1. Some Current Research/Challenges 04/23/2008

2. Admin. r Multimedia applications and QoS slides are linked on the schedule page r Programming assignment 3 m Due on May 5 r Office hours during break m please send email to Antonis and me for appointments

3. Objectives r A brief introduction to some computer networking projects we are working on here at Yale m disclaimer: some projects I describe are not Yale projects r More importantly, focus on perspectives that challenge what we have covered in class

4. Objectives of Networking Research r Faster r More efficient r More reliable r More ubiquitous r Safer

5. Faster

6. “ Within five years, all media will be delivered across the Internet.” - Steve Ballmer, CEO Microsoft, D5 Conference, June 2007 The Internet is increasingly being used for content and media delivery Rising Content Distribution Demand Some speculation

7. Rising Bandwidth Demand r “Desperate Housewives” m 210MB/hour for 320x240 H.264 Video iTunes image m assume 10,000,000 households downloads r How long will that take to download? m 3 days @ 64Gbps non-stop ! r HD video is 7~10 times larger than non-HD video r AT&T predicts 50-fold increase in broadband to 2015 (75% per year) http://www.pbs.org/cringely/pulpit/pulpit20060302.html http://dynamic.abc.go.com/streaming/landing?lid=ABCCOMGlobalMenu&lpos=FEP

8. Internet Bandwidth Growth Source: TeleGeograph Research

9. What Determines Transmission Rate? r Service: transmit a bit stream from a sender to a receiver Encoding channel Decoding output bit stream input bit stream sender receiver Question to be addressed: how much can we send through the channel ?

10. Basic Theory: Channel Capacity r The maximum number of bits that can be transmitted per second (bps) by a physical media is: where W is the frequency range, S/N is the signal noise ratio. We assume Gaussian noise.

11. Fourier Transform r Suppose the period of a data unit is f (=1/T), then the data unit can be represented as the sum of many harmonics (sin(), cos()) with frequencies f, 2f, 3f, 4f, … r A reasonably behaved periodic function g(t), with minimal period T, can be constructed as the sum of a series of sines and cosines:

12. char “b”

13. Signal Attenuation r The quality of signal will degrade when it travels m loss, frequency passing

14. Frequency Dependent Attenuation r The received signal will be distorted even when there is no interference and the transmitted signal is “perfect” square waveform Example: Voltage- attenuation magnitude ratios of Category 5 cable. For example, 500 feet of cable attenuates a 10-MHz, 1-V signal to 0.32 V, which corresponds to about –9.90 dB

15. Example Example: W=3000Hz, S/N  4000 telephone network sender modem Modem Modulation (digit->analog) 3Khz bandwidth (add white noise) ISP demodulation output bit stream input bit stream Analog to Digital quantization for transmitting through the digital telephone backbone ISP modem V.34 (33.6kbps Dialup Modem) channel

16. Example: ADSL r Spectrum allocation: divided into a total of 256 downstream and 32 upstream tones, where each tone is a standard 4kHz voice channel r During initial negotiation, a tone is used only if the S/N is above 6 db (  4)

17. The Wire: Fiber r A look at a fiber r How it works? A graded index fiber

18. The Wire: Fiber r Wide spectrum at low loss: ~0.3db/km (c.f. copper ~190db/km @100Mhz), 30-100km without repeater m bit error rate 10 -15 (c.f. copper 10 -4 -10 -8 ) r bandwidth of a single fiber m commercial: 1.6Tbps using 169 channels m lab: 10 Tbps m theoretical: 100-200Tbps http://www.trnmag.com/Stories/080101/Study_shows_fiber_has_room_to_ grow_080101.html r Lightweight: 33 tons of copper to transmit the same amount of information carried by ¼ pound of optical fiber

19. Advantages of Fibers

20. How to Do Switching? r Optical-Electrical-Optical r Optical switch: optical micro-electro-mechanical systems (MEMS) Optical path One optical switch http://www.qwest.com/largebusiness/enterprisesolutions/networkMaps/preloader.swf

21. Example: MEMS Optical Switch r Using mirrors, e.g. Lambda Router

22. Implications  Fine-grained switching may not be feasible  What is the architecture of optical networks: packet switching, circuit switching, or others?

