140 likes | 239 Views
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.
E N D
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 • 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
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”)
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
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
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)
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
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
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
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
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
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
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)
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