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Application-aware techniques for energy efficient data collection in Wireless Sensor Networks

机译:无线传感器网络中用于节能数据收集的应用感知技术

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Wireless Sensor Networks (WSNs) are distributed systems composed of battery-powered nodes that sense and collect information about the physical world. They enable applications in a wide variety of domains including but not limited to environmental monitoring, health care and disaster management. In such applications, nodes communicate the sensed information over multiple radio links until it reaches its destination referred to as the sink. As wireless communication is the most energy hungry operation, the data collection causes the biggest drain from battery. This motivates research on energy efficient mechanisms for data collection. Though there is a plethora of protocols proposed in research literature, they are not designed to collaborate with the applications. One opportunity from such collaboration is exploiting complete knowledge about application characteristics to make data collection more energy efficient. This enables underlying layers not to provision the resources more than the needs of the application and therefore save valuable battery power. The aim of this thesis is to explore a complex interplay between application characteristics and adaptive mechanisms across network stack using concrete real world deployments. It will propose a generic framework that integrates the adaptations to achieve near-optimal energy efficiency for heterogeneous applications.
机译:无线传感器网络(WSN)是由电池供电的节点组成的分布式系统,这些节点感测并收集有关物理世界的信息。它们使应用程序可以在广泛的领域中使用,包括但不限于环境监控,医疗保健和灾难管理。在这样的应用中,节点通过多个无线电链路传递感测到的信息,直到其到达其目的地(称为接收器)为止。由于无线通信是最耗能的操作,因此数据收集会最大程度地消耗电池电量。这激发了对数据收集的节能机制的研究。尽管研究文献中提出了许多协议,但它们并不是为了与应用程序协作而设计的。这种合作的一个机会是利用有关应用程序特性的完整知识,以使数据收集更加节能。这使基础层可以不提供超出应用程序需求的资源,因此可以节省宝贵的电池电量。本文的目的是使用具体的实际部署来探索应用特性与跨网络堆栈的自适应机制之间的复杂相互作用。它将提出一个通用框架,该框架整合了各种适应技术,以实现异构应用的近乎最佳的能源效率。

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