1. Multi-Channel Wireless Networks: Capacity and Protocols Pradeep Kyasanur and Nitin H. Vaidya University of Illinois at Urbana-Champaign

2. 2 Wireless networks Wireless channel Access Point AB Infrastructure-based Network C D Multi-hop Network  We consider multi-hop networks  Ad hoc networks, mesh networks, sensor networks

3. 3 Key limitation Wireless channel is a shared resource Simultaneous transmissions limited by interference Throughput reduces with multiple hops Higher density reduces per-node throughput Throughput reduces as number of flows increase New applications require higher throughput Streaming video, games Improving network capacity is important

4. 4 Multiple channels Typically, available frequency spectrum is split into multiple channels Large number of channels may be available Using all the available channels is beneficial 26 MHz100 MHz200 MHz150 MHz 2.45 GHz 915 MHz 5.25 GHz 5.8 GHz 3 channels8 channels4 channels 250 MHz500 MHz1000 MHz 61.25 GHz24.125 GHz122.5 GHz

5. 5 Current state of art Typical multi-hop networks use one channel only Key challenge: Connectivity vs using multiple channels Multiple channels not used Network is poorly connected A 11 1 1 1 BC D A 1 2 BC D

6. 6 Multiple interfaces Nodes may be equipped with multiple interfaces Common case may be small number of interfaces Wireless radio interfaces typically support one channel at a time We assume a half-duplex transreceiver Interface can switch to any channel Number of interfaces per node expected to be smaller than number of channels

7. 7 Example configuration IEEE 802.11 has multiple channels 12 in IEEE 802.11a Devices can be equipped with multiple interfaces E.g., one interface per PCMCIA/ mini-PCI slot Typically, fewer interfaces than channels 2 interfaces, 12 channels

8. 8 Focus of research Establish capacity of multi-channel networks How does capacity vary with channels? What are the insights from theoretical study? Design, implement and evaluate protocols Can we use existing protocols? Develop suitable protocols optimized for multi-channel networks How to implement protocols in real systems?

9. 9 Organization Capacity analysis Theory to protocols: Overview of challenges Protocols Interface Management Protocol Routing Protocol Implementation Issues Summary and Future Work

10. 10 Capacity problem Per-node capacity decreases as network density increases Use more channels when network density increases Challenge: Harder to scale interfaces at the same rate as channels How does the network capacity scale with large number of channels, and fewer interfaces than channels?

11. 11 Related work [Gupta&Kumar] have studied the capacity of single channel networks Result applicable for multi-channel networks when number of channels = number of interfaces per node [Gamal et al.] have studied the throughput-delay tradeoff Some of our constructions are based on their work Lot of work on studying capacity in other contexts Mobility, infrastructure-support, delay constraints, etc.

12. 12 Model n nodes in the network, all located on a unit torus c channels are available m interfaces per node Interface operates on one channel at a time Channel model 1: Total bandwidth W, each channel has bandwidth W/c Channel model 2: Total bandwidth Wc, each channel has bandwidth W

13. 13 Network scenarios [Gupta&Kumar] Arbitrary network Nodes can be located anywhere on the torus Traffic patterns can be arbitrarily chosen Measure of capacity – aggregate network transport capacity (bit-meters/sec) Random network Nodes are randomly placed on the torus Each node sets up a flow to a random destination Measure of capacity – minimum of flow throughputs (bits/sec)

14. 14 Results Established tight bounds Upper bounds and constructive lower bounds have same order Capacity depends on ratio of c to m Derived insights from constructions Capacity-optimal routing and scheduling strategies

15. 15 Arbitrary network – Region 1 Capacity constrained by interference

16. 16 Arbitrary network – Region 2 Capacity constrained by interfaces

17. 17 Random network – Region 1 Capacity constrained by connectivity + interference

18. 18 Random network – Region 2 Capacity constrained by interference (arbitrary n/w)

