research-article

A Simulation-driven Methodology for IoT Data Mining Based on Edge Computing

Authors:

Claudio Savaglio,

Giancarlo FortinoAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 21, Issue 2

Article No.: 30, Pages 1 - 22

https://doi.org/10.1145/3402444

Published: 08 March 2021 Publication History

Abstract

With the ever-increasing diffusion of smart devices and Internet of Things (IoT) applications, a completely new set of challenges have been added to the Data Mining domain. Edge Mining and Cloud Mining refer to Data Mining tasks aimed at IoT scenarios and performed according to, respectively, Cloud or Edge computing principles. Given the orthogonality and interdependence among the Data Mining task goals (e.g., accuracy, support, precision), the requirements of IoT applications (mainly bandwidth, energy saving, responsiveness, privacy preserving, and security) and the features of Edge/Cloud deployments (de-centralization, reliability, and ease of management), we propose EdgeMiningSim, a simulation-driven methodology inspired by software engineering principles for enabling IoT Data Mining. Such a methodology drives the domain experts in disclosing actionable knowledge, namely descriptive or predictive models for taking effective actions in the constrained and dynamic IoT scenario. A Smart Monitoring application is instantiated as a case study, aiming to exemplify the EdgeMiningSim approach and to show its benefits in effectively facing all those multifaceted aspects that simultaneously impact on IoT Data Mining.

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Index Terms

A Simulation-driven Methodology for IoT Data Mining Based on Edge Computing
1. Computer systems organization
  1. Embedded and cyber-physical systems
2. Information systems
  1. Information systems applications
    1. Computing platforms
    2. Data mining

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cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 21, Issue 2

June 2021

599 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/3453144

Editor:
Ling Liu
Georgia Institute of Technology, USA

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Copyright © 2021 Association for Computing Machinery.

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Publication History

Published: 08 March 2021

Accepted: 01 May 2020

Revised: 01 April 2020

Received: 01 March 2020

Published in TOIT Volume 21, Issue 2

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Italian MIUR, PRIN 2017 Project “Fluidware”

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Almutairi RBergami GMorgan G(2024)Advancements and Challenges in IoT Simulators: A Comprehensive ReviewSensors10.3390/s2405151124:5(1511)Online publication date: 26-Feb-2024
https://doi.org/10.3390/s24051511
Islam MGuerrieri AGravina RFortino G(2024)A Meta-Survey on Intelligent Energy-Efficient BuildingsBig Data and Cognitive Computing10.3390/bdcc80800838:8(83)Online publication date: 30-Jul-2024
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