23. Higher Efficiency

24. Integrating P2P into Internet Content Distribution r Initially m standalone applications m rogue technology (e.g., copyright issues) r Recent development m becomes part of content delivery infrastructure m integrated P2P + servers solutions m some projects BBC's iPlayer (tremendously popular), Joost, Pando and NBC, MSN video Verizon P2P, Thomson/Telephonica nanoData Center

25. Edge Network Regional Routers Internet Transit Traditional content distribution P2P, e.g., BT More Viewers = Worse performance Higher cost P2P Efficiency - Network oblivious peering -> scattered traffic - Higher financial cost - Inefficiency

26. P2P Problem I: Bandwidth Usage Cache Logic Research: Internet Protocol Breakdown 1993 - 2006

27. P2P Problem II: Increased Operational Costs Violating Internet economics (bypass BGP): relay traffic between providers m increased network operational costs provider customer provider provider to customer

28. r An iterative process between two sets of adaptation: m ISP: traffic engineering to change routing to shift traffic away from higher utilized links current traffic pattern  new routing matrix m P2P: direct traffic to better performing peers current routing matrix  new traffic pattern P2P Problem III: Inefficient Interactions

29. ISP optimizer interacts poorly with P2P. ISP Traffic Engineering+ P2P Latency Optimizer -red: P2P adjust alone; fixed ISP routing -blue: ISP traffic engineering adapt alone; fixed P2P communications

30. P2P Countermeasures use random ports encrypt traffic... Attempts to Address P2P Efficiency Problems ISPs Address P2P upgrade network infrastructure deploy P2P caching devices terminate user connectivity rate-limit P2P traffic... Network neutrality argument

31. The Fundamental Problem r Traditional Internet architectural feedback to application efficiency is limited: m routing (hidden) m rate control through coarse-grained TCP congestion feedback r To achieve better efficiency, needs explicit communications between network resource providers and applications m a network resource provider can be a traditional ISP (AT&T, Verizon) or a content distribution ISP such as Akamai, or a caching provider

32. P4P Objective r Design a framework to enable better providers and applications cooperation r ISP perspective: m guide applications to achieve more efficient resource usage m avoid undesirable (expensive/limited capacity) links to more desirable (inexpensive/available capacity) links r Resource providers such as caching, CDN providers perspective m provide applications with better, on-demand resources/quality r P2P perspective: m better performance for users m decrease incentives for ISPs to “manage” applications

33. P4P Framework – Design Goals r Performance improvement r Scalability and extensibility: support diverse ISP objectives and applications scenarios in large networks r Privacy preservation r Ease of implementation r Open standard: any ISP, provider, applications can easily implement it

34. The P4P Framework r Data plane r control plane m iTracker: a portal for each network service provider m iTracker of a provider can be identified in multiple ways e.g., through DNS SRV records m An iTracker provides multiple interfaces so that others can interact each provider decides the interfaces it provides each interface is encoded in Web Service Definition Language (WSDL) for extensibility

35. Control Path Interfaces r provider capabilities interface: request QoS, CoS, servers participation in content distributions r topology interface: topology and connectivity  ISP policy and guideline interface: e.g., traffic balance ratio for inter-AS peering links, time of day preference r …

36. P4P Control Path : Request Capability ISP B 1: pTracker [content provider] requests ISP B’s participation in content distribution 2: Provider B allocates servers to accelerate content distribution 3: pTracker includes ISP B’s servers in returned peering sets to peers ISP A pTracker a iTracker B iTracker A b 2 3 1 pTracker/content provider requests ISP capabilities to accelerate content distribution.