19. 19 Random network – Region 3 Capacity constrained by bottleneck destination

20. 20 Practical implications When m < c, it is better to use c channels If only m channels are used, larger capacity loss Single interface per node often suffices Up to log(n) channels, 1 interface is sufficient Switching delay may not affect capacity Extra hardware has to be provided

21. 21 Insights for protocol development Multiple interfaces can simplify protocol design Use one interface for receiving data on a fixed channel Use second interface for sending data Routing protocol has to distribute routes Important for multi-channel networks Optimal transmission range depends on density of nodes as well as number of channels Optimum: # of interfering nodes = # of channels

22. 22 Open issues Impact of switching delay has to be better studied Is switching required at all? Capacity under other switching constraints – switch among only a subset of channels Analyze capacity of deterministic networks Given a topology, what is the capacity? What protocols should be used to achieve this capacity?

23. 23 Organization Capacity analysis Theory to protocols: Overview of challenges Protocols Interface Management Protocol Routing Protocol Implementation Issues Summary and Future Work

24. 24 Assumptions Homogeneous channels: Channels with similar ranges and rates Possibly channels in same frequency band Alternatively, use appropriate power control 26 MHz100 MHz200 MHz150 MHz 2.45 GHz 915 MHz 5.25 GHz 5.8 GHz 3 channels8 channels4 channels

25. 25 Design choice: Multiple interfaces Theory indicates single interface may suffice But, multiple interfaces can hide switching delay Multiple interfaces simplify protocols Our proposal, described later, is simple to implement Multiple interfaces can allow full-duplex transfer Useful when multiple channels are available A 1 B C 2

26. 26 Design choice: Protocol separation Separate protocol design into two components Interface management Routing Interface management – shorter timescales Map interfaces to channels Schedule and control interface switching Routing – longer timescales Select “channel diverse” routes

27. 27 Protocol separation overview Routing and Interface assignment Interface Switching and Buffering IP Stack Interface User Space Kernel Space

28. 28 Link layer requirements Utilize all the available channels Even if number of interfaces < number of channels E.g.: Interfaces can be switched to different channels Ensure connectivity is not affected B should be able to communicate with A and D Need to be cognizant of switching delay A 1,23,4 B CD 2

29. 29 Link layer requirements Solution should be simple to implement Avoid the need for complicated co-ordination, tight time synchronization Allow implementation with existing hardware Avoid requiring hardware changes Avoid assuming specific hardware capabilities

30. 30 Routing requirements Improve single flow throughput by using multiple channels Both interfaces can be utilized at the relay nodes Improve network throughput by distributing flows A 13 B CD 2 A 1 4 B C E 2 DF 3

31. 31 Organization Capacity analysis Theory to protocols: Overview of challenges Protocols Interface Management Protocol Routing Protocol Implementation Issues Summary and Future Work

32. 32 Key components Interface assignment strategy How to map interfaces to channels? How to ensure neighboring nodes can communicate with each other? Interface management protocol Control when interfaces are switched, based on assignment strategy Buffer packets if interface is busy

33. 33 Interface assignment strategies Static Interface Assignment Interface to channel assignment is fixed Dynamic Interface Assignment Interface assignment changes with time Hybrid Interface Assignment Some interfaces use static assignment, others use dynamic assignment

34. 34 Static interface assignment Each interface is fixed to one channel Does not require frequent co-ordination A 1,2 B CD Not all channels used Common channel approach (e.g., [Draves2004Mobicom]) Varying channel approach (e.g., [Raniwala2005Infocom]) A 1,2 B CD 2 3 May lead to longer routes E 3 Not possible 3,4

35. 35 Dynamic interface assignment Interfaces can switch channels as needed E.g., [So2004Mobihoc, Bahl2004Mobicom] A 1 B D 2 D is unaware of B’s communication Co-ordination may be needed for each transmission Transmissions can dynamically occur on any channel A 1 - 4 B CD

