footprint• RE significantly improves traffic engineering

objectives• RE + Routing further enhances these benefits• Highly beneficial for flash crowd situations• Highly beneficial in inter-domain traffic

engineering

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Implementing RE on Routers

21

Fingerprint table Packet store

Fingerprint s

• Main operations– Fingerprint computation

• Easy, can be done with CRC

– Memory operations, Read and Write

High Speed Implementation• Reduced the number of memory operations per

packet– Fixed number of fingerprints (<10 per packet)– Used lazy invalidation of fingerprint for packet

eviction– Other optimizations in paper

• Click-based software prototype runs at 2.3 Gbps (approx. OC 48 speed ).

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Summary• RE at every router is beneficial ( 10-50%)

• Further benefits (10-25%) from redesigning routing protocol to be redundancy-aware.

• OC48 speed attainable in software

23

Thank you

24

Backup

25

Flash Crowd Simulation

1 1.5 2 2.5 3 3.5 4 4.50.30.40.50.60.70.80.9

1

SP-MaxLoad SP-RERA

Volume Increment Factor

Max

Link

Util

izati

on

• Flash Crowd: Volume increases at one of the border routers– Redundancy ( 20% -> 50%)– Inter Redundancy Fraction

(0.5 -> 0.75)– Max Link Utilization without

RE is 50%• Traditional OSPF traffic

engineering gets links at 95% utilization at volume increment factor > 3.5

• Whereas SP-RE at 85% , and RA further lower at 75% 26

Impact of Stale Redundancy Profile

1 2 3 4 50

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

SP-RE RA RA-stale

High Volume /24 traces

Redu

ction

in N

etw

ork

Foot

prin

t

• RA relies on redundancy profiles.

• How stable are these redundancy profiles ?

• Used same profile to compute the reduction in network footprint at later times ( with in an hour)

• RA-stale is quite close to RA

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High Speed Implementation

• Use specialized hardware for fingerprint computation• Reduced the number of memory operations per packet

– Number of memory operations is function of number of fingerprints. Fixed the number of sampled fingerprints

– During evicting packet, explicit invalidating fingerprint require memory operations. Used lazy invalidation

• Fingerprint pointer is checked for validation as well as existence.

• Store packet-table and fingerprint-table in DRAM for high-speed– Used Cuckoo Hash-table. As simple-hash based fingerprint

table is too large to fit in DRAM

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Base Implementation Details (Spring et. al)

• Compute fingerprints per packet and sample them• Insert packet into packet store• Check for existence of fingerprint pointer to any

packet, for match detection. • Encode the match region in the packet.• Insert each fingerprint into Fingerprint table.• As store becomes full, evict the packet in FIFO manner• As a packet gets evicted, invalidate its corresponding

fingerprint pointers

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