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Some Current Research/Challenges
04/23/2008
Admin.
Multimedia applications and QoS slides are linked on the schedule page
Programming assignment 3 Due on May 5
Office hours during break please send email to Antonis and me for
appointments
Objectives
A brief introduction to some computer networking projects we are working on here at Yale disclaimer: some projects I describe are not
Yale projects
More importantly, focus on perspectives that challenge what we have covered in class
Objectives of Networking Research
Faster More efficient More reliable More ubiquitous Safer
Faster
“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
Rising Bandwidth Demand
“Desperate Housewives” 210MB/hour
for 320x240 H.264 Video iTunes image
assume 10,000,000 households downloads
How long will that take to download? 3 days @ 64Gbps non-stop !
HD video is 7~10 times larger than non-HD video 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
Internet Bandwidth Growth
Source: TeleGeograph Research
What Determines Transmission Rate?
Service: transmit a bit stream from a sender to a receiver
Encodingchannel
Decodingoutput bit stream
input bit stream
sender receiver
Question to be addressed: how much can we send through the channel ?
Basic Theory: Channel Capacity 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.
)1(log2 NSW
Fourier Transform
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, …
A reasonably behaved periodic function g(t), with minimal period T, can be constructed as the sum of a series of sines and cosines:
11
21 )2cos()2sin()(
nn
nn nftbnftactg
dtnfttgb
dtnfttga
dttgc
Tf
T
Tn
T
Tn
T
T
)2cos()(
)2sin()(
)(
/1
0
2
0
2
0
2
nnn barms char “b”
Signal Attenuation
The quality of signal will degrade when it travels loss, frequency passing
)1(log2 NSW
Frequency Dependent Attenuation
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
Example
Example: W=3000Hz, S/N 4000
kbpsbandwidth 36)40001(log3000max 2
telephone networksender modem
ModemModulation
(digit->analog)
3Khz bandwidth(add white noise)
ISPdemodulation
output bit stream
input bit stream
Analog to Digital quantization
for transmitting throughthe digital telephone
backbone
ISP modem
V.34 (33.6kbps Dialup Modem)
channel
Example: ADSL Spectrum allocation:
divided into a total of 256 downstream and 32 upstream tones, where each tone is a standard 4kHz voice channel
During initial negotiation, a tone is used only if the S/N is above 6 db (4)
kbpsup
Mbpsdown
297)41(log4000*32
4.2)41(log4000*256
2
2
The Wire: Fiber
A look at a fiber
How it works?
A graded index fiber
The Wire: Fiber
Wide spectrum at low loss: ~0.3db/km (c.f. copper ~190db/km @100Mhz), 30-100km without repeater bit error rate 10-15
(c.f. copper 10-4-10-8) bandwidth of a single fiber
commercial: 1.6Tbps using 169 channels lab: 10 Tbps theoretical: 100-200Tbps
http://www.trnmag.com/Stories/080101/Study_shows_fiber_has_room_to_grow_080101.html
Lightweight: 33 tons of copper to transmit the same amount of information carried by ¼ pound of optical fiber
Advantages of Fibers
How to Do Switching?
Optical-Electrical-Optical Optical switch: optical micro-electro-mechanical systems
(MEMS)
Optical path One optical switch
http://www.qwest.com/largebusiness/enterprisesolutions/networkMaps/preloader.swf
Example: MEMS Optical Switch Using mirrors, e.g. Lambda Router
Implications
Fine-grained switching may not be feasible
What is the architecture of optical networks: packet switching, circuit switching, or others?
