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Link Layer: MAC and Summary
11/30/2009
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Admin.
Exam 2 Covers network and link layers Format similar to exam 1; see samples of
exam 2 from past offerings
2
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Recap: Link Layer Services Framing
o encapsulate datagram into frame, adding header, trailer and error detection/correction (e.g., CRC)
Multiplexing/demultiplexingo frame headers to identify src, dest
• different from IP address (ARP) ! Flow control Link media access control (MAC) Reliable delivery between adjacent nodes
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Recap: MAC Protocols
Goals efficient, fair, decentralized, simple
Three broad classes: channel partitioning
divide channel into smaller “pieces” (time slot, frequency, code)
Non-partitioning random access
• allow collisions “taking-turns”
• a token coordinates shared access to avoid collisions
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Recap: Channel Partitioning
TDMA: Time Division Multiple AccessFDMA: Frequency Division Multiple
AccessCDMA: Code Division Multiple Access
Used mostly in wireless broadcast channels (cellular, satellite, etc)
Unique “code” assigned to each user; i.e., code set partitioning
All users share same frequency, but each user m has its own “chipping” sequence (i.e., code) cm to encode data
• e.g. cm = 1 1 1 -1 1 -1 -1 -1
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Recap: CDMA
Each user uses its own code cm
Assume original data are represented by 1 and -1 Encoded signal = (original data) modulated by
(chipping sequence) assume cm = 1 1 1 -1 1 -1 -1 -1
if data is d, send d cm,
• if data d is 1, send cm
• if data d is -1 send -cm
Decoding: inner-product (summation of bit-by-bit product) of encoded signal and chipping sequence if inner-product > 0, the data is 1; else -1
If codes are orthogonal, multiple users can “coexist” and transmit simultaneously with minimal interference
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Recap: Channel Partitioning
Two codes Ci and Cj are orthogonal, if , where we use “.” to denote inner
product, e.g.
If codes are orthogonal, multiple users can “coexist” and transmit simultaneously with minimal interference
0 ij cc
C1: 1 1 1 -1 1 -1 -1 -1 C2: 1 -1 1 1 1 -1 1 1-----------------------------------------C1 . C2 = 1 +(-1) + 1 + (-1) +1 + 1+ (-1)+(-1)=0
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Outline
Recap Non-partitioning MAC protocols
Random access Taking turns (we will not cover in class)
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Random Access Protocols
When a node has packets to send transmit at full channel data rate R no a priori coordination among nodes
Two or more transmitting nodes -> “collision”
Random access MAC protocol specifies: how to detect collisions how to recover from collisions
Examples of random access MAC protocols: slotted ALOHA and pure ALOHA CSMA and CSMA/CD, CSMA/CA
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Slotted Aloha [Norm Abramson]
Time is divided into equal size slots (= pkt trans. time)
Node with new arriving pkt: transmit at beginning of next slot
If collision: retransmit pkt in future slots with probability p, until successful.
Success (S), Collision (C), Empty (E) slots
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Slotted Aloha EfficiencyQ: What is the fraction of successful
slots?suppose n stations have packets to sendsuppose each transmits in a slot with probability
p
- prob. of succ. by a specific node: p (1-p)(n-1)
- prob. of succ. by any one of the N nodes
S(p) = n * Prob (only one transmits) = n p (1-p)(n-1)
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Goodput vs. Offered LoadS =
thro
ughput
=
“goodput”
(
succ
ess
rate
)
G = offered load = np0.5 1.0 1.5 2.0
Slotted Aloha
when p n < 1, as p (or n) increases probability of empty slots reduces probability of collision is still low, thus goodput increases
when p n > 1, as p (or n) increases, probability of empty slots does not reduce much, but probability of collision increases, thus goodput decreases
goodput is optimal when p n = 1
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Maximum Efficiency vs. n
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
2 7 12 17 n
ma
xim
um
eff
icie
nc
y1/e = 0.37
At best: channeluse for useful transmissions 37%of time!
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Pure (unslotted) Aloha Unslotted Aloha: simpler, no clock
synchronization Whenever pkt needs transmission:
send without awaiting for the beginning of slot
Collision probability increases: pkt sent at t0 collide with other pkts sent in [t0-1,
t0+1]
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Pure Aloha (cont.)Assume a node transmit with probability p in one unit of time
P(success by a given node) = P(node transmits) * P(no other node transmits in [t0-1,t0]
* P(no other node transmits in [t0,
t0+1]
= p . (1-p)n-1 . (1-p)n-1
= p . (1-p)2(n-1)
P(success by any of N nodes) = n p . (1-p)2(n-1)
- Bound: 1/(2e) = .18
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Goodput vs. Offered LoadS =
thro
ughput
=
“goodput”
(
succ
ess
rate
)
G = offered load = Np0.5 1.0 1.5 2.0
0.1
0.2
0.3
0.4
Pure Aloha
protocol constrainseffective channelthroughput!
