TY - JOUR
T1 - Edge Computing and Analytics: An Extended Systematic Mapping Study
AU - Morariu, Andrei-Raoul
AU - Nybom, Kristian
AU - Shabulinzenze, Jonathan
AU - Multanen, Petteri
AU - Björkqvist, Jerker
AU - Huhtala, Kalevi
N1 - http://www.iariajournals.org/systems_and_measurements/index.html
PY - 2021
Y1 - 2021
N2 - Connected sensors and devices, the Internet of Things, already today produce more data than data connectivity and cloud services can handle. This gives rise to various forms of distributed sensor data handling, from surveillance cameras with built-in feature detection to alarm functionality in temperature sensors. There is an increased interest in being able to use this sensor data for distributed intelligence. The term "Edge Computing" is often used to denote this distributed computing, performed close to the sensors providing the data. Edge Computing enables services typically provided by cloud services with less communication, lower latency, and independence of the internet infrastructure. In this paper, we present a comprehensive, unbiased overview of state-of-the-art research on edge computing and analytics. From the taxonomy of the 90 identified articles, most articles address task scheduling and operation partitioning while data management and engineering, image and facial recognition, power optimization, and anomaly detection are generally also covered. Simulation remains the most used approach for validation, and research results based on implementations of edge systems in real-life environments are still sparse.
AB - Connected sensors and devices, the Internet of Things, already today produce more data than data connectivity and cloud services can handle. This gives rise to various forms of distributed sensor data handling, from surveillance cameras with built-in feature detection to alarm functionality in temperature sensors. There is an increased interest in being able to use this sensor data for distributed intelligence. The term "Edge Computing" is often used to denote this distributed computing, performed close to the sensors providing the data. Edge Computing enables services typically provided by cloud services with less communication, lower latency, and independence of the internet infrastructure. In this paper, we present a comprehensive, unbiased overview of state-of-the-art research on edge computing and analytics. From the taxonomy of the 90 identified articles, most articles address task scheduling and operation partitioning while data management and engineering, image and facial recognition, power optimization, and anomaly detection are generally also covered. Simulation remains the most used approach for validation, and research results based on implementations of edge systems in real-life environments are still sparse.
KW - edge computing
KW - systematic mapping study
KW - taxonomy
M3 - Article
SN - 1942-261x
VL - 14
SP - 27
EP - 36
JO - International Journal on Advances in Systems and Measurements
JF - International Journal on Advances in Systems and Measurements
IS - 1&2
ER -