The Future of Wireless: Reaching the Unreachable and Adapti - PowerPoint Presentation

Slide1

The Future of Wireless: Reaching the Unreachable and Adaptive Wireless Networks

Henning Schulzrinne(with Arezu Moghadam, Suman Srinivasan, Jae Woo Lee and others)Columbia University

WINLAB 20th - December 2009Slide2

Challenges for years 20...39

Changing usage: H2H  M2MMore than just first-mile accessUser-focused designInterconnecting mobile serviceCovering the white spotsWINLAB 20th - December 2009Slide3

Wireless networks now

WINLAB 20th - December 2009Slide4

Emerging wireless applications

WINLAB 20th - December 2009Slide5

Changing usage

WINLAB 20th - December 2009

voice

web

M2MSlide6

More than just Internet Classic

Networkwirelessmobilitypath stabilitydata

units

Internet “classic”

last hop

end systems

>

hours

IP

datagrams

mesh networks

all links

end systems

> hours

mobile ad-hoc

all links

all nodes, random

minutes

opportunistic

typical

single node

≈

minute

delay-tolerant

all links

some

predictable

some

predictable

bundles

store-carry-forward

all nodes

all nodes

no

path

application data unitsSlide7

Reaching the unreachable

WINLAB 20th - December 2009Slide8

White spaces (real world)

WINLAB 20th - December 2009

$60 for 5 GB



$12/GBSlide9

Internet

?

?

D

Contacts

are

opportunistic

intermittent

802.11 ad-hoc mode

BlueToothSlide10

Web Delivery Model

7DS core functionality: Emulation of web content access and e-mail deliverySlide11

Search Engine

Provides ability to query locally for resultsSearches the cache index using Swish-e libraryStores query for future contactsSlide12

Email exchangeSlide13

BonAHA framework

Node 2Node 1

key21 = value21

key22 = value22

key23 = value23

key24 = value24

key11 = value11

key12 = value12

key13 = value13

key14 = value14

[2] node1.get(key13)

[1] node1.register()

[3] data =

node1.fileGet(

value13);

BonAHA

[CCNC 2009]Slide14

Generic service model?

Opportunistic Network Framework – get(), set(), put(), rm()

ZigBee

BlueTooth

mDNS/

DNS-SD

DHTs?

Gnutella?

ApplicationSlide15

Bulletin Board System

Written in Objective-C, for iPod TouchSlide16

Local MicrobloggingSlide17

Problem – lack of group

communication model for mobile DiTNs?Any cast communication modelEmergencies Traffic congestion notifications Severe weather alerts Traditional multicast as a group communication model



Fails!

No knowledge of the topology

No infrastructure to track group memberships

Communication

with communities of

interest



Even a harder problem!

Market news, sport events

Scientific articles

Advertisement about particular

products

Epidemic routingSlide18

Interest-aware Communication

Jazz

Jazz

Jazz

Rock

Rock

Communication with communities of interest

Interest-aware

m

usic

s

haring

a

pplicationSlide19

UI of Interest-Aware Music and News Sharing Application for 7DSSlide20

Problem 1 of interest-aware: Greedy!

SX

Y

Y

D

1

1

1

3

3

3

3

wireless contact

data transfer

Y

a

b

c

d

e

f

g

2

D

4

4

D

D

X

X

X

Y

h

5

DSlide21

Energy issues

Interest-aware algorithms transmit until end of contact Battery life remains a problem for mobile devices!

Source: TIAX, portable power conferenceSlide22

Solution – PEEP

Still interest-awareInterest vectors; binaryLearning interests: feedback from user, # data items of each category, play times for music files, or LSATransmit-budgetAmount of data items allowed for transmission at each connectionHow to divide the transmit budget? PopularityShould be estimated

1

2

Items of interest?

Others?

1

0

0

1

1

1

0Slide23

Criteria to assign budget?

Only interest-awareMight waste budgetInterest-aware + randomly selectedInterest-aware + popularity estimationIdeal case: we know the global popularityBudget designation (e.g., 50%)

1

2

Items of interest

1

2

Items of interest

random

1

2

Items of interest

popular

1

2

interests

popularSlide24

Popularity estimation

Contact window NHistory of the users’ interestsAverage or weighted averageExample: C=6, N=8Replace the oldest

1

0

1

0

0

1

1

0

0

1

1

1

0

1

0

0

0

0

1

0

0

1

0

0

0

0

1

0

0

0

0

1

0

0

0

0

1

1

0

0

0

0

1

0

1

0

0

0

.62

.37

.37

.25

.12

.25Slide25

Evaluation of PEEPSlide26

Adaptive networks

WINLAB 20th - December 2009Slide27

Spectrum management

WINLAB 20th - December 2009What happens at field level makes the spectrum even tighter. "Stop and consider," said Mendelsohn, "that each coach on the field has a beltpack with four frequencies per pack, with about 10 coaches per team. Then the quarterbacks have two per pack. That's 42 frequencies for each team right there; so with two teams, that's about