Higher Efficiency
Integrating P2P into Internet Content Distribution
Initially standalone applications rogue technology (e.g., copyright issues)
Recent development becomes part of content delivery
infrastructure integrated P2P + servers solutions some projects
• BBC's iPlayer (tremendously popular), Joost, Pando and NBC, MSN video
• Verizon P2P, Thomson/Telephonica nanoData Center
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
P2P Problem I: Bandwidth Usage
Cache Logic Research: Internet Protocol Breakdown 1993 - 2006
P2P Problem II: Increased Operational Costs
Violating Internet economics (bypass BGP): relay traffic between providers
increased network operational costs
provider
customer
provider
provider tocustomer
An iterative process between two sets of adaptation: ISP: traffic engineering to change
routing to shift traffic away from higher utilized links
• current traffic pattern new routing matrix
P2P: direct traffic to better performing peers
• current routing matrix new traffic pattern
P2P Problem III: Inefficient Interactions
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
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
The Fundamental Problem Traditional Internet architectural feedback
to application efficiency is limited: routing (hidden) rate control through coarse-grained TCP
congestion feedback To achieve better efficiency, needs explicit
communications between network resource providers and applications a network resource provider can be a
traditional ISP (AT&T, Verizon) or a content distribution ISP such as Akamai, or a caching provider
P4P Objective Design a framework to enable better providers and
applications cooperation
ISP perspective: guide applications to achieve more efficient resource usage avoid undesirable (expensive/limited capacity) links to more
desirable (inexpensive/available capacity) links
Resource providers such as caching, CDN providers perspective provide applications with better, on-demand
resources/quality
P2P perspective: better performance for users decrease incentives for ISPs to “manage” applications
P4P Framework – Design Goals
Performance improvement Scalability and extensibility: support
diverse ISP objectives and applications scenarios in large networks
Privacy preservation Ease of implementation Open standard: any ISP, provider,
applications can easily implement it
The P4P Framework
Data plane
control plane iTracker: a portal for each network service
provider iTracker of a provider can be identified in
multiple ways• e.g., through DNS SRV records
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
Control Path Interfaces provider capabilities interface: request QoS,
CoS, servers participation in content distributions
topology interface: topology and connectivity
ISP policy and guideline interface: e.g., traffic balance ratio for inter-AS peering links, time of day preference
…
P4P Control Path : Request Capability
ISP B
1: pTracker [content provider] requests ISP B’s participation in content distribution2: 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 BiTracker
A
b
2
3
1
pTracker/content provider requests ISP capabilities to accelerate content distribution.
The Virtual Topology Interface
An interface to guide peer selection
An interface as an optimization decomposition interface guidance through “virtual costs”
Background: Peer Selection
pTracker
webserveruser
“register”
ID1 169.237.234.1:6881ID2 190.50.34.6:5692ID3 34.275.89.143:4545…ID50 231.456.31.95:6882
list of peers
Peer 40Peer 2 Peer 1
…BitTorrent as an example
HTTP GET MYFILE.torrent
MYFILE.torrent
ISP A
Control Path: Virtual Topology Interface
1 4
3
2pTracker
iTracker
peer
Information flow:1. peer 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
The Virtual Topology Interface: Network
PID: set of Points of Presence (PoP)
E: set of links connecting PoPs
ce: the link capacity of link e
Ie(i, j): indicator if link e is on the route from PoP i to PoP j
be: amount of background traffic on link e
The Virtual Topology Interface: P2P
Assume K applications running inside the ISP we call each running P2P application a swarm
Let Tk be the set of acceptable demands for swarm k tk in Tk specifies traffic demand tk
ij from each pair of source-destination PoPs (i,j)
The Virtual Topology Interface
Consider an example: ISP wants to minimize utilization of the highest utilized link the utilization of the highest utilized link is
called the Maximum Link Utilization (MLU)
k
ek ji
ekije
Ee
Ttts
cjiItb
k :k ..
/)),((maxmin
ISP MLU: Transformation
kk
ek ji
ekije
Ttk
cjiItbets
:
),(:..
min
ISP MLU: Dual
Introducing pe (≥ 0) for the inequality of each link e
To make the dual finite, need
)(min)(:;
ee k
keee
Ttke ctbppD
kk
e
eecp 1
ISP MLU: Dual Then the dual is
where pij is the sum of pe along the path from PoP i to PoP j
)(min)(:
e k
keee
Ttke tbppD
kk
e
kee
e kTt
ee tpbpkk
min
ji
kijij
e kTt
ee tpbpkk
min
e k
kee
eTt
ee tpbpkk
min
ISP MLU Dual : Interpretation
Each swarm k chooses tk in Tk to minimize weighted sum of tij
The interface between a swarm and the ISP is the “shadow prices” {pij}
ji
kijij
e kTt
eee tpbppDkk
min)(
Topology with Costs (Illustration)
PID1 PID2
PID3PID6
PID5 PID4
70
2030
10
60
Each PID has:• IP “prefix”
Each link has•“Price”Prices are directional
ISP Update
At update m+1, calculates
eeee
S
See
pcp
mmmpmp
}0;1:{p :S
Sset toprojection:[]
})D({p ofent supergradi :
size step :
)]()()1([)1(
e
e
P2P Operations
Each swarm optimizes its own performance, then picks ISP-friendly peering
For example, selects
where is tolerance, say 80%.
