Elastic multicast: Design extensions and experimentation results.

IEEE Military Communications Conference(2017)

引用 2|浏览4
暂无评分
摘要
This paper describes a new implementation of the Elastic Multicast (EM) protocol including new design enhancements for improved dynamic operation. The paper also presents additional performance data collected from emulation-based mobile network experiments. EM is a low complexity extension to Simplified Multicast Forwarding (SMF) that adds group-specific dynamic pruning of the SMF-based multicast forwarding mesh for higher rate traffic flows. It therefore reduces overhead by pruning the SMF relay sets in areas where no receivers exist. Our experimental emulation results show that, under a variety of mobility conditions and multicast group distribution patterns, EM maintains SMF-like data delivery robustness while significantly reducing overhead. We also demonstrate that a new design feature that provides preemptive ACK messages for active receiver groups leads to lower loss under mobility and sparse receiver groups. Based upon the results, we consider this feature critical to be included in any future EM design. We also present experimental results examining the performance of EM with classical flooding (CF) and connected dominating set (CDS) relay modes. We show, for the experiments examined, that CF provides some reduced loss with minimal additional overhead when used with EM. We also discuss future work and ongoing issues.
更多
查看译文
关键词
design extensions,design enhancements,improved dynamic operation,mobile network experiments,group-specific dynamic pruning,multicast forwarding mesh,SMF relay sets,EM design,elastic multicast protocol,low-complexity extension,simplified multicast forwarding,CDS relay modes,classical flooding,connected dominating set,minimal additional overhead,reduced loss,connected dominating,sparse receiver groups,active receiver groups,preemptive ACK messages,design feature,SMF-like data delivery robustness,group distribution patterns,mobility conditions
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要