37. The Virtual Topology Interface r An interface to guide peer selection r An interface as an optimization decomposition interface m guidance through “virtual costs”

38. Background: Peer Selection pTracker webserver user “register” ID1 169.237.234.1:6881 ID2 190.50.34.6:5692 ID3 34.275.89.143:4545 … ID50 231.456.31.95:6882 list of peers Peer 40 Peer 2 Peer 1 … BitTorrent as an example HTTP GET MYFILE.torrent MYFILE.torrent

39. ISP A Control Path: Virtual Topology Interface 1 4 3 2 pTracker iTracker peer Information flow: 1. pe er queries pTracker 2. pTracker asks iTracker for guidance (occasionally) 3. iTracker returns high-level peering suggestions 4. pTracker selects and returns a set of active peers, according to the suggestions iTracker can be run by trusted third parties, P2P network, or ISPs for security/privacy

40. The Virtual Topology Interface: Network r PID: set of Points of Presence (PoP) r E: set of links connecting PoPs r c e : the link capacity of link e r I e (i, j): indicator if link e is on the route from PoP i to PoP j r b e : amount of background traffic on link e

41. The Virtual Topology Interface: P2P r Assume K applications running inside the ISP m we call each running P2P application a swarm r Let T k be the set of acceptable demands for swarm k m t k in T k specifies traffic demand t k ij from each pair of source-destination PoPs (i,j)

42. The Virtual Topology Interface r Consider an example: ISP wants to minimize utilization of the highest utilized link m the utilization of the highest utilized link is called the Maximum Link Utilization (MLU)

43. ISP MLU: Transformation

44. ISP MLU: Dual r Introducing p e (≥ 0) for the inequality of each link e r To make the dual finite, need

45. ISP MLU: Dual r Then the dual is where p ij is the sum of p e along the path from PoP i to PoP j

46. ISP MLU Dual : Interpretation r Each swarm k chooses t k in T k to minimize weighted sum of t ij r The interface between a swarm and the ISP is the “shadow prices” {p ij }

47. Topology with Costs (Illustration) PID1PID2 PID3PID6 PID5PID4 70 20 30 10 60 Each PID has: IP “prefix” Each link has “Price” Prices are directional

48. ISP Update r At update m+1, calculates

49. P2P Operations r Each swarm optimizes its own performance, then picks ISP-friendly peering r For example, selects where  is tolerance, say 80%.

50. Example: Multihoming Multihoming m A common way of connecting to Internet Smart routing m Intelligently distribute traffic among multiple external links m Improve performance m Improve reliability  Reduce cost User ISP 1 ISP K Internet ISP 2

51. Interdomain Topo PID1PID2 PID3PID6 PID5PID4 70 20 30 10 60 Provider1 Provider 2 Provider 3 Cost?

52. Integrating Cost Min with P4P

53. Field-Tests r So far integrated with m BitTorrent on PlanetLab m Pando: a P2P software (18 million downloads) m Maze: about 5 million users r Run iTrackers  Verizon at Yale m Telephonica at its own location r Collect data from Feb. 21 to March 2

54. ISP Perspective: Overall

55. Traffic within Verizon

56. Average Hop Each Bit Traverses r Why less than 1: many transfers are in the same metro-area; also same metro-area peers are utilized more by tit-for-tat.

57. P2P Perspective: Download Rates

58. Current Status r P4P-WG r Next step m wider integration m IETF standard AT&T Bezeq Intl BitTorrent CacheLogic Cisco Systems Grid Networks Joost LimeWire Manatt Oversi Pando Networks PeerApp Telefonica Group VeriSign Verizon Vuze Univ of Washington Yale University Abacast AHT Intl Akamai Alcatel Lucent CableLabs Cablevision Comcast Cox Comm Juniper Networks Microsoft MPAA NBC Universal Nokia RawFlow Solid State Networks Thomson Time Warner Cable Turner Broadcasting

59. Higher Reliability

60. Is the Internet Reliable? r A key design objective of the “Internet” (i.e., packet-switched networks) is robustness r Does the Internet infrastructure achieve the target reliability objective of a highly reliable system (99.999%)?

