Prof. Maria Papadopouli

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24 Νοε 2013 (πριν από 3 χρόνια και 10 μήνες)

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1

Lecture on
Mobile P2P Computing


Prof. Maria Papadopouli

University of Crete

ICS
-
FORTH

http://www.ics.forth.gr/mobile







Agenda


Introduction on Mobile Computing & Wireless Networks


Wireless Networks
-

Physical Layer


IEEE 802.11 MAC


Wireless Network Measurements & Modeling


Location Sensing


Performance of VoIP over wireless networks


Mobile Peer
-
to
-
Peer computing


Exciting research problems


2

General Objectives


Build some background on wireless networks,
IEEE802.11, positioning, mobile computing


Explore some research projects


and possibly research collaborations


3

Environmental Monitoring

Source:
Joao
Da Silva’s talk at Enisa, July 20
th
, 2008

Tagged products

Source:
Joao
Da Silva’s talk at Enisa, July 20th, 2008

Source:
Joao
Da Silva’s talk at Enisa, July 20th, 2008

Source:
Joao
Da Silva’s talk at Enisa, July 20th, 2008

New networking paradigms for efficient search
and sharing mechanisms

Source:
Joao
Da Silva’s talk at Enisa, July 20th, 2008

9

10

Fast Growth of Wireless Use




Social networking (e.g., micro
-
blogging)



Multimedia downloads (e.g., Hulu, YouTube)



Gaming (Xbox Live)



2D video conferencing



File sharing & collaboration



Cloud storage


Next generation applications



Immersive video conferencing



3D Telemedicine



Virtual & Augmented reality



Assistive Technology




Rapid increase in the m
ultimedia mobile Internet traffic

Fast Growth of Wireless Use (2/2)



Video driving rapid growth in mobile Internet traffic


Expected to rise 66x by 2013 (Cisco Visual
Networking Index
-
Mobile Data traffic Forecast)


11

12

Energy constrains

13



W
ireless Internet via
A
P
s


D
ata
A
ccess via
I
nfostations


D
ata
A
ccess using the
P
eer
-
to
-
P
eer

paradigm






Hybrid mobile information access


(manifesting a combination of the above paradigms)



Paradigms of M
obile
I
nformation
A
ccess

14

A
ims at “continuous” wireless Internet access



broadly defined by three types networks
:


W
ireless wide area

networks (WANs)


W
ireless local area networks (LANs)


W
ireless personal

area networks (PANs)

Wireless
I
nternet via APs

15

Infostations


Wireless
-
enabled
s
erve
r

attached to
data repository


Wireless devices in range

can query the infostation to acquire

data


Can

be


stand
-
alone servers


clustered with other infostations connected over terrerstrial links

16


Di
stributed system
without

any


C
entralized control


Infrastructure



D
istinguished by the following

criteria


S
elf
-
organization


A
utonomy


S
ymmetry


Peer
-
to
-
Peer
s
ystems

Mobile Peer
-
to
-
Peer Computing


When two devices (peers) are in wireless range of
each other, they may share resources:


Share data


Network connection


Relay packets on behalf of each other


Enable resource sharing among peers in a self
-
organizing, energy
-
efficient manner

Wireless Network via an Infrastructure

Router

Internet

User A

User B

AP

Switch

Peer
-
to
-
Peer Paradigm

Server
-
to
-
Client Paradigm

Client gets data from AP



User C

How does information diffuse in mobile peer
-
to
-
peer systems
?

Trapping model from


particle
-
kinetics

Server
-
to
-
Client:

Applications Using Mobile P2P


Location
-
based applications


Social networking application




For example:
Facebook integrated with positioning,
google maps, 7DS, photojournal


User
-
centric access of the spectrum


19

Photojournal


Sharing multimedia files with your friends


Mobile P2P paradigm


Superimpose multimedia information on google
maps by correlating the timestamps of multimedia
files and recorded positioning information


Review, share, search multimedia files across a
(single
-
hop) network of friends


20

http://www.ics.forth.gr/mobile/

http://www.ics.forth.gr/mobile/


23

Research Issues on Cognitive Radios

INFORTE

Lecture Series


Prof. Maria Papadopouli

University of Crete

ICS
-
FORTH

http://www.ics.forth.gr/mobile







Underutilization of licensed spectrum


Licensed

portions

of

the

spectrum

are

underutilized
.


