Enjoy the South African goodies

1

Enjoy the South African goodiesRooibos tea: "ooi" is the same as "oy" in boy, "o" make a perfect circle with your mouth

Koeksisters: "koek" is the same as "cook", "r" make a short sound of a cat purring

This presentation is done on Ubuntu, pronounced "ooboontoo"Meaning: "We are what we are because of other people"

“A person with ubuntu is open and available to others, affirming of others, does not feel threatened that others are able and good, for he or she has a proper self-assurance that comes from knowing that he or she belongs in a greater whole and is diminished when others are humiliated or diminished”

Archbishop Desmond Tutu

License-free wireless networks for developing regions :

reflection and future directions

David Johnson

MAE Presentation

CommitteeElizabeth M Belding (chair), Kevin Almeroth, Heather Zheng

3

"Always and everywhere, free resources have been crucial to innovation and creativity.”

- Lawrence Lessig in The Future of Ideas: The Fate of the Commons in a Connected World

4

Picture a deep rural village in Africa

How would you connect everyone in this village to each other and the Internet?

Some ideas Cover the world in LEO

satellites

5

Cover rural areas with cellular/wimax networks

Dig trenches and lay fiber

Use power line communication

Now think again with this context

6

90% to 100%80% to 90%70% to 80%60% to 70%50% to 60%40% to 50%30% to 40% 0% to 20%no data

% people living on <$2 per day

The solution was/is

7

$40

Extend range

Build mesh networks

Use directional/smart antennas

Change MAC for real time traffic

Channel allocation schemes

Use multiple radios

MANET ad hoc networking protocols

Key lesson was: Free low cost resource spurred massive research/innovation

But that said – cellular doing well

8

But is this a solution for broadband access ?

Is this just Africa’s problem?

From 2000 to 2006 the US dropped from 3rd to 16th in terms of share of people with broadband and the speed of these connections

9

1 International Telecommunications Union (ITU), http://www.itu.int/ITU-D/ict/statistics/at_glance/top20_broad_2005.html.2 Organization for Economic Cooperation and Development (OECD), http://www.oecd.org/sti/ict/broadband.

ITU broadband penetration rankings1

Organization for Economic Cooperation and Development 2

Low operating and start up costs Self-organizing – little skill needed to build Self-repairing – network survives if nodes go down Makes optimal use of available wireless spectrum Scalable to low or high density communities Scalable from small to large network sizes Works in environment with low bandwidth to Internet Energy efficient - suitable for renewable energy source Minimizes risk from logistical challenges (dirty power,

illiteracy, locally available, theft) [Brewer ‘06]

10

What are the characteristics of the best solution

Principle of Perato non-dominance holds true

Successful deployments

11

India: Airjaldi [Surana ‘08]

India: Aravind Eye-care

Zambia: Linknet [Matthee ‘07]

S. Africa: Peebles Valley [Johnson ‘07]

Presentation overview

12

Coverage optimization

S D

Wireless mesh networking

o Gateway discoveryo Multiple radios o Link metricso Opportunistic routing

Smart antennas Cognitive radios Monitoring

802.22

License-free is the root of the causality tree

13

License free

Low power requirement

Less coverage area

Mesh networks(deal with LOS)

Cognitive radios

Smart antennas

802.11

Spread spectrum

Primary userIn LOS bands Secondary user

In NLOS bands

Interference detection requirement

Motivation behind chosen themes

Areas I won’t cover but are still important Business models for low income users Social sciences to expose issues with introducing disruptive

technology into rural societies Delay-Tolerant Networking (DTNs) Distributed MAC schemes for 802.11 Telecommunications Policy research

Subset of themes chosen based on Matches characteristics of the ideal solution Fundamental work which is repeatedly referred to Ability of work to be technology agnostic

14

Outline of research Networking planning:

coverage optimization Solutions from the past using 802.11 mesh networks

Metrics Gateway selection Opportunistic routing Multi-radio mesh

What’s next: Improved spacial & frequency reuse Smart Antennas Cognitive radios and white spaces

Wireless monitoring15

PLA

NO

PE

RATE

MO

NITO

R

Coverage problem – random argument

16

A

How many nodes required to cover A with a k-connected network

License-free frequencies5.8 GHz 2.4 GHz

700MHz (white spaces)