36. 36 Hybrid strategies One common channel used as “control” channel One interface always fixed to this channel Remaining channels used as “data” channels Second interface switches among data channels Common control channel becomes a bottleneck Channel for data transmission negotiated on control channel A 1 B CD 11 2-4 [Nasipuri1999Wcnc] [Jain2001Ic3n]

37. 37 Proposed hybrid assignment One interface “fixed” on a channel Different nodes use different fixed channels Other interfaces “switch” as needed Dynamic assignment Fixed interface receives data on well-known channel Avoids co-ordination issues, deafness problems Switchable interfaces send on recipient's fixed channel Retain flexibility of dynamic assignment

38. 38 Hybrid assignment example A Fixed (ch 1) Switchable B Fixed (ch 2) Switchable C Fixed (ch 3) Switchable 12 32 Switchable interface of B switches to channel 3 when sending to node C, and to channel 1 when sending to node A Any node pairs within transmission range can communicate

39. 39 Identifying fixed channel Static Approach: Fixed channel as a function of node-identifier Simple to build, but may not balance assignment Dynamic approach: Choose fixed channel based on neighborhood information A node chooses least used channel for fixed channel Can balance load, and still inexpensive

40. 40 Interface management Each channel is associated with a queue Broadcast packets are inserted in to every queue Fixed interface services fixed channel queue Switchable interface services other channels Channels serviced in round-robin fashion Each channel is serviced for at most MaxSwitchTime

41. 41 UDP throughput – chain topology

42. 42 FTP throughput – chain topology

43. 43 Open issues Broadcast cost increases linearly with channels Consider partial broadcasts Use a separate broadcast channel, with third interface Fixed channel selection is topology-based Consider load, channel quality information Integrate with a routing solution

44. 44 Organization Capacity analysis Theory to protocols: Overview of challenges Protocols Interface Management Protocol Routing Protocol Heterogeneous channels Summary and Future Work

45. 45 Routing approach Existing routing protocols can be operated over interface management protocol May not select channel diverse routes Does not consider cost of switching interfaces Our solution Develop a new channel-aware metric Incorporate metric in an on-demand source-routed protocol

46. 46 Selecting channel diverse routes Most routing protocols use shortest-hop metric Not sufficient with multi-channel networks Need to exploit channel diversity A B C D 1 1 21 Route A-C-D is better When possible, select routes where different hops are on different channels

47. 47 Impact of switching cost Interface switching cost has to be considered Switching interfaces incurs a delay A node may be on different routes, requiring switching A B C D 21 2 1 Route A-B-D is better E 3 When possible, select routes that do not require frequent switching

48. 48 Designing a routing metric Measure switching cost for a channel Measure total link cost of a hop Combine individual link costs into path cost A B C D 21 2 1 E 3

49. 49 Measuring switching cost Switching cost depends on the likelihood a switch is necessary before transmission Fixed channel has cost 0 “Active” channel has low switching cost Switching cost (SC) directly proportional to time spent on other channels C D 1 E 3 0.9 0.1

50. 50 Routing protocol Incorporate metric in on-demand source-routed protocol (similar to DSR) RREQ messages modified to include link costs Source initiates RREQ Intermediate nodes forward RREQ if, New RREQ Cost of RREQ smaller than previously seen RREQ Destination can compute best path Using link cost information in sent RREQ

51. 51 Throughput in random networks

52. 52 Throughput with varying load

53. 53 Open issues Incorporate load information into MCR metric Support for route caching Metric does not allow route combination Design alternate metrics? Integrated routing and fixed channel selection Can improve performance at cost of increased complexity

54. 54 Organization Capacity analysis Theory to protocols: Overview of challenges Protocols Interface Management Protocol Routing Protocol Implementation Issues Summary and Future Work

55. 55 Lack of multi-channel support Existing assumptions break with multiple channels Assume # of channels = # of interfaces Routing table has interface information only Not easy to use multiple interfaces Switching channels requires explicit invocation Interfaces and channels not hidden from applications Frequent switching not permitted

