arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 0810.2513cs.NIcs.DCcs.ITmath.IT
收藏

移动性对Gossip算法的影响

The Impact of Mobility on Gossip Algorithms

Anand D. Sarwate, Alexandros G. Dimakis

摘要:

研究了网络中节点移动性对平均流言算法收敛时间的影响。结果表明,少量的完全移动的节点可以产生一个显着减少收敛时间。一种方法是开发用于推导收敛时间的下限合并节点根据其移动模式。这种方法是用来表明,如果代理有一维移动在同一方向上的收敛时间提高了最多一个常数。上界得到的收敛时间使用技术从理论的马尔可夫链,并表明,简单的移动模型可以显着加速八卦,只要移动路径显着重叠。仿真验证了不同的移动模式可以有显着不同的影响分布式算法的收敛性。

英文摘要:

The influence of node mobility on the convergence time of averaging gossip algorithms in networks is studied. It is shown that a small number of fully mobile nodes can yield a significant decrease in convergence time. A method is developed for deriving lower bounds on the convergence time by merging nodes according to their mobility pattern. This method is used to show that if the agents have one-dimensional mobility in the same direction the convergence time is improved by at most a constant. Upper bounds are obtained on the convergence time using techniques from the theory of Markov chains and show that simple models of mobility can dramatically accelerate gossip as long as the mobility paths significantly overlap. Simulations verify that different mobility patterns can have significantly different effects on the convergence of distributed algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