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Topology Control for Guaranteed Connectivity Provisioning in Heterogeneous Sensor Networks

机译:异构传感器网络中用于保证连通性供应的拓扑控制

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摘要

Topology control is important for heterogeneous sensor networks in order to minimize the total network power consumption under the constraint that all sensor nodes’ connectivity requirements are satisfied. To address this issue, an optimization problem is first formulated, which is formally proved to be NP-hard. For practical applications, an effective solution, named topology adaptation algorithm (TAA), is proposed. TAA adopts both graph theory and maximum flow theory to find prespecified node disjoint paths with low time complexity and high network power efficiency. In order to further save the network power consumption, a judgment theory is proposed to remove any unnecessary long edges at the beginning without affecting network connectivity. Both theoretical and numeric results show that the proposed topology control algorithm can outperform counterparts in terms of the total network power consumption, the percentage of supernodes achieving -connectivity, the average degree of nodes, and the average length of paths.
机译:拓扑控制对于异构传感器网络很重要,以便在满足所有传感器节点的连接性要求的约束下将总网络功耗降至最低。为了解决这个问题,首先提出了一个优化问题,该问题已被正式证明是NP难的。对于实际应用,提出了一种有效的解决方案,称为拓扑适应算法(TAA)。 TAA同时采用图论和最大流理论,以较低的时间复杂度和较高的网络功率效率找到预定的节点不相交路径。为了进一步节省网络功耗,提出了一种判断理论,从一开始就消除了不必要的长边而又不影响网络连通性。理论和数值结果均表明,所提出的拓扑控制算法在总网络功耗,实现连接的超节点的百分比,平均节点度和平均路径长度方面优于同类算法。

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