Statistical solution for unplanned networks [Bettsetter ’02]

Coverage problem – planned argument

17

Topology issues [Robinson’06] Avoid totally random

deployment if possible Some perturbation from

basic structure ok Optimum location of Mesh

routers and gateways (NP Hard) Mixed Integer linear

programming solution [Amaldi ‘08 ]

Multi-objective particle swarm optimization [Benyamina ‘09]






PLA

NO

PE

RATE

MO

NITO

R

Mesh networks family tree

19

Mesh networks

Proactive Stigmergic OpportunisticNetwork Coding

AODVPerkins 99

DSRJohnson 96

SrcRRMorris 05

Hybrid

OLSRJacquet 02

ZRPHaas 01

DYMOChakeres 07

B.A.T.M.A.N.Johnson 08

HSLSSantivanez 01

Reactive

Metrics

ETTDraves 04

ETXCouto 03

ExORBiswas 05

AntHocNetDi Caro 04

CodeORLin 08

MOREChachulski 07

7

2

31

6

8

4

5

9

S

D7

2

31

6

8

4

5

9

11-3 1-3-5

1-3-5-81-3-5-81-3-5-8

1-3-51-3-5-7-8

1-3-5-7

1-3-5-7-81-3-5-7-8

1-3-5-7-8

S

DN13

2

D N H3 * 1

2 * 1

4 3 2

4 2 2

7

2

31

6

8

4

5

9N53

6

7

N8

7

5

9

7

2

31

6

8

4

5

9

1,10

1,10

1,10

1,10

1,10

1,9

1,8

1,5

Mesh networks – no one size fits all

20

Handles Mobility

CPU overhead

Startup time

Handles link saturation

Scales to large net

Routing overhead

AODV Good Not tested Slow Good Good LowDSR Average Not tested Slow Poor Average Very lowOLSR Not tested High Fast Poor Average

if MPR off else poor

Very high

B.A.T.M.A.N Not tested Low Average Good Not tested

High

[Das ‘00, Johnson ’08]

Taxonomy of mesh network development

21

Bellman-ford (‘56)

Djikstra (‘59)

RIP

OSPF

IEEE

IETF

Open source

Academia

Commercial

802.1d 802.11s

AODV [Perkins ‘98]

DSR [Johnson ‘98]OLSR [Jacquet ‘01]

B.A.T.M.A.N [Johnson ‘08]

SrcrExOR

MerakiStrixMeshdynamics Open-mesh

Freifunk

*About 118 protocolsMORE

Tropos

*About 14 implementations

* http://en.wikipedia.org/wiki/List_of_ad-hoc_routing_protocols 8 March 2010

ETX

ETT

http://en.wikipedia.org/wiki/List_of_ad-hoc_routing_protocols

Routing Metrics Hop count proved

inadequate for mesh Expected Transmission

Count (ETX)[DeCouto ‘03] Incorporates the effect of fwd

and rev link loss Ignores transmission rate

Expected transmission time (ETT) [Draves ‘04] Biased towards more high

data rate links22

Optimal Gateway selection Current protocols simply

choose best route to gateway Minimize total traffic

between APs [Tajima ‘06] Uses expected number of

associated clients Proactive approach to avoid

congestion [Nandiraju ‘06] Explicit messaging to change

gateway when congested

23

Wired backbone

Opportunistic routing and network coding Send packet to multiple next hop

neighbors Improve statistical chance of

packet delivery ExOR [Biswas ‘05]

Choose set of next hop nodes using best ETX

Batches packets Forwarder with best path to

destination sends MAC-independent Opportunistic

Routing and Encoding (MORE) [Chachulski07] Network coding technique Randomly mix packets and send to

multiple forwarders Good for multicast

24

S D

A

90%

B

C

30% 85%

90%

30%

10%

70% 70%

May get lucky!

