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Shuchi Chawla Ashok Anand Chitra Muthukrishnan UW-Madison. Redundancy Elimination As A Network-Wide Service. Srinivasan Seshan Vyas Sekar CMU. Scott Shenker UC-Berkeley. Ram Ramjee MSR-India. Aditya Akella UW-Madison. Growing traffic vs. network performance. Other svcs (backup). - PowerPoint PPT Presentation
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REDUNDANCY ELIMINATION AS A NETWORK-WIDE SERVICE
Aditya AkellaUW-Madison
Shuchi Chawla Ashok Anand Chitra MuthukrishnanUW-Madison
Srinivasan Seshan Vyas SekarCMU
Ram RamjeeMSR-India
Scott ShenkerUC-Berkeley
Growing traffic vs. network performance2
Network traffic volumes growing rapidly Annual growth: overall (45%),
enterprise (50%), mobile (125%)*
Growing strain on installed capacity everywhere Core (Asian ISPs – 80-90%
core utilization), enterprise access, data center, cellular, wireless…
How to sustain robust network performance?
* Interview with Cisco CEO, Aug 2007, Network worldEnterprises
Mobile users Home users
Video
Data centers Web content
Other svcs(backup)
ISPcore
Strain on installed link capacities
Enterprises
Scale link capacities by suppressing duplicates
3
A key idea: suppress duplicates Popular objects, partial content
matches, backups, app headers Effective capacity improves ~ 2X
Many approaches Application-layer caches Protocol-independent schemes
Below app-layer WAN accelerators, de-duplication
Content distribution CDNs like Akamai, CORAL Bittorrent
Point solutions apply to specific link, protocol, or app
Mobile users Home users
Video
Data centers Web content
Other svcs(backup)
Wan Opt
Wan Opt
Dedup/archival
Dedup/archival
ISP HTTPcache
CDN
Universal need to scale capacities4
Wan Opt
Wan Opt
Dedup/archival
Dedup/archival ISP HTTP
cache
Network RedundancyElimination Service
Point solutions inadequate
RE: A primitive operation supported inherently in the network
o Applies to all links, flows (long/short), apps, unicast/multicast
o Transparent network service; optional end-point modifications
o How? Implications?
Architectural support to address universal need to
scale capacities? Implications?
Bittorrent
✗ Point solutions:Little or no benefit in the core
✗ Point solutions:Other links must re-implement specific RE mechanisms
✗ Point solutions: Only benefit system/app attached
How? Ideas from WAN optimization
5
5
Cache Cache
WAN link
Data center Enterprise Network must examine byte streams, remove duplicates, reinsert Building blocks from WAN optimizers: RE agnostic to application, ports or
flow semantics Upstream cache = content table + fingerprint index
Fingerprint index: content-based names for chunks of bytes in payload Fingerprints computed for content, looked up to identify redundant byte-
strings Downstream cache: content table
Internet2
Packet cache at every router
Network RE service: apply protocol-indep RE at the packet-level on network links IP-layer RE service
From WAN acceleration to router packet caches
6
Wisconsin
BerkeleyCMU
Router upstream removes redundant bytes
Router downstream reconstructs full packet
(Hop-by-hop works for slow links
Alternate approaches to scale to faster links…)
Implications overview: Performance and architectural benefits
7
Improved performance everywhere even if partially enabled Generalizes point deployments and app-specific approaches
Benefits all network end-points, applications Crucially, benefits ISPs
Improved switching capacity, responsiveness to sudden overload
Architectural benefits Enables new protocols and apps
Min-entropy routing, RE-aware traffic engineering (intra- and inter-domain) Anomaly detection, in-network filtering of unwanted traffic
Simplifies/improves apps: need not worry about using network efficiently Application control messages & headers can be verbose better diagnostics Controlling duplicate transmission in app-layer multicast is a non-issue
Internet2
Implications example: Performance benefits8
Network RE 12 pkts
(ignoring tiny packets)
Without RE 18 pkts
33% lower
Wisconsin
BerkeleyCMU
Generalizes pointdeployments
Benefits ISPs: improve effective switching capacity
62 packets
32 packets
32 packets
Wisconsin
Internet2
Implications example: New protocols
9
RE + routing 10 pkts
Simple RE 12 pkts
BerkeleyCMU
9
✓ Redundancy-based anomaly detectors
✓ Network-assisted spam filtering ✓ New content distribution
mechanisms
✓ Minimum-entropy routing✓ New, flexible traffic engineering
mechanisms✓ Inter-domain protocols
Network RE service: Quantitative results10
Analysis of 12 enterprises: traffic 15-60% redundant [SIGMETRICS 09] ~1GB of cache sufficient to identify redundancies DRAM or PCM (PRAM) on routers
Network RE benefits both ISPs and end-networks [SIGCOMM 08] Upto 15-50% better util, responsive TE, control inter-domain traffic impact Centralized algorithm for min-entropy routing (using “redundancy profiles”)
Reduces utilization by a further 10-25% in intra-domain case Inter-domain min-entropy routing: gains much more significant (50-80%)
Is network RE viable at high speeds? Not in its current form… Compression is slow: limits hop-by-hop speed at each hop to 2.5Gbps
Acceptable for access, wireless, cellular links, not for the core Also, wastes memory on multiple routers limits effectiveness
SmartRE: Concerted network-wide RE11
Toss out link-by-link view; treat RE as a network-wide problem per ISP [Current work]
Memory usage: each packet compressed/un-compressed once Throughput: allow reconstruction multiple hops away from compression
Stand-alone reconstruction much faster when freed from dependence on compression immediately upstream
Reconstructor can reconstruct a lot more, from multiple different compression agents Resource-awareness: carefully account for network and device resources,
and traffic Compression/reconstruction/caching locations decided based on memory capacity
and memory operations Also consider global TE objectives
Just 4% from ideal RE (no memory or processing constraints)
Summary and future directions12
RE service to scale link capacities everywhere Architectural niceties and performance benefits High speed router RE seems feasible Future directions
End-host participation Role of different memory technologies – DRAM, flash and PCM Theoretical issues – pricing and economics, routing policy, network
design Network coding as an alternative to compression