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Cross-Layer Interactions in Multihop Wireless Sensor Networks: A Constrained Queueing Model

机译:多跳无线传感器网络中的跨层交互:约束排队模型

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In this article, we propose a constrained queueing model to investigate the performance of multihop wireless sensor networks. Specifically, the cross-layer interactions of rate admission control, traffic engineering, dynamic routing, and adaptive link scheduling are studied jointly with the proposed queueing model. In addition, the stochastic network utility maximization problem in wireless sensor networks is addressed within this framework. We propose an adaptive network resource allocation scheme, called the ANRA algorithm, which provides a joint solution to the multiple-layer components of the stochastic network utility maximization problem. We show that the proposed ANRA algorithm achieves a near-optimal solution, that is, (1 - ε) of the global optimum network utility where ε can be arbitrarily small, with a trade-off with the average delay experienced in the network. The proposed ANRA algorithm enjoys the merit of self-adaptability through its online nature and thus is of particular interest for time-varying scenarios such as multihop wireless sensor networks.
机译:在本文中,我们提出了一个约束排队模型来研究多跳无线传感器网络的性能。具体来说,与提出的排队模型一起研究了速率接纳控制,流量工程,动态路由和自适应链路调度的跨层交互。另外,在此框架内解决了无线传感器网络中的随机网络效用最大化问题。我们提出了一种称为ANRA算法的自适应网络资源分配方案,该方案为随机网络效用最大化问题的多层组件提供了联合解决方案。我们表明,所提出的ANRA算法实现了接近最优的解决方案,即全局最优网络效用的(1-ε),其中ε可以任意小,并且需要权衡网络中的平均延迟。所提出的ANRA算法通过其在线性质而具有自适应的优点,因此对于诸如多跳无线传感器网络的随时间变化的场景特别感兴趣。

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