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Dynamic resource allocation for supporting real-time multimedia applications in IEEE 802.15.3 WPANs

Dynamic resource allocation for supporting real-time multimedia applications in IEEE 802.15.3 WPANs

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The IEEE 802.15.3 medium access control (MAC) protocol is an emerging standard for high-rate wireless personal area networks (WPANs), especially for supporting high-quality real-time multimedia applications. Despite defining quality of service (QoS) signalling mechanisms for interoperability between devices, IEEE 802.15.3 does not specify resource allocation algorithms that are left to manufacturers. To guarantee the QoS of real-time variable bit rate (VBR) videos and utilise the radio resource efficiently, the authors propose a dynamic resource allocation algorithm. The proposed bandwidth allocation algorithm is based on a novel traffic predictor. Recently, the variable step-size normalised least mean square (VSSNLMS) algorithm was employed for on-line traffic prediction of VBR videos. However, the performance of the VSSNLMS algorithm significantly degrades due to the abrupt traffic variation occurring at the scene boundary. To tackle this problem, the authors design a novel traffic predictor based on a simple scene detection algorithm and the VSSNLMS algorithm. Analyses using real-life MPEG video traces indicate that the proposed traffic predictor significantly outperforms the VSSNLMS algorithm with respect to the prediction error. The performance of the proposed bandwidth allocation algorithm is also investigated by comparing several existing algorithms. Simulation results demonstrate that the proposed bandwidth allocation algorithm surpasses other mechanisms in terms of channel utilisation, buffer usage and packet loss rate.

References

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      • `Part 15.3: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for High Rate Wireless Personal Area Networks (WPANs)', IEEE Std 802.15.3–2003, September 2003.
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      • Garrett, M., Willinger, W.: `Analysis, modeling and generation of self-similar VBR video traffic', Proc. ACM SIGCOMM Comput. Commun. Rev., 1994, p. 269–280, 24, (4).
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      • P. Seeling , F.H.P. Fitzek , M. Reisslein . (2006) Video traces for network performance evaluation.
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      • P. Seeling , M. Reisslein , B. Kulapala . Network performance evaluation using frame size and quality traces of single-layer and two-layer video: a tutorial. IEEE Commun. Surv. Tutorials , 2 , 58 - 78
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      • A. Adas . Using adaptive linear prediction to support real-time VBR video underRCBR network service model. IEEE/ACM Trans. Netw. , 5 , 635 - 644
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      • Mpeg-4 and h.263 video traces for network performance evaluation, http://www.tkn.tu-berlin.de/research/trace/trace.html.
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      • NS-2: ‘NS-2 network simulator’, http://www.isi.edu/nsnam/ns/.
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      • Intel Lab: IEEE 802.15.3 MAC Model, http://www.macroangel.com/nslast.zip.
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