1 / 29

Self Organizing Wireless Mesh Networks

Self Organizing Wireless Mesh Networks. Microsoft Research March 21, 2003. Intel/Microsoft Quarterly Strategic CTO Review. What is a Mesh Network?. e.g. MeshNetworks, Invisible Networks, Radiant Networks, Nokia’s Rooftop Network. Architecture affects design decisions on

dezso
Download Presentation

Self Organizing Wireless Mesh Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Self Organizing WirelessMesh Networks Microsoft Research March 21, 2003 Intel/Microsoft Quarterly Strategic CTO Review

  2. What is a Mesh Network? e.g. MeshNetworks, Invisible Networks, Radiant Networks, Nokia’s Rooftop Network • Architecture affects design decisions on • Capacity management, fairness, addressing & routing, mobility management, energy management, service levels, integration with the Internet, etc.

  3. Scoping out the Problem • What is the achievable capacity in an ideal wireless mesh? How can we reach this optimal capacity? • What is the best way to reach mesh nodes? That is, how should we assign addresses and route packets within the mesh and to the Internet? • How should we ensure fairness and privacy for end-users and security for the network? How should we guard against malicious nodes? • What are the applications that exploit the properties of the Mesh?

  4. Mesh Formation: When does a viable mesh form? The answer is a function of the environment, and business model, however if we leave out the business model…

  5. Problem Formulation Question How many homes in the neighborhood have to sign up before a viable mesh forms? Answer depends on Definition of “viable” Neighborhood topology Wireless range Probability of participation by a given houshold Example Scenario Viable mesh: group of at least 25 houses that form a connected graph Topology: A North Seattle Neighborhood. 8214 houses, 4Km x 4Km Wireless range: 50, 100, 200 and 1000 meters Houses decide to join at random, independent of each other. We consider 0.1% to 10% participation rates.

  6. Mesh Formation: Simulation Results • 5-10% subscription rate needed for suburban topologies with 200 m wireless ranges • Once a mesh forms, it is usually well-connected • i.e. number of outliers are few (most nodes have > 2 neighbors) • Need to investigate other joining models • Business model considerations will be important Increasing range is key for viable mesh connectivity

  7. Investigating current technologies There are many problems with existing technology -- we cover only a few to make some points

  8. Background: The Hidden Terminal Problem Consider the following scenario [Tobachi75] • B is in range of A & C; A & C are out of range of each other • i.e. A & C are hidden from each other • A sends a packet to B • C sends a packet to B • The packets collide at B • results in reduction of throughput CSMA doesn’t work • C can’t know that it has to wait • since it can’t hear A B A C Solution: RTS/CTS - with intended transmission duration [Karn90]

  9. Multihop Networks Case: Packets in Flight Example RTS RTS RTS RTS RTS 1 2 3 4 5 6 7 8 9 10 11 CTS CTS Backoff window doubles 4 nodes are active, 2 packets in flight Backoff algorithm hurts Microsoft Confidential

  10. Single Hop Range and Hop Effect: 802.11a & 802.11b 1 wall / hop 802.11b versus 802.11a

  11. Conclusions from our Studies • Multihop with IEEE 802.11{a.b,g} • Severe throughput degradation as number of hops increase • Poor fairness properties • No guarantee that every user will get a fair share (equal) bandwidth • Current software (firmware) for ad hoc 802.11 connectivity is immature • Frequent disconnects & network partitioning, loss of bcast packets Bottom Line: Current off-the-shelf WLAN technologies are not suitable for multihop

  12. Overcoming Limitations, Innovating

  13. A 15-Node Mesh Testbed in Building 113 • IEEE 802.11a 1st generation wireless NICs • Internally developed multihop routing protocol • Packet overhead is minimal when nodes are relatively static • Use it for everyday tasks, email, web, etc. • On-going improvements in performance via intelligent software

  14. Increasing Capacity – Multiple Radios Multihop wireless networks with single radio are inefficient, as a node can not transmit and receive simultaneously. Network capacity can be significantly improved if a second radio, tuned to an orthogonal channel is available • Multiple radios provide frequency diversity • reduce contention • provide robustness

  15. MultiRadio Unification Protocol (MUP) • Allows systems to locally optimize use of available spectrum • Use existing hardware • Support legacy applications • Interoperate with legacy hardware • Global information should not be required

  16. Simulations with a Real Topology Mesh formation among 35 randomly selected houses 252 houses in a Seattle neighborhood Web surfer Range is 250 meters Routes via AODV (IETF) ITAP

  17. Performance using Seattle Neighborhood Using realistic Web Traffic 40-50% reduction in delay compared to a one-radio network

  18. How do Wireless Devices affect Mesh Performance Do we need Spectrum Etiquettes?

  19. Phone on In the presence of other 2.4 GHz devices Panasonic 2.4GHz Spread Spectrum Phone 5m and 1 Wall from receiver

  20. Local behavior affects Global Performance! Doesn’t care Packets get dropped!

  21. Summing it up • We believe community networking will become increasingly important. • MSR has several technologies in the works that will make it attractive. • Viable meshes (of 25 nodes or above) can be formed with as few as 10% of the homes participating - Need good range and capacity • Current off-the-shelf WLAN technologies are not suitable for building reliable high capacity meshes • Capacity can be improvedby utilizing the entire available spectrum • Local misbehaving wireless devices cause unacceptable performance reduction • At this time, per packet channel switching is not a viable option. Additional Notes: • Cross industry spectrum harmonization is important for this vision to succeed. • Mesh networking is an important area of research for MSR (researchers from Redmond, Cambridge & SVC Labs are involved).

  22. Backup

  23. Etiquette Proposal • Transmit Power Control (TPC) • Reduce interference between neighbors, increase capacity through increased spatial reuse • Dynamic Frequency Selection (DFS) • Reduce destructive interference resulting from simultaneous transmissions • Listen Before Talk with Channel Wait Time (LBT-CWT) • Eliminate the possibility of devices being shut out from using the spectrum In addition….

  24. Etiquette Proposal (cont.) • TPC is applied to the entire unlicensed band • DFS is applied to x % of the unlicensed band • LBT-CWT is applied to (100-x) % of the unlicsensed band For example, 5 GHz Unlicensed 6.0 5.6 5.9 5.5 5.8 5.4 5.7 5.3 5.2 5.1 5.0 US TPC, LBT-CWT TPC, DFS

  25. .... to achieve serious capacity improvement…range, power and topology control are necessary Microsoft confidential

  26. u u w w w v v Why Topology Control? u u w v V Increased Interference! Reduced throughput!

  27. Ensuring Connectivity while Decreasing Interference Who should be my neighbor ? What should be my transmission power? Power level influences range Power level determines interference Power level affects routes Want to decidelocally but want to guarantee connectivity globally

  28. Cone Based Algorithm Theorem: If a 5p/6 and we find a neighbor in the cone, then we are connected. a Transmit with minimum power within a cone till you hit a node -- that’s your power limit !

  29. Cone Based Algorithm with Edge Removal Performance: Before After

More Related