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.

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

Savaglio C.
;
Fortino G.
2021-01-01

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.
2021
cloud computing
Data mining
edge computing
Internet of Things
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/360688
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 73
  • ???jsp.display-item.citation.isi??? 50
social impact