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Efficient computation of maximal independent sets in unstructured multi-hop radio networks

机译:非结构化多跳无线电网络中最大独立集的有效计算

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When being deployed, ad-hoc and sensor networks are unstructured and lack an efficient and reliable communication scheme. Hence, the organization of a MAC layer is the primary goal during and immediately after the deployment of such networks. Computing a good initial clustering facilitates this task and is therefore a vital part of the initialization process. A clustering based on a maximal independent set provides several highly desirable properties. Besides yielding a dominating set of good quality, such a clustering avoids interference between clusterheads, thus allowing efficient communication. We propose a novel algorithm that works under a model capturing the characteristics of the initialization phase of unstructured radio networks, i.e., asynchronous wake-up, scarce knowledge about the topology of the network graph, no collision detection, and the hidden terminal problem. We show that even under these hard conditions, the algorithm computes a maximal independent set in polylogarithmic time.
机译:部署时,自组织网络和传感器网络是非结构化的,缺乏有效而可靠的通信方案。因此,MAC层的组织是部署此类网络期间和部署之后的主要目标。计算良好的初始聚类有助于完成此任务,因此是初始化过程的重要组成部分。基于最大独立集的聚类提供了几个非常理想的属性。除了产生高质量的主要集合之外,这种集群避免了集群头之间的干扰,从而实现了有效的通信。我们提出一种新颖的算法,该算法在一种模型下工作,该模型捕获了非结构化无线电网络的初始化阶段的特征,即异步唤醒,对网络图拓扑的了解不足,没有冲突检测以及隐藏终端问题。我们表明,即使在这些困难的条件下,该算法也会计算出一个多对数时间的最大独立集。

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