Multi-radio mesh and channel assignment Adding multiple radios adds extra

capacity and allows full-duplex Distributed channel assignment

[Raniwala ’05] Load-aware channel assignment Nodes only assign channels to

down NICs - Prevents channel change ripple

Interference aware channel assignment [Ramachandran ’06] Use a common default channel Channel assignment server Multi-radio conflict graph -

represent edges as vertices

25

Wired backbone

1

1

2

3

1

3

12

1

3

2

2

1

P

C

C1 C2

N1 N2

UP-NICs

DOWN-NICs

So far we’ve existed in a world of Antennas with fixed radiation patters Fixed chosen frequencies with a specific bandwidth

26

What happens if we break free of these limitations?


coverage optimization Solutions from the past using 802.11

Wireless mesh networks Metrics Gateway selection Opportunistic routing Multi-radio mesh



PLA

NO

PE

RATE

MO

NITO

R

Smart Antennas Distance problem is solved in rural networks by adding

directional antennas. New device appearing may not be within range of one of the

beams … breaks self-configuring argument Smart antennas allow you beam form in another direction

28

Spacial Division Multiple Access (SDMA) Enhance the received signal Suppress interference Increase the network capacity

Early work on directional/smart antennas MAC for directional/smart antenna Assume you have directional and omni

antenna on each node DMAC [Ko ‘00] needs location

Send RTS directionally, CTS omni MMAC [Choudhury ‘02]

multi-hop RTS Allows directional – directional link

Performance of ad hoc with beamforming [Ramanathan ‘01] Directional neighbor discovery Soft collision avoidance

29

RTS RTS

CTS CTS

DATA DATA

DATA DATA

ACKACK

DRTS(B)

OCTS(B,C)OCTS(B,C)

DATA

DATA

DATA

ACK

DRTS(D)

OCTS(D,E)OCTS(D,E)

DATA

ACK

BA C D E

Smart antenna challenges

30

Directional hidden terminal Deafness

DS1

S2

D1

D2

DS1

S2

D1

D2

Smart antennas MAC solutions

31

Synchronous Collision resolution (SCR) [Stine ‘06] Use slotted channel Attempt to gain access every slot

Medium access for multiple beams [Jain ’08] TX/RX of multiple packets on different

beams, same channel Separate data queue for each beam Hybrid Network allocation Vector

(NAV) maintains beam - neighbor pairs






PLA

NO

PE

RATE

MO

NITO

R

Cognitive radios

33

Like animals and people they seek their own kind (other radios to communicate with); avoid or outwit enemies (interfering radios); find a place to live (usable spectrum); conform to the etiquette of their society (the Regulator); make a living (deliver the services that their user wants); deal with entirely new situations and learn from experience.

“A cognitive radio (CR) is a radio that can change its transmitter parameters based on interaction with the environment in which it operates” FCC

The typical environment of a cognitive radio

34

[Akyldiz ‘06]

Spectrum sensing

35

We have inherited very inefficient spectrum allocationNeed to use temporally unused spectrum, called white space

or spectrum holesGeographical variations in the utilization of assigned

spectrum ranges from 15% to 85%

Sensing and allocating channels Spectrum sensing for cognitive

radios [Cabric ‘04] Signals are cyclostationary - best

use auto correlation Cooperative sensing pays

Physical confLict grAph geNerator (PLAN) [Yang ‘08] Cumulative effect of interference Optimal radius can still be found

with unit disk assumption Build analytical framework to find

optimal radius Iterative radius adjustment of

individual nodes based on local conflict

36

10 3020 40 50

Number of users

0.2

0.8

0.4

0.6

1.0

Pro

babi

lity

of in

terfe

renc

e

Fraction of CRs used = 0Fraction of CRs used = 0.1Fraction of CRs used = 0.2

Restrict -> Relax approach

Cognitive radios in mesh networks Cognitive Mesh network

(COMNET) [Chowdhury ‘08] Primary/secondary band operation Distributed interference sensing All MRs get same contraints and

locally solve channel allocation Use contention window for channel

sensing Use Triangulation to detect primary

users

37

TV band white spaces On November 4, 2008, FCC issued a ruling permitting the use

of un-licensed devices in the white spaces [channel 21 (512 MHz) to 51 (698 MHz)]

Requirement for white space wireless devices not interfering with incumbents, including TV broadcasts and wireless microphone transmissions.

