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The Edge of Smartness

The Edge of Smartness

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The Edge of Smartness

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  1. The Edge of Smartness Carey Williamson Department of Computer Science University of Calgary Email: carey@cpsc.ucalgary.ca 1 1

  2. Main Message Application Transport Network Data Link Physical Application Transport Network Data Link Physical Core Network 2 2 Now, more than ever, we need “smart edge” devices to enhance the performance, functionality, and efficiency of the Internet

  3. The End-to-End Principle 3 3 • 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

  4. The End-to-End Principle: Revisited 4 4 • 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!

  5. (Selected) Existing Examples 5 5 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

  6. The Smart Edge 6 6 • 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

  7. Example 1:Redundant Traffic Elimination 7 7

  8. 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) 8

  9. Redundant Traffic Elimination (RTE) 9 9 • 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

  10. RTE Process Pipeline • 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 10 10

  11. Main Sources of Redundancy 11 11

  12. RTE Summary 12 12 • 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

  13. Example 2:The TCP Incast Problem 13 13

  14. Motivation 14 14 • 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)

  15. Problem Formulation TCP retransmission timeouts • 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 goodput for data center applications? TCP throughput degradation 15

  16. Summary Summary: TCP Incast Problem • 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 16

  17. Concluding Remarks Application Transport Network Data Link Physical Application Transport Network Data Link Physical Core Network 17 17 We need “smart edge” devices to enhance the performance, functionality, security, and efficiency of the Internet (now more than ever!)

  18. Future Outlook and Opportunities 18 18 Traffic classification QoS management Load balancing Security and privacy Cloud computing Virtualization everywhere Multipath TCP congestion control …