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Ad Hoc Networking with Bluetoot

Ad Hoc Networking with Bluetoot. Wireless Mobile Internet Mobicom, Rome, Italy, July 2001. Mario Gerla, Rohit Kapoor, Manthos Kazantzidis (UCLA), Per Johansson (Ericsson). Focus of the Paper.

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Ad Hoc Networking with Bluetoot

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  1. Ad Hoc Networking with Bluetoot Wireless Mobile Internet Mobicom, Rome, Italy, July 2001. Mario Gerla, Rohit Kapoor, Manthos Kazantzidis (UCLA), Per Johansson (Ericsson)

  2. Focus of the Paper • Two candidates for role of MAC layer in PANs: • IEEE 802.11- We assume use of DCF mode, which is the mode implemented in the WaveLAN cards. • Bluetooth – • We investigate only ACL links

  3. Simulation Environment • Simulation environment is NS-2 • It supports the 802.11 in the DCF mode • We augmented NS with the Bluetooth model • Bluetooth model • MAC layer implements features like FH, TDD, Multi-slot packets, ARQ etc. • Channel model takes into account path loss, shadowing and fading. • Slave polling strategy is the one used by Capone et.al. (“Efficient Polling Schemes for Bluetooth picocells, ICC 2001”)

  4. Case Study • Conference Hall – • Assume no infrastructure in the form of access points • Bluetooth or WaveLAN devices wanting to communicate • Simulation parameters – • 50m * 100m room; nodes randomly distributed • For Bluetooth, piconets formed by clustering nodes close enough to each other; number of slaves in each piconet chosen randomly • Piconets may overlap, causing collisions • Traffic consists of mix of TCP, Video and Voice

  5. Case Study (cont) • Voice Model • Brady model – On-off Voice sources, on and off times exponentially distributed, with mean 1sec and 1.35 sec respectively • Voice coding rate is 8 Kbit/s, packetisation period 20ms • TCP connections are large file transfers, 500-byte packets • TCP, Voice, Video connections in the ratio 1:1:1 • Experiments performed for different values of number of nodes and connections

  6. Video Traffic • Video sources • Real traces (Star Wars trailer clip, encoded using Intel’s H.263 compatible codec) • Traces smoothed – a frame returned by the codec is distributed uniformly in time using a target of 200-byte packets Figure 1: A few seconds from the H263 source trace (sec, bytes)

  7. Video Traffic • Adaptive and non-adaptive video • Non-adaptive video – average rate 256Kbps • Adaptive video • Uses average rates of 48, 64, 80, 128 and 256 Kbps • Adaptation is based on end-to-end periodic (1sec) feedback of number of pkts received in the interval • Server adapts its sending rate using max/min threshold • If loss rate < min threshold(=5%), server increases rate • If loss rate > max threshold(=15%), server reduces rate, choosing a rate that is appropriate to support the reported loss rate

  8. Video Traffic Experiment • Experiment targets at showing adaptive behavior of video with 802.11 and Bluetooth • Experiment parameters • 30 nodes, 60 connections • 90% of connections start at 8.6s and finish at 16.6s • Others start at 0.5s and run till 32s (end of simulation) • We study the adaptive behavior of a video connection that lasts throughout • When more connections are added (8.6s) • WaveLAN downgrades to lowest possible rate due to high loss rates • Bluetooth downgrades gradually since loss rates are lower

  9. End-to-End Adaptation • Fewer packets get lost for Bluetooth, but their delay is increased: • WaveLAN retransmits a collided packet a finite no. of times and then drops it; high collisions lead to large no. of packet drops • In Bluetooth, collisions are low due to FH; fewer dropped packets Bluetooth WaveLAN

  10. Loss Rates for video connections for H.263(x-axis is no. of nodes/ no. of connections) Conference Hall experiment for different number of nodes and connections - Non-Adaptive Video

  11. Video Loss rates higher for WaveLAN In Bluetooth, loss rates are less than 1% Loss rates are reduced in WaveLAN compared to non-adaptive video Conference Hall experiment for different number of nodes and connections - Adaptive Video

  12. A play-out buffer of 350ms may be needed for a packet loss ratio of less than 5% Since the scenario is of a congested network, uncontrolled access to channel causes large no. of collisions A play-out buffer of 80 ms achieves the same loss rate Voice delays lower for Bluetooth Controlled access of BT achieves keeps delays low Voice Results – 30 nodes, 60 connections

  13. Results • Aggregate throughput • Higher in WaveLAN for small number of nodes • For larger no. of nodes, BT increases capacity • For larger no. of connections, more collisions in WaveLAN cause throughput to be lower • TCP and Video share bandwidth better in Bluetooth • Loss Rates for adaptive video connections for H.263(x-axis is no. of nodes/ no. of connections)

  14. Conclusion • Bluetooth performs well in mixed data and real-time traffic scenarios • Gives better delays to voice traffic; lower loss rates for video • Bandwidth is shared better between Video and TCP; TCP does not show “capture effect” in Bluetooth • WaveLAN has higher system throughput for small number of nodes, but Bluetooth catches up when number of nodes is increased • Experiments performed with DCF mode of 802.11; in future, we plan to repeat for PCF mode

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