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首页> 外文期刊>IEEE transactions on wireless communications >Network lifetime maximization with cross-layer design in wireless sensor networks
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Network lifetime maximization with cross-layer design in wireless sensor networks

机译:无线传感器网络中的跨层设计可最大限度地延长网络寿命

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摘要

This paper investigates a cross-layer design approach for minimizing energy consumption and maximizing network lifetime (NL) of a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for MSSS WSN can be formulated as a mixed integer convex optimization problem with the adoption of time division multiple access (TDMA) in medium access control (MAC) layer, and it becomes a convex problem by relaxing the integer constraint on time slots. Impacts of data rate, link access and routing are jointly taken into account in the optimization problem formulation. Both linear and planar network topologies are considered for NL maximization (NLM). With linear MSSS and planar single-source and single-sink (SSSS) topologies, we successfully use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the optimal NL when all nodes are exhausted simultaneously. The problem for planar MSSS topology is more complicated, and a decomposition and combination (D&C) approach is proposed to compute suboptimal solutions. An analytical expression of the suboptimal NL is derived for a small scale planar network. To deal with larger scale planar network, an iterative algorithm is proposed for the D&C approach. Numerical results show that the upper-bounds of the network lifetime obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are obtained.
机译:本文研究了一种跨层设计方法,该方法可将具有能源约束的多源单汇(MSSS)WSN的能耗降至最低,并延长其网络寿命(NL)。可以通过在媒体访问控制(MAC)层中采用时分多址(TDMA)将MSSS WSN的优化问题表述为混合整数凸优化问题,并且通过放宽对时隙的整数约束,它成为凸问题。 。在优化问题的制定过程中,综合考虑了数据速率,链路访问和路由的影响。线性和平面网络拓扑均考虑用于NL最大化(NLM)。利用线性MSSS和平面单源单汇(SSSS)拓扑,我们成功地使用Karush-Kuhn-Tucker(KKT)最优性条件来导出所有节点同时耗尽时的最优NL的解析表达式。平面MSSS拓扑的问题更为复杂,提出了一种分解与组合(D&C)方法来计算次优解。对于小型平面网络,得出了次优NL的解析表达式。针对大规模平面网络,提出了一种D&C方法的迭代算法。数值结果表明,我们提出的优化模型获得的网络寿命上限是紧密的。获得了有关NL的重要见解以及WSN NLM的跨层设计的好处。

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