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Efficiency analysis and derivation of enhanced deployment models for sensor networks

机译：效率分析和传感器网络增强部署模型的推导

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摘要

In this paper we analyse the efficiency of Distributed Source Coding (DSC) and its dependence on the node deployment strategies for Wireless Sensor Networks (WSN). The impact of correlation in both node locations and sensed phenomenon on the performance of WSNs in realistic environments is investigated. We show that significant energy savings and lifetime extensions are possible using DSC under different deployment models and varying data correlation structures. Furthermore, we derive enhanced pseudo-random deployment models that exploit different amounts of a priori information. Those models lead to significantly optimised initial network deployments which can be subsequently used with other existing optimisation techniques. The derived comprehensive framework enables thorough and realistic evaluation of WSNs even on bit-level. Overall the energy-efficiency, sensing coverage and lifetime of WSNs are strongly improved by our suggested deployment strategy.
机译：在本文中，我们分析了分布式源编码（DSC）的效率及其对无线传感器网络（WSN）节点部署策略的依赖性。研究了节点位置和感知现象之间的相关性对现实环境中无线传感器网络性能的影响。我们表明，在不同的部署模型和不同的数据关联结构下，使用DSC可以显着节省能源并延长使用寿命。此外，我们得出了利用不同数量的先验信息的增强型伪随机部署模型。这些模型导致对初始网络部署进行了大幅优化，随后可以将其与其他现有优化技术一起使用。派生的综合框架甚至可以在位级别上对WSN进行全面而现实的评估。通过我们建议的部署策略，WSN的总体能效，感测覆盖范围和使用寿命得到了显着改善。

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