Slotted Aloha
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Dynamics of (Slotted) Aloha
In reality, the number of stations backlogged is changing we need to study the dynamics when using a
fixed transmission probability p
Assume we have a total of m stations (the machines on a LAN): n of them are currently backlogged, each tries
with a (fixed) probability p the remaining m-n stations are not backlogged.
They may start to generate packets with a probability pa, where pa is much smaller than p
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Modeln backlogged
each transmits with prob. p
m-n: unbacklogged
each transmits with prob. pa
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Dynamics of Aloha: Effects of Fixed Probability
n: number of backlogged stations
0 m
successful transmission rate at
offered load np + (m-n)pa
new arrival rate:(m-n) pa
desirable stable point
undesirable stable point
Lesson: if we fix p, but n varies, we may have an undesirable stable point
offered load = 1
- assume a total ofm stations- pa << p- success rate is thedeparture rate, the rate the backlog is reducing
dep.andarrivalrateofbackloggedstations
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Summary of Problems of Aloha Protocols Problems
slotted Aloha has better efficiency than pure Aloha but clock synchronization is hard to achieve
Aloha protocols have low efficiency due to waste of collision or empty slots
• when offered load is optimal (p = 1/N), the goodput is about 37%
• when the offered load is not optimal, the goodput is even lower
undesirable steady state at a fixed transmission rate, when the number of backlogged stations varies
Thus problems to be addressed: approximate slotted Aloha without clock
synchronization reduce the penalty of collision or empty slots infer optimal transmission rate
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CSMA: Carrier Sense Multiple Access
CSMA: listen before transmitObjective: approximate slotted Aloha (compared
with pure Aloha)
If backlogged, wait until channel sensed idle, then transmit pkt with prob. p
human analogy: don’t interrupt others !
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CSMA Collisions
collisions can still occur:propagation delay means two nodes may nothear each other’s transmission
Collision:entire packet transmission time wasted; still not veryefficient!
spatial layout of nodes along EthernetA B C D
tim
e
t0
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CSMA/CD (Collision Detection) Human analogy: the polite conversationalist
CSMA/CD: observations:
• collisions can be detected within short time• if colliding transmissions are aborted, we can reduce
channel wastage carrier sensing, deferral as in CSMA collision detection:
• easy in wired LANs: measure signal strengths, compare transmitted, received signals
• difficult in wireless LANs: receiver shuts off while transmitting
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spatial layout of nodes along EthernetA B C D
tim
e
t0
spatial layout of nodes along EthernetA B C D
tim
e
t0
B detectscollision, aborts
D detectscollision,aborts
CSMA/CD: Collision Detection
instead of wasting the whole packettransmission time, abort after detection.
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Efficiency of CSMA/CD Given collision detection, instead of wasting the
whole packet transmission time (a slot), we waste only the time needed to detect collision.
Use a contention slot of 2 T, where T is one-way propagation delay (why 2 T ?)
When the transmission probability p is approximately optimal (p = 1/N), we try approximately e times before each successful transmission
P/C
P: packet size, e.g. 1000 bitsC: link capacity, e.g. 10Mbps
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Efficiency of CSMA/CD The efficiency (the percentage of useful time) is
approximately
The value of a plays a fundamental role in the efficiency of CSMA/CD protocols.
Question: you want to increase the capacity of a link layer technology (e.g., , 10 Mbps Ethernet to 100 Mbps), but still want to maintain the same efficiency, what can you do?
PTC
aTea
CPT
CP
CP
where,511
11
2 5
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Summary of Problems to be Addressed
Approximate slotted Aloha
Reduce the penalty of collision or empty slots
Infer optimal transmission rate
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The Basic MAC Mechanisms of Ethernet
get a packet from upper layer;K := 0; n := 0; // K: control wait time; n: no. of
collisionsrepeat: wait for K * 512 bit-time; while (network busy) wait; wait for 96 bit-time after detecting no signal; transmit and detect collision; if detect collision stop and transmit a 48-bit jam signal; n ++; m:= min(n, 10), where n is the number of
collisions choose K randomly from {0, 1, 2, …, 2m-1}. if n < 16 goto repeat else give up
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Ethernet’s Exponential Backoff:
Goal: adapt retransmission attempts to estimated current load compared with CSMA, 1/2m can be considered
as p not a static p---adjusted using exponential
backoff• first collision: choose K from {0,1}; delay is K x 512
bit transmission times• after second collision: choose K from {0,1,2,3}…• after ten or more collisions, choose K from {0,1,2,3,4,
…,1023}
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Ethernet
“Dominant” LAN technology: First widely used LAN
technology Kept up with speed race: 10 Mbps, 100 Mbps,
1 Gbps, 10 Gbps
Metcalfe’s Ethernetsketch
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Ethernet Frame Structure
Sending adapter encapsulates IP datagram (or other network layer protocol packet) in Ethernet frame
Preamble: 8 bytes 7 bytes with pattern 10101010 followed by one byte with
pattern 10101011 (why the preamble?) Source and dest. addresses: 6 bytes Type: indicates the higher layer protocol, mostly IP but
others may be supported such as Novell IPX and AppleTalk
CRC: CRC-32 checked at receiver, if error is detected, the frame is simply dropped
8 6 6 2 46-1500 (including padding) 4
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Physical Layer
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Internet Bandwidth Growth
Source: TeleGeograph Research
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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 ?
