the edge of smartness

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Copyright © 2005 Department of Computer Science

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The Edge of Smartness

Carey WilliamsonDepartment of Computer ScienceUniversity of Calgary

Email: [email protected]

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Main Message• Now, more than ever, we need “smart edge”

devices to enhance the performance, functionality, and efficiency of the Internet

Application

Transport

Network

Data Link

Physical

Application

Transport

Network

Data Link

PhysicalCoreNetwork

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The End-to-End Principle• Central design tenet of the Internet (simple core)• Represented in design of TCP/IP protocol stack• Wikipedia: Whenever possible, communication

protocol operations should be defined to occur at the end-points of a communications system

• Some good reading:– J. Saltzer, D. Reed, and D. Clark, “End-to-End

Arguments in System Design”, ACM ToCS, 1984– M. Blumenthal and D. Clark, “Rethinking the Design

of the Internet: The end to end arguments vs. the brave new world”, ACM ToIT, 2001

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The End-to-End Principle: Revisited• Claim: The ongoing evolution of the Internet is

blurring our notion of what an end system is• This is true for both client side and server side

– Client: mobile phones, proxies, middleboxes, WLAN– Server: P2P, cloud, data centers, CDNs, Hadoop

• When something breaks in the Internet protocol stack, we have to find a suitable retrofit to make it work properly

• We have done this repeatedly for decades, and will likely keep doing it again and again!

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(Selected) Existing Examples• Mobility: Mobile IP, MoM, Home/Foreign Agents• Small devices: mobile portals, content transcoding• Web traffic volume: proxy caching, CDNs• Wireless: I-TCP, Proxy TCP, Snoop TCP, cross-layer• IP address space: Network Address Translation (NAT)• Multi-homing: smart devices, cognitive networks, SIP• Big data: P2P file sharing, BT, download managers• P2P file sharing: traffic classification, traffic shapers• Security concerns: firewalls, intrusion/anomaly detection• Intermittent connectivity: delay-tolerant networks (DTN)• Deep space: inter-planetary IP

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The Smart Edge• Similar “tweaks” will be needed at server side• Putting new functionality in a “smart edge”

device seems like a logical choice, for reasons of performance, functionality, efficiency, security

• What is meant by “smart”?– Interconnected: one or more networks; define basic

information units; awareness of location/context– Instrumented: suitably represent user activities;

location, time, identity, and activity; perf metrics– Intelligent: provisioning, management, adaptation;

appropriate decision-making in real-time

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Example 1:Redundant Traffic Elimination

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Basic Principles of RTE• If you can “remember” what you have

sent before, then you don’t have to send another copy

• Redundant Traffic Elimination (RTE)

• Done using a dictionary of chunks and their associated fingerprints

• Examples:– Joke telling by certain CS professors– Data deduplication in storage systems (90% savings)– “WAN Optimization” in networks (20% savings)

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Redundant Traffic Elimination (RTE)

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• Purpose: Use bottleneck link more efficiently• Basic idea: Use a cache of data chunks to avoid

transmitting identical chunks more than once

• RTE process:– Divide IP packet into chunks– Select a subset of chunks– Store a cache of chunks at two ends

of a network link or path– Transfer only chunks that are not cached

• Works within and across files• Combines caching and chunking

C hunk A C hunk B C hunk C

D istance O verlap

C hunk cache

Chunk B

Chunk A

Chunk CFP C

FP A

FP B

.. ... .

.. ... .. ..

. ... ..

. ..

F P A = fingerp rin t (C hunk A )

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RTE Process Pipeline

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Packet

NIC

Chunking(no overlap)

FIFO cachemanagement

Forwarding

Yes

Yes

Packet

NIC

Fingerprinting

Forwarding

Large enough?

No

Next chunk

Overlap OK?

No

non-FIFO cachemanagement

Current Proposed

Fingerprinting

Chunk expansion Content

promising?No

Yes

Improve traditional RTE

Exploit traffic non-uniformities: Packet size (bypass

technique) Chunk popularity

(new cache management scheme)

Content type (content-aware RTE)

Up to 50% more detected redundancy

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Type Value Description Example

Nulls 57.1% Consecutive null bytes 0x00000000

Text 16.7% Plain text (English) Gnutella

HTTP 7.3% HTTP directives Content-Type:

Mixed 6.2% Plain text and other chars 14pt font

Binary 5.8% Random characters 0x27c46128

HTML 3.7% HTML code fragments <HTML> <p>

Char+1 3.2% Repeated text chars AAAAAAAz

Main Sources of Redundancy

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RTE Summary

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• Improves traditional RTE savings by up to 50%• Techniques can be used individually or together• RTE very beneficial for wireless traffic

– 30% of users have 10-50% redundant traffic

• Proposed a novel content-aware RTE– Improve RTE savings by up to 38%

• Challenges of content-aware RTE– Needs refinement to be able to work on real traces, or

exploit an appropriate traffic classification scheme

– Needs improvement in execution time

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Example 2:The TCP Incast Problem

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Motivation

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• Emerging IT paradigms– Data centers, grid computing, HPC, multi-core– Cluster-based storage systems, SAN, NAS– Large-scale data management “in the cloud”– Data manipulation via “services-oriented computing”

• Cost and efficiency advantages from IT trends, economy of scale, specialization marketplace

• Performance advantages from parallelism– Partition/aggregation, Hadoop, multi-core, etc.– Think RAID at Internet scale! (1000x)

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Problem Formulation

• High-speed, low-latency network (RTT ≤ 0.1 ms) • Highly-multiplexed link (e.g., 1000 flows)• Highly-synchronized flows on bottleneck link• Limited switch buffer size (e.g., 100 packets)

How to provide high goodputfor data centerapplications?

TCP retransmission timeouts

TCP throughput degradation

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Summary

• Data centers have specific network characteristics

• TCP-incast throughput collapse problem emerges

• Solutions:

– Tweak TCP parameters for this environment

– Redesign TCP for this environment

– Rewrite applications for this environment (Facebook)

– Smart edge coordination for uploads/downloads

Summary: TCP Incast Problem

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Concluding Remarks• We need “smart edge” devices to enhance the

performance, functionality, security, and efficiency of the Internet (now more than ever!)

Application

Transport

Network

Data Link

Physical

Application

Transport

Network

Data Link

PhysicalCoreNetwork

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Future Outlook and Opportunities

• Traffic classification• QoS management• Load balancing• Security and privacy• Cloud computing• Virtualization everywhere• Multipath TCP congestion control• …

the edge of smartness

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