George Giakkoupis , Volker Turau , Isabella Ziccardi
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引用次数: 0
摘要
我们重新考虑了卢比(Luby,1986 年)的开创性工作中提出的计算最大独立集的两种著名分布式随机算法。我们对这些算法进行了改进,使它们在不牺牲运行时间的情况下实现自稳定,也就是说,在任何 n 个节点图上,这两种算法都能在 O(logn) 同步轮中高概率地实现稳定。第一种算法有三种状态,但需要知道最大度的上限。第二种算法不需要任何有关图的信息,但使用的状态数与节点度呈线性关系。两种算法都使用对数大小的信息。
We reconsider two well-known distributed randomized algorithms computing a maximal independent set, proposed in the seminal work of Luby (1986). We enhance these algorithms such that they become self-stabilizing without sacrificing their run-time, i.e., both stabilize in synchronous rounds with high probability on any n-node graph. The first algorithm gets along with three states, but needs to know an upper bound on the maximum degree. The second does not need any information about the graph, but uses a number of states that is linear in the node degree. Both algorithms use messages of logarithmic size.
期刊介绍:
Information Processing Letters invites submission of original research articles that focus on fundamental aspects of information processing and computing. This naturally includes work in the broadly understood field of theoretical computer science; although papers in all areas of scientific inquiry will be given consideration, provided that they describe research contributions credibly motivated by applications to computing and involve rigorous methodology. High quality experimental papers that address topics of sufficiently broad interest may also be considered.
Since its inception in 1971, Information Processing Letters has served as a forum for timely dissemination of short, concise and focused research contributions. Continuing with this tradition, and to expedite the reviewing process, manuscripts are generally limited in length to nine pages when they appear in print.