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Mercury: A modeling, simulation, and optimization framework for data stream-oriented IoT applications
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DOI：10.1016/j.simpat.2019.102037.png)
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摘要
En 中文
The Internet of Things is transforming our society by monitoring users and infrastructures' behavior to enable new services that will improve life quality and resource management. These applications require a vast amount of localized information to be processed in real-time so, the deployment of new fog computing infrastructures that bring computing closer to the data sources is a major concern. In this context, we present Mercury, a Modeling, Simulation, and Optimization (M&S&O) framework to analyze the dimensioning and the dynamic operation of real-time fog computing scenarios. Our research proposes a location-aware solution that supports data stream analytics applications including FaaS-based computation offloading. Mercury implements a detailed structural and behavioral simulation model, providing fine-grained simulation outputs, and is described using the Discrete Event System Specification (DEVS) mathematical formalism, helping to validate the model's implementation. Finally, we present a case study using real traces from a driver assistance scenario, offering a detailed comparison with other state-of-the-art simulators.
Keyword:
Fog computing
Edge federation
MBSE
IoT
Data stream
5G
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4.6
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2.6K
被引数:
4.8K
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