Edge Intelligence Service Orchestration with Process Mining

In the post-cloud computing era, edge computing as a distributed computing paradigm, integrating the core capabilities of computing, storage, network, and application, provides EIS (edge intelligence service), such as real-time business, data optimization, intelligent application, security, and priv...

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Bibliographic Details
Main Authors: Yong Zhu, Zhihui Hu, Zhenyu He
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/20/10436
Description
Summary:In the post-cloud computing era, edge computing as a distributed computing paradigm, integrating the core capabilities of computing, storage, network, and application, provides EIS (edge intelligence service), such as real-time business, data optimization, intelligent application, security, and privacy protection. The EIS has become the core value driver to promote the IoE (Internet of Everything), to dig deeply into data value and create a new ecology of application scenarios. With the emergence of new business processes, EIS orchestration has also become a hot topic in academic research. A design methodology based on a complete “describe-synthesize-verify-evaluate” process was established to explore executable design specifications for EIS by means of model validation and running instances. As proof of concept, a CPN (colored Petri net) prototype was simulated and its operational processes were discovered by process mining from event data available in EIS for behavior verification. The instances running on WISE-PaaS demonstrate the feasibility of the research methodology, which aims to optimize EIS through service orchestration.
ISSN:2076-3417