Congestion-Aware Rate Adaptation in Wireless Networks: A Measurement-Driven Approach

Acharya, Prashanth Aravinda Kumar; Sharma, Ashish; Belding, Elizabeth; Almeroth, Kevin C.; Papagiannaki, Konstantina

doi:10.1109/sahcn.2008.11

Cited by 75 publications

(39 citation statements)

References 14 publications

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“…Finally, other protocols, [1,3] use timing information from the physical layer (such as "channel busy" time from Madwifi or packet interarrival times) to infer interference losses, but are susceptible to the same inefficiencies as frame-level protocols in general.…”

Section: Frame-level Bit Rate Adaptationmentioning

confidence: 99%

“…If the interferer's signal starts after the receiver synchronizes with the sender's frame, then the interference will manifest itself as a sudden spike in the BER estimated from SoftPHY hints 1 . A sudden change in BER by orders of magnitude within a small number of bits cannot be explained by stochastic channel fading, whose physics are more gradual.…”

Section: Interference Detectionmentioning

confidence: 99%

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Cross-layer wireless bit rate adaptation

Vutukuru¹,

Balakrishnan²,

Jamieson

2009

Proceedings of the ACM SIGCOMM 2009 Conference on Data Communication

268

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This paper presents SoftRate, a wireless bit rate adaptation protocol that is responsive to rapidly varying channel conditions. Unlike previous work that uses either frame receptions or signal-to-noise ratio (SNR) estimates to select bit rates, SoftRate uses confidence information calculated by the physical layer and exported to higher layers via the SoftPHY interface to estimate the prevailing channel bit error rate (BER). Senders use this BER estimate, calculated over each received packet (even when the packet has no bit errors), to pick good bit rates. SoftRate's novel BER computation works across different wireless environments and hardware without requiring any retraining. SoftRate also uses abrupt changes in the BER estimate to identify interference, enabling it to reduce the bit rate only in response to channel errors caused by attenuation or fading. Our experiments conducted using a software radio prototype show that SoftRate achieves 2× higher throughput than popular frame-level protocols such as SampleRate [4] and RRAA [24]. It also achieves 20% more throughput than an SNR-based protocol trained on the operating environment, and up to 4× higher throughput than an untrained SNR-based protocol. The throughput gains using SoftRate stem from its ability to react to channel variations within a single packet-time and its robustness to collision losses.

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Section: Frame-level Bit Rate Adaptationmentioning

confidence: 99%

Section: Interference Detectionmentioning

confidence: 99%

Cross-layer wireless bit rate adaptation

Vutukuru¹,

Balakrishnan²,

Jamieson

2009

Proceedings of the ACM SIGCOMM 2009 Conference on Data Communication

268

View full text Add to dashboard Cite

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“…In this approach the entire rate space is explored periodically to empirically identify the optimal rate. Examples of algorithms of this type include SampleRate [3], RBAR [10], OAR [11], WOOF [12], CHARM [13] and Smart-rate [14]. The second strategy is the incremental type where algorithms record statistics regarding their current rate and its neighboring rates, and make incremental changes.…”

Section: Related Workmentioning

confidence: 99%

“…To avoid using RTS/CTS, WOOF [12] uses Channel Busy Time (CBT) as an indicator of network load. Higher CBT means heavier traffic in the network, so that a transmission failure is more likely to be caused by collision rather than noise.…”

Section: B Packet-loss Based Estimatesmentioning

confidence: 99%

“…It supports several physical layer transmission rates, with 802.11b having four (1, 2, 5.5 and 11 Mb/s), 802.11a having eight (6,9,12,18,24,36,48 and 54 Mb/s), while 802.11g has all twelve of the 802.11b and 802.11a rates, and 802.11n has eight when using two streams at 20 Mhz and a guard interval of 800ns (13,26,39,52,78,104,117, 130 Mb/s). A range of rates are available as their modulation and coding schemes give them distinct robustness characteristics to noise on the medium.…”

Section: Introductionmentioning

confidence: 99%

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H-RCA: 802.11 Collision-Aware Rate Control

Huang

Duffy

Malone

2013

IEEE/ACM Trans. Networking

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Abstract-Rate control methodologies that are currently available in 802.11 network cards seriously under-utilize network resources and, in addition, per-second throughputs suffer from high variability. In this article we introduce an algorithm, H-RCA, that overcomes these shortcomings, giving substantially higher, and less variable, throughput. The approach solely uses information already available at the driver-level to function and can be implemented on 802.11e commodity hardware.H-RCA's design objective is to minimize the average time each packet spends on the medium (including retries) in order to maximize total network throughput. It uses a development of a recently proposed estimation scheme to distinguish transmission failures due to collisions from those caused by channel noise. It employs an estimate of the packet loss ratio due to noise in assessing whether it is appropriate to change rate. We demonstrate experimentally that packet loss ratio is not necessarily a monotonic increasing function of rate; this is accounted for in H-RCA's design.As H-RCA statistically separates noise losses from those caused by collisions, ns-2 simulations show that it is robust to changing environments. H-RCA does not require specific hardware support nor any change to the IEEE 802.11 protocol. This point is substantiated with results from an experimental implementation.

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Wireless Local Area Networks

2008

Wireless Broadband Networks

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I would like to express my deep and sincere gratitude to my supervisor, Doctor Ken Duffy. His wide knowledge and his logical way of thinking have been of great value for me. His superhuman patience, encouraging and personal guidance have provided a good basis for this thesis. During my PhD study, the most important thing he taught me is the principle of being scientific. That is 'every idea should come after a strong proof'. All of these are appreciated greatly.I should also send my sincere thanks to my great mentor, Doctor David Malone, who has helped me a lot. Without his help, our simulations and experiments could not run very well. During my PhD study, it was he that taught me so many sparkling ideas in scientific experimentation. Thank you very much.A number of people have made my stay in Ireland an enjoyable experience, especially Professor Douglas Leith. I am grateful to Rosemary Hunt, Kate Moriarty and Ruth Middleton for their willingness to help in all sorts of administrative matters.Finally, I am forever indebted to my parents and my wife for their understanding, endless patience and encouragement when it was most required.Thank you a billion times! xiii

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Congestion-Aware Rate Adaptation in Wireless Networks: A Measurement-Driven Approach

Cited by 75 publications

References 14 publications

Cross-layer wireless bit rate adaptation

Cross-layer wireless bit rate adaptation

H-RCA: 802.11 Collision-Aware Rate Control

Wireless Local Area Networks

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