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Using Stochastic Activity Networks to Study the Energy Feasibility of Automatic Weather Stations

机译:使用随机活动网络研究自动气象站的能量可行性

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Automatic Weather Stations (AWSs) are systems equipped with a number of environmental sensors and communication interfaces used to monitor harsh environments, such as glaciers and deserts. Designing such systems is challenging, since designers have to maximize the amount of sampled and transmitted data while considering the energy needs of the system that, in most cases, is powered by rechargeable batteries and exploits energy harvesting, e.g., solar cells and wind turbines. To support designers of AWSs in the definition of the software tasks and of the hardware configuration of the AWS we designed and implemented an energy-aware simulator of such systems. The simulator relies on the Stochastic Activity Networks (SANs) formalism and has been developed using the Mobius tool. In this paper we first show how we used the SAN formalism to model the various components of an AWS, we then report results from an experiment carried out to validate the simulator against a real-world AWS and we finally show some examples of usage of the proposed simulator.
机译:自动气象站(AWSS)是配备了许多环境传感器和用于监控恶劣环境的通信接口的系统,例如冰川和沙漠。设计这些系统是具有挑战性的,因为设计人员必须最大化采样和传输数据的时间,同时考虑到系统的能量需求,在大多数情况下,由可充电电池供电并利用能量收集,例如太阳能电池和风力涡轮机。为了支持AWSS的设计者在软件任务的定义和我们设计和实现了这种系统的能量感知模拟器的硬件配置中。模拟器依赖于随机活动网络(SAN)形式主义,并使用Mobius工具开发。在本文中,我们首先展示我们如何使用SAN形式主义来模拟AWS的各种组成部分,然后我们从执行的实验报告结果,以验证模拟器对真实世界AWS,我们终于显示了一些使用的例子提出的模拟器。

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