Efficient resource utilization for multi-flow wireless multicasting transmissions

Tu, Wanqing

Abstract

Wireless multimedia services are major applications of next generation wireless networks. This paper is one of the first to study the efficient utilization of network resources for increasing the number of concurrent multimedia flows when a channel becomes saturated. We theoretically study the flow scheduling policy and the channel aggregation policy in both single-hop and multi-hop wireless networks with the motivation of ameliorating the trade-off between limited channel resources and multiple flow transmission. To increase the number of performance guaranteed multimedia flows, based on the dynamic states of wireless channels and the profiles of multimedia flows, the two policies fully utilize the performance gap to schedule concurrent flows for transmission in turn and aggregate multiple channels' residual capacities for useful flow transmissions. We then design a novel algorithm - efficient multi-flow multicast transmission (EMMT) - to apply the proposed policies to practical wireless multimedia multicast applications. At last, we use ns2 simulations to evaluate the studied policies and the EMMT algorithm. Our simulation results prove the effectiveness of our schemes in improving network ability to admit more multimedia flows. © 1983-2012 IEEE.

Citation

Tu, W. (2012). Efficient resource utilization for multi-flow wireless multicasting transmissions. IEEE Journal on Selected Areas in Communications, 30(7), 1246-1258. https://doi.org/10.1109/JSAC.2012.120810

• Journal Article Type: Article
• Online Publication Date: Jul 24, 2012
• Publication Date: Aug 9, 2012
• Deposit Date: Jun 1, 2025
• Journal: IEEE Journal on Selected Areas in Communications
• Print ISSN: 0733-8716
• Electronic ISSN: 1558-0008
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 30
• Issue: 7
• Pages: 1246-1258
• DOI: https://doi.org/10.1109/JSAC.2012.120810
• Public URL: https://durham-repository.worktribe.com/output/3999832