84

frequencies." But that's hardly all. "Then add another 15 frequencies for the referees, the chain gang and security frequencies. That's

99

— before counting the TV broadcasters, which require

40

frequencies each, minimum," he said. "Then there are another

15

for home and away radio, and

20

more for various broadcasters doing stand-ups before and after the game. "And what most people forget about is,"

Mendelsohn

said, "that all of this RF is basically contained within and around just 100 yards."

http://www.tvtechnology.com/article/90772

Steve

Mendelsohn

, game day frequency coordinator for the NFL. Slide28

Spectrum

WINLAB 20th - December 2009http://

www.ntia.doc.gov/osmhome/allochrt.pdfSlide29

But often lightly used

29http://www.sharedspectrum.com/measurements/

NYC, August 2004Slide30

Cognitive radio is insufficient

Solution: Cognitive radio!  ?Doesn’t help with dense applicationslong time scales (hours  days)(geographic database solution seems most likely)each frequency still inefficiently used

automated sharing on shorter time scales

WINLAB 20th - December 2009Slide31

Mobile applications

WINLAB 20th - December 2009Slide32

Mobile why’s

Why does each mobile device need its own power supply?Why do I have to adjust the clock on my camera each time I travel?Why do I have to know what my IMAP server is and whether it uses TLS or SSL?Why do I have to “synchronize” my iPhone

?

Why do I have to manually update software?

Why

do we use USB memory sticks when all laptops have 802.11b?Slide33

Oct. 2007

33Context-aware communicationcontext = “the interrelated conditions in which something exists or occurs”anything known about the participants in the (potential) communication

relationship

time

at current location of destination

capabilities

audio, video, text, …

location

location-based call routing

location events

activity/availability

rich presence

automotive safety

sensor data (mood,

physiometric)

medical monitoringSlide34

Examples of “invisible” behaviorSlide35

Usability: Interconnected devices

any weather service

school closings

opens

(home, car, office) doors

incoming call

generates TAN

acoustic alerts

updates location

time, location

alert, events

address bookSlide36

Conclusion

Focus shifting: speed to diversity, functionality, autonomic behaviorApplications beyond voice and webmore than “Internet of things” & sensor networksSeamless user experience across cellular, WLAN & disruption-tolerant networksWINLAB 20th - December 2009Slide37

Backup slides

WINLAB 20th - December 2009Slide38

Deploying services

WINLAB 20th - December 2009

NetServ

Shared

hosting

Cloud

c

omputing

Dedicated

hosting

Colocation

Own

data center

Unit

Java task

VM

/html

server

rack

100s of racks

Provided

computation

storage

network

power

AC

computation

network

power

AC

web

server

network

power

AC

computation

storage

network

power

AC

network

power

AC

setup time

seconds

minutes

hours

day

week

years

cost

?

$1/hour

$0.10/GB

$0.10/GB-month

$20/month

$100/month

$550+/rack

$10M/yearSlide39

Networks beyond the Internet

Network modelroute stabilitymotion of data routersInternet

minutes

unlikely

mobile ad-hoc

3

τ

disruptive

store-carry-forward

< 3

τ

helpfulSlide40

Destination/delivery mode

Destination/delivery mode

Multicast

Anycast

Unicast

Interest-driven

Location-driven

Person

Location-driven

Any node that meets

conditions

e.g., any AP or

infostation to upload

Messages

7DS message delivery

Geographic routing

GeOpps

Community-

based routing

Interest-aware

communication

Geographic

routing

GeOpps

GeoDTN+Nav

Oracle-based

EBR

MaxProp

Prophet

Spray and wait

BUBBLE

SimBetSlide41

Depth and breadth

Depth and breadth

Two-hops / Source routing

More than two hops /

Per-hop routing

Single copy

Multiple copies

One-hop

Direct delivery

between a sender and a receiver

Single link

Multiple links

Flooding

Epidemic routing,

MaxProp

Shortest path

Oracle-based

Several possible paths

Oracle-based

GeOpps

GeoDTN+Nav

Prophet

SimBet

Spray and wait

EBR

BUBBLESlide42

Knowledge

Knowledge

Zero knowledge

Deterministic information

Temporal information

Spatial information

Route/destination-invariant

Mobility pattern

randomized routing

Epidemic routing

Spray and wait

7DS message delivery

Bus, train

Oracle-based

Probabilistic information

Popularity/centrality

Time-varying, dynamics are known

Time-invariant

Route-varying,

Destination- invariant

Satellite

Oracle-based

Satellite

GeOpps

GeoDTN+Nav

Oracle-based

Personal relationship

Route/destination location varying

Prophet

MobySpace

EBR

BUBBLE

SimBet

Navigation system

GeoDTN+Nav

MaxProp

Prophet