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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
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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
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nnn barms char “b”
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Signal Attenuation
The quality of signal will degrade when it travels loss, frequency passing
)1(log2 NSW
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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 (= 20 log 1/0.32)
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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
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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
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Course Summary
The Internet is a general-purpose, large-scale, distributed computer network
Major design features packet switching for simplicity and efficiency hour-glass architecture end-to-end principle distributed system considering social/economical structures
resource allocation principle and framework (e.g., optimization framework and AIMD)
stable, adaptive control (e.g., sliding window self clocking, CSMA/CD/Expo)
hierarchical, distributed routing
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Evolution Driven by Technology, Infrastructure, Policy,
Applications, and Understanding: technology
• e.g., wireless/optical communication technologies and device miniaturization (sensors)
infrastructure• e.g., cloud computing
applications• e.g., content distribution, game, tele presence, sensing, grid
computing, VoIP, IPTV understanding
• e.g., resource sharing principle, routing principles, mechanism design, and optimal stochastic control (randomized access)
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Many Issues
How to make it faster
How to make it more efficient
How to make it more reliable/robust/secure
44
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Faster
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The Wire: Fiber
A look at a fiber
How it works?
A graded index fiber
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The Wire: Fiber
Wide spectrum at low loss: ~0.3db/km (c.f. copper ~190db/km @100Mhz), 30-100km without repeater
Bandwidth of a single fiber 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
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Advantages of Fibers
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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
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Example: MEMS Optical Switch Using mirrors, e.g. Lambda Router
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Implications
Fine-grained switching may not be feasible
What is the architecture of optical networks: packet switching, circuit switching, or others?
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More Efficient
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Large deployment of highly adaptive, multipoint applications
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
App: direct traffic to better performing end points
• current routing matrix new traffic pattern
Problem: Inefficient Interactions
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ISP optimizer interacts poorly with App.
ISP Traffic Engineering+ App Latency Optimizer
- red: App adjust alone; fixed ISP routing- blue: ISP traffic engineering adapt alone; fixed App communications
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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
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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
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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
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Reliability
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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%)?
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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
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Unreachable Networks: 10 days
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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
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Backup Slides
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The P4P Framework
Data plane
control plane P4P server: a portal for each network service
provider A P4P server provides multiple interfaces so
that others can interact• each provider decides the interfaces it provides
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The Virtual Topology Interface
An interface to guide peer selection
An interface as an optimization decomposition interface guidance through “virtual costs”
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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
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The Virtual Topology Interface: App
Assume K applications running inside the ISP
Let Tk be the set of acceptable demands for app k tk in Tk specifies traffic demand tk
ij from each pair of source-destination PoPs (i,j)
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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)
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ISP MLU: Transformation
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ISP MLU: Dual
Introducing pe (≥ 0) for the inequality of each link e
To make the dual finite, need
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ISP MLU: Dual Then the dual is
where pij is the sum of pe along the path from PoP i to PoP j
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ISP MLU Dual : Interpretation
Each App k chooses tk in Tk to minimize weighted sum of tij
The interface between an App and the ISP is the “shadow prices” {pij}
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Topology with Costs (Illustration)
PID1 PID2
PID3PID6
PID5 PID4
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Each PID has:• IP “prefix”
Each link has•“Price”Prices are directional
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ISP Update
At update m+1, calculates
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App Operations
Each app. optimizes its own performance, then picks ISP-friendly peering
For example, selects
where is tolerance, say 80%.
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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
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Interdomain Topo
PID1 PID2
PID3PID6
PID5 PID4
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Provider1
Provider 2
Provider 3
Cost?
Cost?
Cost?
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Integrating Cost Min with P4P
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Field Test: Traffic within Verizon
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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.
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App Perspective: App Rates