Packet Caches on Routers: The Implications of Universal Redundant Traffic Elimination Ashok Anand, Archit Gupta, Aditya Akella University of Wisconsin, Madison Srinivasan Seshan Carnegie Mellon University Scott Shenker University of California, Berkeley 1
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Packet Caches on Routers: The Implications of Universal Redundant Traffic Elimination
Packet Caches on Routers: The Implications of Universal Redundant Traffic Elimination. Ashok Anand , Archit Gupta, Aditya Akella University of Wisconsin, Madison Srinivasan Seshan Carnegie Mellon University Scott Shenker University of California, Berkeley. - PowerPoint PPT Presentation
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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 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
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
27
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
28
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