MIS的平均唤醒复杂度与匹配

M. Ghaffari, Julian Portmann
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引用次数: 9

摘要

Chatterjee、Gmyr和Pandurangan [PODC 2020]最近为分布式算法引入了唤醒复杂度的概念,该概念测量节点处于唤醒状态的轮数。在其他回合中,节点处于休眠状态,不执行任何计算或通信。测量唤醒轮数在分布式计算的许多设置中具有重要意义,例如,在关注能耗的传感器网络中。在那篇论文中,Chatterjee等人提供了一种优雅的随机算法来解决最大独立集(MIS)问题,该算法实现了O(1)个节点平均唤醒复杂度。也就是说,节点之间的平均唤醒时间为O(1)轮。然而,为了实现这一点,该算法牺牲了更标准的轮复杂度度量,从众所周知的MIS的O(łog n)界,由于Luby [STOC'85],到O(łog^3.41 n)轮。我们的第一个贡献是提出了一个简单的随机分布式MIS算法,该算法在高概率下具有O(1)节点平均唤醒复杂度和O(łog n)最坏情况轮复杂度。我们的第二个技术贡献是展示了对于最大匹配的1+ε近似和最小顶点覆盖的2+ε近似具有相同的O(1)节点平均唤醒复杂度和O(łog n)最坏情况轮复杂度的算法,其中ε表示任意小的正常数。
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Average Awake Complexity of MIS and Matching
Chatterjee, Gmyr, and Pandurangan [PODC 2020] recently introduced the notion of awake complexity for distributed algorithms, which measures the number of rounds in which a node is awake. In the other rounds, the node is sleeping and performs no computation or communication. Measuring the number of awake rounds can be of significance in many settings of distributed computing, e.g., in sensor networks where energy consumption is of concern. In that paper, Chatterjee et al. provide an elegant randomized algorithm for the Maximal Independent Set (MIS) problem that achieves an O(1) node-averaged awake complexity. That is, the average awake time among the nodes is O(1) rounds. However, to achieve that, the algorithm sacrifices the more standard round complexity measure from the well-known O(łog n) bound of MIS, due to Luby [STOC'85], to O(łog^3.41 n) rounds. Our first contribution is to present a simple randomized distributed MIS algorithm that, with high probability, has O(1) node-averaged awake complexity and O(łog n) worst-case round complexity. Our second, and more technical contribution, is to show algorithms with the same O(1) node-averaged awake complexity and O(łog n) worst-case round complexity for 1+ε approximation of maximum matching and 2+ε approximation of minimum vertex cover, where ε denotes an arbitrary small positive constant.
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