REAP: Robust, Energy Efficient Wireless Sensor Networks for Outdoor Scenarios by Adaption of Operation Parameters

REAP：通过调整操作参数，为户外场景提供稳健、节能的无线传感器网络

• 批准号: 317849339
• 负责人: Professor Dr.-Ing. Felix Büsching
• 金额: --
• 依托单位: Institut für Betriebssysteme und Rechnerverbund
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/317849339?language=en
• 关键词: REAP; Robust; Energy; Efficient; Wireless

The opportunities for Wireless Sensor Networks are as well various and challenging. In agriculture, e.g., distributed sensors can be used to measure plant growth or for soil analysis. Here, robustness of single nodes and the whole network is of major importance for successful projects or smart farming approaches. Almost every environmental impact has also direct or indirect influence on the lifetime of the nodes or the network, whereby also huge deviations in environmental conditions occur. Provoked by sun exposure, a single sensor node can show a difference in temperature of 56° C in just one day. Additionally, there is an intense heterogeneity in temperature between the particular nodes within the network.To enable a long-term operation of sensor networks under such conditions they should be very robust against such influences and energy supply has to be ensured. Besides other things, robustness can be achieved by reducing the energy requirements of the node, respectively by adapting the requirements to the generation or vice versa. Additionally, some tasks (e.g., record, store, or process data) can be postponed or relocated in order to adapt them in the temporal or the spatial dimension, on a single node and/or within the network, and to adjust them to the specific environmental or energy conditions.So, especially in outdoor scenarios we have the situation that a.) Some nodes may work more energy efficient than others - due to their temperature and their individual characteristics (heterogeneity within the network) and b.) Changing environmental conditions (over time - e.g. direct sunlight / shadow or day / night) lead to dynamic shift of the energy efficiency of single nodes or the whole network. Opportunities for Energy Harvesting share this dynamics, as well.Monitoring the changing environmental conditions allows to benefit from the systems dynamics. Realistic models for energy and reliability will be derived from these measurements. Combined with the knowledge about the characteristics of the nodes in the network, this information can, e.g., be used for routing decisions, task scheduling, and processing within the network. By predicting the environmental variables, a suitable time for performing intensive computations or forwarding data in delay tolerant networks can be determined. Specific scheduling and routing protocols will be developed to achieve a robust wireless sensor network under dynamic conditions. The investigated relations and the implemented algorithms will be evaluated continuously in a real environment.

无线传感器网络的机会也是多种多样的，具有挑战性。例如，在农业方面，分布式传感器可用于测量植物生长或用于土壤分析。在这里，单个节点和整个网络的鲁棒性对于成功的项目或智能农业方法至关重要。几乎每一种环境影响也对节点或网络的寿命有直接或间接的影响，由此也会出现环境条件的巨大偏差。在阳光照射的刺激下，单个传感器节点可以在一天内显示56° C的温差。此外，网络中的特定节点之间存在强烈的温度不均匀性，为了使传感器网络能够在这种条件下长期运行，它们应该对这种影响非常鲁棒，并且必须确保能量供应。除此之外，还可以通过降低节点的能量需求来实现鲁棒性，分别通过使需求适应发电或反之亦然。此外，一些任务（例如，记录、存储或处理数据）可以被推迟或重新定位，以便在时间或空间维度上、在单个节点上和/或在网络内调整它们，并且将它们调整到特定的环境或能量条件。一些节点可能比其他节点更节能-由于它们的温度和它们的个体特征（网络内的异质性）和B.）环境条件的变化（随着时间的推移-例如直射阳光/阴影或白天/夜晚）导致单个节点或整个网络的能源效率的动态变化。能源收集的机会也共享这种动态。监测不断变化的环境条件可以从系统动态中受益。能源和可靠性的现实模型将从这些测量中得出。与关于网络中的节点的特性的知识相结合，该信息可以例如，用于路由决策、任务调度和网络内的处理。通过预测环境变量，可以确定在延迟容忍网络中执行密集计算或转发数据的合适时间。具体的调度和路由协议将被开发，以实现一个强大的无线传感器网络在动态条件下。所研究的关系和实现的算法将在真实的环境中持续评估。