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The Impact of Clustering in Distributed Topology Control

机译:聚类在分布式拓扑控制中的影响

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Topology control is the problem of assigning power levels to the nodes of an ad hoc network so as to maintain a specified network topology while minimizing energy consumption (either minimizing the maximum power used by any node or minimizing the total (i.e. average) power used by the nodes). In [18], a hybrid framework for distributed topology control based on clustering was proposed. That framework, called CLTC, specifies algorithms for both 1-connected and 2-connected topologies, and works with any clustering algorithm. CLTC utilizes centralized topology control within each cluster, but is otherwise fully distributed, hence the characterization of the method as hybrid. This paper studies the effect of six representative clustering methods on the quality of the topology control solutions provided by CLTC. The results establish that the most important factors in determining the performance of CLTC are the average cluster size and the closeness of nodes in clusters. This leads to a tradeoff between the energy consumption, the complexity of cluster formation, and the scope to which the operations of CLTC are fully distributed. The paper also shows that, in general, there is a considerable increase in power usage (in the vicinity of 150%) by requiring a 2-connected network versus a 1-connected network.
机译:拓扑控制是将功率级别分配给ad hoc网络的节点,以维持指定的网络拓扑,同时最大程度地降低能耗(最小化任何节点使用的最大功率或最小化单个节点使用的总(即平均)功率)的问题。节点)。在[18]中,提出了一种基于集群的分布式拓扑控制混合框架。这个称为CLTC的框架指定了1连接和2连接拓扑的算法,并且可以与任何群集算法一起使用。 CLTC在每个群集中利用集中式拓扑控制,但在其他方面却是完全分布式的,因此将方法表征为混合。本文研究了六种代表性聚类方法对CLTC提供的拓扑控制解决方案质量的影响。结果表明,确定CLTC性能的最重要因素是平均群集大小和群集中节点的紧密程度。这导致在能耗,集群形成的复杂性以及CLTC的运行完全分布的范围之间进行权衡。该论文还表明,一般而言,相对于1个连接的网络,通过2个连接的网络,功率使用量显着增加(在150%附近)。

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