@inproceedings{bb3232ebf63a46dcbd1f4aba84bdfe22,
title = "An Architecture for Intelligent Data Processing on IoT Edge Devices",
abstract = "As the Internet of Things edges closer to mainstream adoption, with it comes an exponential rise in data transmission across the current Internet architecture. Capturing and analyzing this data will lead to a wealth of opportunities. However, this ungoverned, unstructured data has the potential to exhaust the resources of an already strained infrastructure. Analyzing data as close to the sources as possible would greatly enhance the success of the IoT. This paper proposes a distributed data processing architecture for edge devices in an IoT environment. Our approach focuses on a vehicular trucking use case. The goal is to recreate the traditionally centralized Storm processes on the edge devices using a combination of Apache MiNiFi and the user's custombuilt programs. Our approach is shown to preserve computational accuracy while reducing by upwards of 90 percent the volume of data transferred from edge devices for centralized processing.",
keywords = "Apache MiNiFi, Context Aware Computing, Data Distribution, Edge Processing, Internet of Things",
author = "Roger Young and Sheila Fallon and Paul Jacob",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 19th IEEE UKSim-AMSS International Conference on Modelling and Simulation, UKSim 2017 ; Conference date: 05-04-2017 Through 07-04-2017",
year = "2018",
month = may,
day = "14",
doi = "10.1109/UKSim.2017.19",
language = "English",
series = "Proceedings - 2017 UKSim-AMSS 19th International Conference on Modelling and Simulation, UKSim 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "227--232",
editor = "Glenn Jenkins and Alessandra Orsoni and Richard Cant and David Al-Dabass",
booktitle = "Proceedings - 2017 UKSim-AMSS 19th International Conference on Modelling and Simulation, UKSim 2017",
address = "United States",
}