NITOS能源监测框架:实验性无线网络部署中的实时电力监测

Stratos Keranidis, Giannis Kazdaridis, Virgilios Passas, T. Korakis, I. Koutsopoulos, L. Tassiulas
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引用次数: 11

摘要

节能协议和算法的开发需要深入了解现实世界设备的功耗特征。为此,研究界进行了能效分析,主要集中在功耗模型的开发上。然而,最近的研究[1]强调,即使在分析单个设备运行的非复合场景下,现有模型也无法准确估计能耗。在现实生活场景下,这些模型的无能进一步凸显,在现实生活中,多个设备同时运行所产生的冲击使得传统模型的应用完全不合适。因此,需要通过应用在线监测解决方案对复杂配置和拓扑下的能效评估进行实验研究。在这项工作中,我们提出了创新的NITOS能源消耗监测框架(EMF),能够支持在线监测能源消耗,以及实验执行。开发的框架建立在低成本的分布式网络上,但高度精确的设备,并与大规模无线NITOS测试平台完全集成。框架评估是在低级实验下进行的,低级实验展示了平台的高准确性,高级实验展示了在线和分布式监测如何促进对现实试验台实验的能源性能评估。
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NITOS energy monitoring framework: real time power monitoring in experimental wireless network deployments
Development of energy-efficient protocols and algorithms requires in-depth understanding of the power consumption characteristics of real world devices. To this aim, energy efficiency analysis is performed by the research community, mainly focusing on the development of power consumption models. However, recent studies [1] have highlighted the inability of existing models to accurately estimate energy consumption even in non-composite scenarios, where the operation of a single device is analyzed. The inability of such models is further highlighted under real life scenarios, where the impact induced by the simultaneous operation of several devices renders the application of traditional models completely inappropriate. As a result, energy efficiency evaluation under complex configurations and topologies, needs to be experimentally investigated through the application of online monitoring solutions. In this work, we propose the innovative NITOS Energy consumption Monitoring Framework (EMF) able to support online monitoring of energy expenditure, along with the experiment execution. The developed framework is built on a distributed network of low-cost, but highly accurate devices and is fully integrated with the large-scale wireless NITOS testbed. The framework evaluation is performed under both low-level experiments that demonstrate the platform's high-level accuracy, as well as through high-level experiments that showcase how online and distributed monitoring can facilitate energy performance assessment of realistic testbed experiments.
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