61. Perspective r 911 Phone service (1993 NRIC report +) m 29 minutes per year per line m 99.994% availability r Std. Phone service (various sources) m 53+ minutes per line per year m 99.99+% availability r …what about the Internet? m Various studies: about 99.5% m Need to reduce down time by 500 times to achieve five nines; 50 times to match phone service

62. Threats to Internet Availability: Operator Errors - 80% IT budget spent on maintaining status quo - human configuration errors account for about 60% of all network outages. Zeus Kerravala, Yankee Group

63. Shadow Configurations as a Network Management Primitive

65. Threats to Internet Availability: Accidents Stockton Rialto El Paso Oroville - 675,000 excavation accidents Sprint Backbone: Jan. 9, 2006

66. Reliability as an Interdomain Service r ISPs pool resources to form an “insurance” pool m implications? r Resilient routing reconfiguration

67. Threats to Internet Availability: Natural Disasters

68. Unreachable Networks: 10 days

69. Internet Disaster Recovery Response r Why slow response? m the cable repairing is slow: not until 21 days after quake m BGP is not designed to create business relationship r Objective m a meta-BGP to facilitate discovery and creation of BGP business relationship

70. More Ubiquitous Connectivity

71. Goal of Network Access “People and their machines should be able to access information and communicate with each other easily and securely, in any medium or combination of media – voice, data, image, video, or multimedia – any time, anywhere, in a timely, cost-effective way.” Dr. G. H. Heilmeier, Oct 1992

72. Network Access: Ubiquitous Access r Goals m be connected whenever possible via the “best” available network ubiquitous location-aware, e.g. –what services (e.g., printers) are available “here”? –where is the “nearest” database/cache? –where is the “nearest” ATM? m handle multiple network interfaces may operate at the same time m support the application’s graceful adaptation to the available bandwidth and latency m transparent handoff of user sessions among different devices/networks r Example: wireless overlay m may take off if we can combine cellular and WLAN Motorola CN 620

73. Access: Build an Access Network Fast: Ad-Hoc Networks

74. Faster Wireless

75. Recap: Traditional Routing r So far, all routing protocols in wireless also use the framework of traditional Internet routing we covered in class m a graph representation of underlying network point-to-point graph edges with costs m select a lowest-cost route for a src-dest pair m commit to a specific route before forwarding

76. A Simple Motivating Scenario r Assumes independent loss r Internet architecture computes routing with one pre- committed route

77. Implications?

78. How about Using Multiple Paths? Traditional Routing 3 forwarders 4 links Opportunistic: 7 forwarders 18 links

79. Opportunistic Coding

80. Motivating Scenario r A sends 1 packet to B; B sends packet 3 to A r If R has both packets 1 and 3, it can combine them and explore coding and broadcast nature of wireless ABR

81. Faster Wireless: Summary r Both approaches dispose the point-to-point Internet link abstraction r Both approaches take advantage of opportunities and leverage broadcast nature of wireless medium to its advantage

82. New Access: Connecting the Physical World r Mark Weiser from Xerox: transparent computing is the ultimate goal m computers should disappear into the background

83. Network Access: Sensors N S EW 2 Axis Magnetic Sensor 2 Axis Accelerometer Light Intensity Sensor Humidity Sensor Pressure Sensor Temperature Sensor r COTS sensors m embedded microprocessor m RF transceiver 916MHz, ~20m range, 4800 bps m 1 week fully active, 2 yr @1% m recharge by solar, wind, …

84. Course Summary r The field is moving fast, broad and not well-defined ! r Driven by Technology, Infrastructure, Applications, and Understanding: m technology e.g., wireless/optical communication technologies and device miniaturization (sensors) m infrastructure e.g., global infrastructure m applications e.g., P2P, content distribution, sensing, grid computing, VoIP, IPTV m understanding e.g., resource sharing principle, routing principles, mechanism design, and randomized access