More TV broadcasts will be freed up because of transition to digital TV (DTV)

38

Country DateFaroe islands 2003

Luxembourg 2006

USA 2009-06-12

Russia Start in 2015

South Africa 2011-11-01

802.22 for Wireless Regional Area Networks Introduction to the first wireless standard based on cognitive radios [Cordeiro ‘06] Range up to 100km Physical – OFDMA MAC – centralized TDMA Vacate channel if DTV -116dBm,

ATV -94dBm, mic -107dBm Client directional to Base Station,

Omni for sense Cooperative sensing Client and Base Station transmit

co-existence beacon

39

How much white space is there [Mishra ‘09]?

Protection argument: Prevent harmful interference to primary users Pollution argument: More attractive for secondary user to move further from primary transmitter Actual available channels is based on an intersection of these view points Tradeoff for fading margin choice overall 30:1 (person-channels gained for white space : broadcast

channels lost) What’s more important TV or digital divide?

40

Recovered by -114dBm rule with adjacent channel protectionRecovered by -114dBm rule with out adjacent channel protection

Actually available with adjacent channel protectionActually available without adjacent channel protection

Salt

lake

city

, UT

Linc

oln,

ID

Explanation for white space graph

41

-114dBm

-108dBm

Cognitive radio

Pollution

Protection

Primary transmitter

Primary receiver

White space

Recent work in white spaces – Wi-Fi 2.0 WhiteFi [Bahl ‘09]

Create a Wi-Fi like network in white spaces

aggregate channels and vary width SIFT to detect AP any channel Clients sense - use backup channel

Dynamic Spectrum Access in DTV Whitespaces [Deb ‘09] Measures Aggregate spectral

efficiency (ASE) - client RSSI Control channel(CC) 433MHz (ISM) interference graph (IG) from CC proportionally fair white space

spectrum allocation uses ASE, IG, and AP demand

42SIFT = Signal interpretation Before Fourier 10 APs over square 500m, total users 0->50 uniform distribution






PLA

NO

PE

RATE

MO

NITO

R

Wireless monitoring How do you find the source of

Performance issues in the network No connectivity problems – partitioning of

network Turn you client devices into sensors and

use them as conduits [Adya ’04] Expanding ring of detail monitoring for

access point monitoring (Antler) [Raghavendra ’08] Finds out cause of performance problem

Interference Congestion Poor signal Authentication/Association problem

44

Wireless monitoring Principle in Antler applied to Mesh (MeshMon) [Raghavendra ’09]

Increase level of monitoring detail on client and mesh node when > threshold Able to debug upstream problem in mesh using command and control server

45

46

To conclude …

Best solution characteristics revisited

47

Characteristic Research area

Low operating and start up costs License-free wireless

Self-organizing and Self repairing Mesh networks

Optimal use of wireless spectrum Cognitive radios, coverage planning

Scalable to low/high density communities Smart antennas, coverage planning

Scalable from small to large networks Mesh networks with multiple radios, coverage planning

Works with low bandwidth Internet Optimal gateway selection, coverage planning

Energy efficient Smart antennas, coverage planning

Logistical challenges …

Open Problems Intersection of routing with smart antennas/ cognitive radios required cross-

layer design Degree of layer exposure is an ongoing research question

Coverage optimization for mesh Extend to real digital terrain models Change model for smart antennas and cognitive radios

Smart Antennas for mesh Build a link metric with directionality Synchronization issues with slotted scheme Opportunistic routing

Cognitive radios Link metric for mesh aware of available spectrum Channel allocation in non-continuous bands

48

Matrix of research areas

49

Coverage planning

Mesh routing

Link Metrics

Gateway discovery

Opportunistic routing

Multiple radio mesh

Smart Antennas

Cognitive radio

Monitoring

Coverage planning

Mature for cellular

Early stage – add dtm

x x Slight model change

new new new x

Mesh Routing

mature mature new for Rural networks

mature mature Early stage new early stage

Link Metrics

mature new mature mature new new x

Gateway discovery

mature x x x x x

Opportunistic Routing

Early stage Early stage new new incremental

Multiple radio mesh

mature new new incremental

Smart Antennas

Early stage in license-free

new incremental

Cognitive radio

Early stage

incremental

Monitoring mature

Dtm = digital terrain model

Ke a leboha Dankie

Thankyou

50

Enjoy the South African goodies

Documents

Transcript of Enjoy the South African goodies