Example: Multihoming
Multihoming A common way of
connecting to Internet
Smart routing Intelligently distribute
traffic among multiple external links
Improve performance Improve reliability Reduce cost
User
ISP 1
ISP K
InternetISP 2
Interdomain Topo
PID1 PID2
PID3PID6
PID5 PID4
70
2030
10
60
Provider1
Provider 2
Provider 3
Cost?
Cost?
Cost?
Integrating Cost Min with P4P
kk
ek ji
ekijee
ek ji
ekije
Ttk
vjiItbEe
cjiItbEe
ts
:
),(:
),(:
..
min0
Field-Tests
So far integrated with BitTorrent on PlanetLab Pando: a P2P software (18 million downloads) Maze: about 5 million users
Run iTrackers Verizon at Yale Telephonica at its own location
Collect data from Feb. 21 to March 2
ISP Perspective: Overall
Traffic within Verizon
Average Hop Each Bit Traverses
Why less than 1: many transfers are in the same metro-area; also same metro-area peers are utilized more by tit-for-tat.
P2P Perspective: Download Rates
Current Status
P4P-WG Next step
wider integration 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
Higher Reliability
Is the Internet Reliable?
A key design objective of the “Internet” (i.e., packet-switched networks) is robustness
Does the Internet infrastructure achieve the target reliability objective of a highly reliable system (99.999%)?
Perspective
911 Phone service (1993 NRIC report +) 29 minutes per year per line 99.994% availability
Std. Phone service (various sources) 53+ minutes per line per year 99.99+% availability
…what about the Internet? Various studies: about 99.5% Need to reduce down time by 500 times to
achieve five nines; 50 times to match phone service
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
Shadow Configurations as a Network Management Primitive
Shadow Configurations as a Network Management Primitive
Threats to Internet Availability: Accidents
Stockton
Rialto
El Paso
Oroville
- 675,000 excavation accidentsSprint Backbone: Jan. 9, 2006
Reliability as an Interdomain Service
ISPs pool resources to form an “insurance” pool implications?
Resilient routing reconfiguration
Threats to Internet Availability: Natural Disasters
Unreachable Networks: 10 days
Internet Disaster Recovery Response
Why slow response? the cable repairing is slow: not until 21 days
after quake BGP is not designed to create business
relationship
Objective a meta-BGP to facilitate discovery and
creation of BGP business relationship
More Ubiquitous Connectivity
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
Network Access: Ubiquitous Access Goals
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?
handle multiple network interfaces• may operate at the same time
support the application’s graceful adaptation to the available bandwidth and latency
transparent handoff of user sessions among different devices/networks
Example: wireless overlay may take off if we can combine
cellular and WLAN
Motorola CN 620
Access: Build an Access Network Fast: Ad-Hoc Networks
Faster Wireless
Recap: Traditional Routing
So far, all routing protocols in wireless also use the framework of traditional Internet routing we covered in class a graph representation of underlying network
• point-to-point graph edges with costs select a lowest-cost route for a src-dest pair commit to a specific route before forwarding
A Simple Motivating Scenario
Assumes independent loss Internet architecture computes routing with one pre-
committed route
Implications?
How about Using Multiple Paths?
Traditional Routing3 forwarders
4 links
Opportunistic:7 forwarders
18 links
Opportunistic Coding
Motivating Scenario
A sends 1 packet to B; B sends packet 3 to A
If R has both packets 1 and 3, it can combine them and explore coding and broadcast nature of wireless
A BR
Faster Wireless: Summary
Both approaches dispose the point-to-point Internet link abstraction
Both approaches take advantage of opportunities and leverage broadcast nature of wireless medium to its advantage
New Access: Connecting the Physical World
Mark Weiser from Xerox: transparent computing is the ultimate goal computers should disappear into the
background
Network Access: Sensors
N
S
EW 2 Axis Magnetic Sensor
2 Axis Accelerometer
Light Intensity Sensor
Humidity Sensor
Pressure Sensor
Temperature Sensor
COTS sensors embedded microprocessor RF transceiver
• 916MHz, ~20m range, 4800 bps 1 week fully active, 2 yr @1% recharge by solar, wind, …
Course Summary
The field is moving fast, broad and not well-defined !
Driven by Technology, Infrastructure, Applications, and Understanding: technology
• e.g., wireless/optical communication technologies and device miniaturization (sensors)
infrastructure• e.g., global infrastructure
applications• e.g., P2P, content distribution, sensing, grid computing, VoIP,
IPTV understanding
• e.g., resource sharing principle, routing principles, mechanism design, and randomized access