Experimental Performance Evaluation of Bit-Rate Selection Algorithms in Multi-Vehicular Networks
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IEEE 802.11 PHY supports multiple transmission rates according to multiple different modulations and coding schemes. Each WiFi station selects its own transmission rate according to its own algorithm; in particular, the IEEE 802.11 standards do not specify the bit-rate selection method. Although many adaptive bit-rate selection algorithms have been proposed, there is limited research and evaluation on the performance of such algorithms for roadside networks, especially in cases with multi-vehicle roadside multi-vehicular WiFi networks. In this thesis we propose an opportunistic highest bit-rate algorithm, Opportunistic Highest Bit-Rate Multi-Vehicular WiFi Networks (OHBR-MVN), specifically for roadside multi-vehicular WiFi networks. Our proposal is based on three key characteristics of such networks: (1) vehicles will drive closer to, and eventually pass, the roadside WiFi station, experiencing a progressively better transmission environment; (2) the vast majority of data transmitted in single-vehicle drive-by downloading scenarios occurs at the maximum transmission rate; (3) vehicles that transmit at less than the maximum rate do so at the expense of those that could send more data at a higher transmission rate. We therefore believe that transmitting only at the highest possible bit-rate is the preferred algorithm for such networks. Further, this approach keeps the bit-rate selection extremely simple, avoiding the complexity and resulting problems of adaptive approaches. Through a series of experiments that compare the throughput of both fixed and adaptive bit-rate selection algorithms we show that our approach yields both higher throughput and better fairness characteristics, while being significantly simple, and thus more robust.
Cite this version of the work
Giyeong Son (2011). Experimental Performance Evaluation of Bit-Rate Selection Algorithms in Multi-Vehicular Networks. UWSpace. http://hdl.handle.net/10012/5774