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Enjoy the South African goodies

Enjoy the South African goodies. Rooibos 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 "

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Enjoy the South African goodies

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  1. Enjoy the South African goodies Rooibos 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

  2. License-free wireless networks for developing regions : reflection and future directions David Johnson MAE Presentation Committee Elizabeth 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?

  5. Some ideas • Dig trenches and lay fiber • Cover the world in LEO satellites • Cover rural areas with cellular/wimax networks • Use power line communication

  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 Now think again with this context % people living on <$2 per day

  7. The solution was/is MANET ad hoc networking protocols Extend range Build mesh networks Use directional/smart antennas $40 Change MAC for real time traffic Use multiple radios Channel allocation schemes Key lesson was: Free low cost resource spurred massive research/innovation

  8. But that said – cellular doing well But is this a solution for broadband access ?

  9. 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 ITU broadband penetration rankings1 Organization for Economic Cooperation and Development 2 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.

  10. What are the characteristics of the best solution • 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] Principle of Perato non-dominance holds true

  11. Successful deployments India: Airjaldi [Surana ‘08] Zambia: Linknet [Matthee ‘07] India: Aravind Eye-care S. Africa: Peebles Valley [Johnson ‘07]

  12. Presentation overview • Coverage optimization • Wireless mesh networking • Gateway discovery • Multiple radios • Link metrics 802.22 • Opportunistic routing • Smart antennas • Cognitive radios • Monitoring S D

  13. License-free is the root of the causality tree License free Primary user In LOS bands Secondary user In NLOS bands Low power requirement Interference detection requirement Less coverage area Spread spectrum 802.11 Cognitive radios Mesh networks (deal with LOS) Smart antennas

  14. 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

  15. 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 monitoring PLAN OPERATE MONITOR

  16. Coverage problem – random argument License-free frequencies 2.4 GHz 5.8 GHz A 700MHz (white spaces) How many nodes required to cover A with a k-connected network Statistical solution for unplanned networks [Bettsetter ’02]

  17. Coverage problem – planned argument • 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]

  18. 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 monitoring PLAN OPERATE MONITOR

  19. Mesh networks family tree D Mesh networks S Reactive Proactive Stigmergic Opportunistic Network Coding Hybrid 1,10 1,10 7 7 7 7 OLSR Jacquet 02 ZRP Haas 01 HSLS Santivanez 01 1,10 AODV Perkins 99 MORE Chachulski 07 1,9 1,10 1-3-5-7-8 B.A.T.M.A.N. Johnson 08 ExOR Biswas 05 5 5 5 DSR Johnson 96 3 3 3 8 8 8 DYMO Chakeres 07 5 SrcRR Morris 05 1-3-5-7-8 1-3-5-7-8 1 1 1 AntHocNet Di Caro 04 CodeOR Lin 08 3 8 1-3-5 1,10 1,5 1-3-5-7-8 1-3-5-7 6 6 6 1 9 9 9 1-3 1-3-5 4 4 4 2 2 2 6 1 1,8 9 Metrics 1-3-5-8 4 1-3-5-8 2 D 1-3-5-8 ETX Couto 03 ETT Draves 04 S

  20. Mesh networks – no one size fits all [Das ‘00, Johnson ’08]

  21. Taxonomy of mesh network development IEEE 802.1d 802.11s IETF Bellman-ford (‘56) RIP AODV [Perkins ‘98] OLSR [Jacquet ‘01] Djikstra (‘59) DSR [Johnson ‘98] OSPF Open source B.A.T.M.A.N [Johnson ‘08] *About 14 implementations Freifunk Academia ETX MORE ExOR *About 118 protocols Srcr ETT Commercial Meshdynamics Open-mesh Strix Meraki Tropos * http://en.wikipedia.org/wiki/List_of_ad-hoc_routing_protocols 8 March 2010

  22. 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 links

  23. Optimal Gateway selection Wired backbone • 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

  24. Opportunistic routing and network coding 90% A B • 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 30% 90% 85% 30% May get lucky! 10% S D 70% 70% C

  25. Multi-radio mesh and channel assignment Wired backbone • 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 2 1 P 1 1 2 1 3 3 2 UP-NICs C 1 1 DOWN-NICs 3 2 C1 C2 N1 N2

  26. So far we’ve existed in a world of • Antennas with fixed radiation patters • Fixed chosen frequencies with a specific bandwidth What happens if we break free of these limitations?

  27. Outline of research • Networking planning: • coverage optimization • Solutions from the past using 802.11 • Wireless 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 monitoring PLAN OPERATE MONITOR

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

  29. 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 RTS RTS CTS CTS DATA DATA DATA DATA ACK ACK DRTS(B) OCTS(B,C) OCTS(B,C) DRTS(D) DATA OCTS(D,E) OCTS(D,E) DATA DATA ACK DATA ACK A B C D E

  30. Smart antenna challenges D1 D1 D D S1 S1 S2 S2 D2 D2 Directional hidden terminal Deafness

  31. Smart antennas MAC solutions • 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

  32. 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 monitoring PLAN OPERATE MONITOR

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

  34. The typical environment of a cognitive radio [Akyldiz ‘06]

  35. Spectrum sensing • We have inherited very inefficient spectrum allocation • Need to use temporally unused spectrum, called white space or spectrum holes • Geographical variations in the utilization of assigned spectrum ranges from 15% to 85%

  36. Sensing and allocating channels 1.0 • Spectrum sensing for cognitive radios [Cabric ‘04] • Signals are cyclostationary - best use auto correlation • Cooperative sensing pays • Physical confLictgrAphgeNerator (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 0.8 0.6 Probability of interference Fraction of CRs used = 0 Fraction of CRs used = 0.1 Fraction of CRs used = 0.2 0.4 0.2 Number of users 40 50 20 30 10 Restrict -> Relax approach

  37. 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

  38. 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)

  39. 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

  40. 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? Lincoln, ID Salt lake city, UT Recovered by -114dBm rule with adjacent channel protection Recovered by -114dBm rule with out adjacent channel protection Actually available with adjacent channel protection Actually available without adjacent channel protection

  41. Explanation for white space graph Primary receiver Cognitive radio White space Primary transmitter Protection Pollution -108dBm -114dBm

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

  43. 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 monitoring PLAN OPERATE MONITOR

  44. 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

  45. 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

  46. To conclude …

  47. Best solution characteristics revisited

  48. 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

  49. Matrix of research areas Dtm = digital terrain model

  50. Ke a leboha Dankie Thankyou

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