Disclosing Edge Intelligence: A Systematic Meta-Survey
From remote (e.g., cloud-based) to local (e.g., Edge Intelligence) data processing.Abstract
The Edge Intelligence (EI) paradigm has recently emerged as a promising solution to overcome the inherent limitations of cloud computing (latency, autonomy, cost, etc.) in the development and provision of next-generation Internet of Things (IoT) services. Therefore, motivated by its increasing popularity, relevant research effort was expended in order to explore, from different perspectives and at different degrees of detail, the many facets of EI. In such a context, the aim of this paper was to analyze the wide landscape on EI by providing a systematic analysis of the state-of-the-art manuscripts in the form of a tertiary study (ie, a review of literature reviews, surveys, and mapping studies) and according to the guidelines of the PRISMA methodology. A comparison framework is, hence, provided and sound research questions outlined, aimed at exploring (for the benefit of both experts and beginners) the past, present, and future directions of the EI paradigm and its relationships with the IoT and the cloud computing worlds.
Vincenzo Barbuto
PhD Student in Information and Communication Technologies
My research focuses on developing and implementing AI techniques that can operate directly on data sources, such as sensors and IoT devices, to enable real-time and efficient decision-making at the network edge.