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A local algorithm to compute multiple connected dominating sets in wireless sensor networks

机译:计算无线传感器网络中多个连接的支配集的本地算法

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We investigate the problem of computing a family of connected dominating sets (CDSs) in wireless sensor networks (WSNs) in a distributed manner. Specifically, we present a local algorithm that computes a family S_1,S_2, ...,S_m of non-trivial CDSs with the goal to maximise α = m/k, where k = max_(u∈v)|(i :u ∈S_i}|. In other words, we wish to find as many CDSs as possible, while minimising the number of frequencies of each node in these sets. Since CDSs play an important role for maximising network lifetime when they are used as backbones for broadcasting messages, maximising α reduces the possibility of repeatedly using the same subset of nodes as backbones. We provide an upper bound on the value of α via a 'nice' relationship between all minimum vertex-cuts and CDSs in the network graph, and present a local algorithm for the α maximisation problem. For a subclass of unit disk graphs (UDGs), it is shown that our algorithm achieves a constant approximation factor of the optimal solution. Here, a WSN is modelled as an UDG.
机译:我们调查以分布式方式计算无线传感器网络(WSNs)中的连接控制集(CDS)族的问题。具体来说,我们提出一种局部算法,该算法计算非平凡CDS的族S_1,S_2,...,S_m,目标是最大化α= m / k,其中k = max_(u∈v)|(i:u ∈S_i} |。换句话说,我们希望找到尽可能多的CDS,同时尽量减少这些集合中每个节点的频率,因为CDS用作广播的骨干网对于最大化网络寿命具有重要作用。消息,最大化α减少了重复使用相同的节点子集作为主干的可能性,我们通过网络图中所有最小顶点切割和CDS之间的“精妙”关系为α值提供了上限, α最大化问题的局部算法。对于单位磁盘图(UDG)的子类,表明我们的算法实现了最优解的恒定逼近因子,在此,将WSN建模为UDG。

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