Available Bandwidth Estimation in IEEE 802.11- Based Wireless Networks Samarth Shah, Kai Chen, Klara Nahrstedt Department of Computer Science University.

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Presentation transcript:

Available Bandwidth Estimation in IEEE Based Wireless Networks Samarth Shah, Kai Chen, Klara Nahrstedt Department of Computer Science University of Illinois at Urbana-Champaign This work was funded by the DoD ONR MURI N and NSF EIA grants

Introduction n Theoretical channel capacity depends on the physical layer –1, 2, 5.5 or 11 Mbps for IEEE n Bandwidth actually available to the application is less due to: –Protocol overhead –MAC layer contention »Location-dependent in multi-hop or multi-cell environments –Location-dependent channel errors »Signal fading, bit-errors due to physical objects such as walls, doors, etc.

IEEE MAC and Our Scheme n IEEE MAC: –Carrier sense: »Medium idle? Send RTS »Medium busy? Wait until medium idle, backoff for collision avoidance, send RTS –RTS-CTS-DATA-ACK –Collision? Increase backoff interval exponentially n Our scheme: –Does not modify IEEE in any way –Uses data transmissions for bandwidth estimation »No separate probing packets, etc. –Performed in the device driver of the wireless interface »Device driver loaded as a module under Linux

Bandwidth Estimation n Measured BW = S/(t r – t s ) –Running average with decay/Average over an interval –More contention? More time channel sensed as busy, more RTS/CTS collisions, higher backoffs => BW estimate smaller –More channel errors? Bit-errors in RTS/DATA cause RTS/DATA retransmission => BW estimate smaller –Only successfully transmitted MAC frames used in estimate RTSCTSACK DATA (size S) channel busy, backoff, contention t s packet readyt r packet recvd time

Packet Size n Packet size affects BW estimate –Low channel bit-error rate (BER)? Larger packet size => higher throughput –High BER? Larger packet size => Larger probability of bit-error => lower throughput n Indexed table of BW estimates for different packet size ranges –Separate estimation for data and acks (i.e., higher-layer acks) at source and destination respectively T’put size Higher BER Lower BER

Normalization n For low BERs –Scenarios used in our simulation and testbed experiments –Increasing part of BER-packet size-throughput curve n Packet size from 64B to 640B n We can have a single estimate normalized to a reference packet size (512B) n Key observations for normalization: –Channel busy + backoff + RTS/CTS + ACK overhead same for packets of all sizes –Once channel captured, DATA is transmitted at physical channel rate, for all packet sizes n Normalization enables estimation at source for both data and acks

Simulation Results n CBR Contention experiments: –Running average with decay n Variable contention experiments (for predictability): –%age difference between successive 2 sec. intervals –1 contending TCP flow: >97% of the time 97% of the time <= 20% difference –7 contending TCP flows: >80% of the time 80% of the time <= 20% difference

Application n Channel Time Proportion (CTP) –A link has bandwidth estimate k bps, a flow over it requires j bps => it requires a fraction j/k of the channel shared by nodes in its neighborhood n Use this in admission control for both single- and multi-hop IEEE networks n Admission control inaccurate –Admitting new traffic increases contention in the shared channel –Changes bandwidth estimate of flows n Dynamic bandwidth management n For more see: –S. Shah, K. Chen and K. Nahrstedt, Dynamic Bandwidth Management in Single-hop Ad hoc Wireless Networks, MONET journal special issue on Algorithmic Solutions for Wireless, Mobile, Ad Hoc and Sensor Networks (eds. Bar-Noy, Bertossi, Pinotti and Raghavendra), –K. Chen and K. Nahrstedt, EXACT: An Explicit Rate-based Flow Control Framework in MANET, Technical Report UIUCDCS-R /UILU-ENG , Department of Computer Science, University of Illinois at Urbana-Champaign, updated December, 2002.