EmPro: an Environment/Energy Emulation and Profiling Platform for Wireless Sensor Networks

EmPro: an Environment/Energy Emulation and Profiling Platform for Wireless Sensor Networks
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EmPro:无线传感器网络的环境/能源仿真和分析平台

DOI:
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发表时间:
2006
期刊:
2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks
影响因子:
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通讯作者:
P. Chou
P. Chou
中科院分区:
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文献类型:
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作者:
Chulsung Park;P. Chou

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无线传感器平台的定量评估是困难的。与可以从文件运行SPEC基准的通用计算机不同,很难再现刺激传感器节点所需的环境输入。即使可能,开环回放也无法正确解释这些节点行为中内置的自适应性。因此,研究人员求助于模拟,这种模拟没有考虑所有相关因素,而不会产生显著的速度损失。为了解决这个问题,我们提出了EmPro,环境/能源仿真和分析系统的无线传感器网络。它准确地输出电信号,不仅模拟传感器的数字和模拟输入,还模拟电源以及根据预编程序列的RF衰减。这种仿真方法使研究人员能够以逼真的方式实时运行网络传感器,具有完全的可控性和再现性。分析模式下的EmPro还可以捕获WSNs的可观察行为以进行详细分析。在Eco和MICA 2无线传感器网络平台上的实验结果表明,EmPro可以高精度地实时驱动这些硬件系统。我们希望EmPro能加快测试速度,并成为无线传感器网络平台急需的标准基准测试工具
Quantitative evaluation of wireless sensor platforms is difficult. Unlike general purpose computers that can run SPEC benchmarks from a file, it is difficult to reproduce the environmental input needed to stimulate the sensor nodes. Even if possible, open-loop playback would be unable to correctly account for adaptivity built into the behavior of these nodes. As a result, researchers resort to simulations, which do not consider all relevant factors without significant speed penalty. To address this problem, we propose EmPro, an environment/energy emulation and profiling system for WSNs. It accurately outputs electrical signals to emulate not only digital and analog inputs to the sensors but also the power sources as well as RF attenuation according to pre-programmed sequences. This emulation approach enables researchers to run the networked sensors in real-time in a realistic manner with full controllability and reproducibility. EmPro in profiling mode can also capture the observable behavior of WSNs for detailed analysis. Experimental results on the Eco and MICA2 WSN platforms show that EmPro can drive these hardware systems in real-time with high accuracy. We expect EmPro will expedite testing and serve as a sorely needed standard benchmarking tool for WSN platforms