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A Novel Approximation for Multi-Hop Connected Clustering Problem in Wireless Networks

机译:无线网络中多跳连接群集问题的一种新型近似

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摘要

Wireless sensor networks (WSNs) have been widely used in a plenty of applications. To achieve higher efficiency for data collection, WSNs are often partitioned into several disjointed clusters, each with a representative cluster head in charge of the data gathering and routing process. Such a partition is balanced and effective, if the distance between each node and its cluster head can be bounded within a constant number of hops, and any two cluster heads are connected. Finding such a cluster partition with minimum number of clusters and connectors between cluster heads is defined as minimum connected -hop dominating set ( -MCDS) problem, which is proved to be NP-complete. In this paper, we propose a distributed approximation named CS-Cluster to address the -MCDS problem under unit disk graph. CS-Cluster constructs a sparser -hop maximal independent set ( -MIS), connects the -MIS, and finally checks and removes redundant nodes. We prove the approximation ratio of CS-Cluster is , where is a parameter related with but is no more than 18.4. Compared with the previous best result , our approximation ratio is a great improvement. Our evaluation results demonstrate the outstanding performance of our algorithm compared with previous works.
机译:无线传感器网络(WSN)已被广泛用于许多应用中。为了实现更高的数据收集效率,WSN通常被划分为几个不相连的群集,每个群集都有一个代表数据收集和路由过程的代表性群集头。如果每个节点与其簇头之间的距离可以限制在恒定的跃点范围内,并且任何两个簇头都已连接,则这种分区是平衡且有效的。找到具有最少数量的簇和簇头之间的连接器的簇分区定义为最小连接-跳跃支配集(-MCDS)问题,事实证明它是NP完全的。在本文中,我们提出了一种名为CS-Cluster的分布式近似值,以解决单位磁盘图下的-MCDS问题。 CS-Cluster构造一个稀疏的-hop最大独立集(-MIS),连接-MIS,最后检查并删除冗余节点。我们证明CS-Cluster的近似比率为,其中是一个与参数相关但不大于18.4的参数。与以前的最佳结果相比,我们的近似率有了很大的提高。我们的评估结果表明,与以前的工作相比,我们的算法具有出色的性能。

著录项

  • 来源
    《IEEE/ACM Transactions on Networking》 |2017年第4期|2223-2234|共12页
  • 作者单位

    Department of Computer Science and Engineering, Shanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai, China;

    Department of Computer Science and Engineering, Shanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai, China;

    Department of Computer Science and Engineering, Shanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai, China;

    Department of Computer Science and Engineering, Shanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai, China;

    Department of Computer Science and Engineering, Shanghai Key Laboratory of Scalable Computing and Systems, Shanghai Jiao Tong University, Shanghai, China;

    The University of Texas at Dallas, Richardson, TX, USA;

    The University of Texas at Dallas, Richardson, TX, USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Wireless sensor networks; Approximation algorithms; Clustering algorithms; Wireless networks; IEEE transactions; Two dimensional displays; Spread spectrum communication;

    机译:无线传感器网络;近似算法;聚类算法;无线网络;IEEE交易;二维显示;扩频通信;

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