According

to

FCC,

only

5
%

of

the

spectrum

from

30

MHz

to

30

GHz

is

used

in

the

US
.

Cognitive radios


Intelligent

devices

that

can

coexist

with

licensed

users

without

affecting

their

quality

of

service


Licensed

users

have

higher

priority

and

are

called

primary

users


Cognitive

radios

access

the

spectrum

in

an

opportunistic

way

and

are

called

secondary

users



Networks

of

cognitive

radios

could

function

at

licensed

portions

of

the

spectrum


Demand

to

access

the

ISM

bands

could

be

reduced



Coexistence of secondary users


Usually, in cognitive radio networks, a large number of
secondary users compete to access the spectrum



A

protocol

should

define

the

behavior

of

all

these

users

such

that

the

network’s

performance

is

maximized



Performance metrics:


Spectrum utilization


Fairness


Interference to primary users

Performance optimization


Proposed

protocols

in

the

literature

define

an

optimization

problem


The

utility

function

depends

on

the

performance

metrics



Parameters

of

the

problem

are

chosen

from

the

following

set
:


Channel

allocation


Adaptive

modulation


Interference

cancellation


Power

control


Beamforming

Definition of the problem

1. Channel allocation


Problem formulation:


2 secondary users compete for access in the band [F
1

F
2
].


The interference plus noise power as observed by the first user
is:







Question
:

Which

is

the

best

way

for

this

user

to

distribute

its

transmission

power

at

the

interval

[F
1

F
2
]?

Channel capacity


According

to

Shannon

the

maximum

rate

that

can

be

achieved

in

a

channel

is
:




S
:

signal

power


N
:

interference

plus

noise

power


B
:

width

of

the

channel




As

the

power

that

is

introduced

to

a

channel

increases,

the

achievable

rate

increases

more

and

more

slowly
.










N
S
B
S
R
1
log
)
(
2
N
S
B
N
N
S
B
dS
S
dR




1
2
ln
1
1
1
2
ln
)
(
Energy investment in two channels


We

start

by

investing

energy

in

the

first

channel

until

it’s

total

power

becomes

equal

to

N
2
.


After

that

point,

energy

is

divided

equally

among

the

two

channels
.

ds
dR
ds
dR
N
B
N
B
2
1
2
1
1
2
ln
1
2
ln



ds
dR
ds
dR
N
B
P
N
B
2
1
2
1
1
1
2
ln
1
2
ln




Water filling strategy


The

best

way

for

a

user

to

invest

it’s

power

is

to

distribute

it

in

the

whole

range

of

frequencies
.

Channel allocation problem


M

users

compete

to

access

a

band


They

do

not

use

the

selfish

water

filling

strategy



Instead

they

cooperate

and

divide

the

spectrum

among

them

in

the

most

efficient

way



The

initial

band

is

divided

into

a

number

of

non

overlapping

frequency

bins


An

algorithm

maps

the

bins

to

users

in

such

a

way

that

a

global

utility

function

is

maximized

Cooperation

Is

it

possible

for

the

two

users

to

achieve

a

better

rate

if

they

cooperate?


Example
:








When

R
1

>

R
1

then

dividing

the

bandwidth

among

the

two

users

is

more

effective

than

water

filling
.


)
2
1
log(
2
2
1
N
P
P
B
R



)
1
log(
'
1
N
P
B
R


Channel allocation algorithm


There

are

various

ways

that

a

channel

allocation

algorithm

could

be

designed
.


Distributed

or

centralized
.


Proactive

or

on

demand
.


Predetermined

channel

allocation
.


Allocation

of

contiguous

or

non

contiguous

bins

to

devices
.

Primary and secondary channels


Channels

that

are

allocated

to

a

user

are

called

primary



Channels

that

a

user

borrows

from

the

neighborhood

are

called

secondary



Predetermined

channel

allocation

is

not

so

suitable

for

cognitive

radio

networks,

duo

to
:


Changes

of

channel

conditions

caused

by

primary

user

activity


Network

topology

changes

very

often



User
-
centric Spectrum Sharing


Spectrum is a valuable resource!



Improve its spectrum utilization


Primary users “sub
-
lease” part of spectrum


Secondary users take advantage of the unused
spectrum


Different algorithms for bin allocation across
secondary and primary users

37