56. 56 Requirements Hide interface management from “data path” Allow existing applications to work unmodified Break node-channel mapping Allow channel to be selected based on destination Support multi-channel / single channel broadcast Broadcast primitive required for many applications

57. 57 Proposed architecture Channel Policy Manager Interface and Channel Abstraction Layer IP Stack Interface ARP User Applications Abstraction layer exports single virtual interface Channel switching details are hidden Fixed channel selection, and routing protocol is implemented as part of channel policy manager Joint work with Chandrakanth Chereddi

58. 58 Organization Capacity analysis Theory to protocols: Overview of challenges Protocols Interface Management Protocol Routing Protocol Heterogeneous channels Implementation Issues Summary and Future Work

59. 59 Summary Goal of the project is to utilize multiple channels Research issues considered are Analysis of capacity of multi-channel networks Design of protocols for multi-channel networks Implementing protocol suite in testbed

60. 60 Future work Capacity analysis with switching delay What if there is no switching allowed at all? Flow-aware protocol design Assign channels based on channel quality and load Select routes based on existing routes Implementation and measurement Fully implement all protocols Measure characteristics of multiple channels

61. 61 Questions? More details at: http://www.crhc.uiuc.edu/wireless

62. 62 Backup Slides

63. 63 Arbitrary Network: Upper bound Interference constraints [Gupta&Kumar]: Each pair of simultaneous receivers must have minimum separation Separation depends on transmission radius Bounds the number of simultaneous transmissions Interface constraint: Only m interfaces available Each node can send/receive at most m bits/sec

64. 64 Arbitrary Network: Lower bound Divide torus in to square cells Each cell has nodes c sender nodes c receiver nodes

65. 65 Random Networks: Upper bound Arbitrary network constraints: Random network is a special case of an arbitrary network Connectivity constraint: A minimum transmission range is needed to ensure network is connected Destination bottleneck constraint: The maximum number of incoming flows at any node will limit per-flow throughput

66. 66 Lower bound: Routing Divide torus in to square cells of area a(n) a(n) depends on the number of channels Route through cells on the straight line joining source and destination Balance route assignment within each cell

67. 67 Lower bound: Step 1 schedule Divide every second in to “hop-color” slots Flow scheduling: For each hop of a flow, schedule its transmission in some hop-color slot Procedure: Build a routing graph Vertices are nodes in the network One edge for every hop Edge color the graph Number of colors used = number of hop-color slots Map each color to a “hop-color” slot Every hop is scheduled in slot associated with its color

68. 68 Lower bound: Step 2 schedule Divide each “hop-color” slot in to “node” slots Node scheduling: Each node can only transmit in its node slot Procedure: Build an interference graph Vertices are nodes in the network One edge for every pair of nodes that may interfere Vertex color the graph # of colors = # of node slots per hop-color slot Map each color to a slot Each node transmits only in slot associated with its color

69. 69 Switching Delay Initial analysis ignores interface switching delay Upper bounds do not mandate switching Open question: Is interface switching required at all Possible that switching delay does not affect capacity Lower bound constructions affected by delay Capacity affected only if there are latency constraints Even with latency constraints, multiple interfaces can hide delay

70. 70 Benefits of Proposed Strategy Frequent co-ordination not required Fixed channel information infrequently exchanged Maintains full-connectivity Any node pairs within transmission range can communicate No changes required to MAC protocol Can be built with existing IEEE 802.11 hardware

71. 71 Arbitrary networks Two capacity regions capacity is When capacity is When

72. 72 Random networks Three capacity regions capacity is 1) 2) capacity is 3) capacity is

73. 73 One approach Based on ETT measurement [ Draves2004Mobicom ] ETT(j) = Expected Transmission Time of packet LinkLossRate measurement modified LinkRate measured from probing driver

74. 74 One path metric (MCR) Based on WCETT [ Draves2004Mobicom ] Path cost limited by bottleneck channel cost ( X j ) Network throughput depends on aggregate cost

75. 75 CBR throughput

76. 76 CBR throughput