Editorial

Efficient AI Applications in Edge-Cloud Environments

Authors

  • In-Young Ko 1) Korea Advanced Institute of Science and Technology, South Korea
  • Michael Mrissa 2) InnoRenew CoE, Slovenia 3 )University of Primorska, Slovenia
  • Juan Manuel Murillo 4) University of Extremadura, Spain 5) COMPUTAEX Foundation, Spain
  • Abhishek Srivastava Indian Institute of Technology Indore, India

Keywords:

Editorial

Abstract

The international workshop on Big Data-Driven Edge Cloud Services (BECS) provides a venue for scholars and practitioners to share their experi- ences and present their ongoing work in the development of data-driven AI applications and services in a distributed computing environment known as the edge cloud. The third edition of the workshop (BECS 2023)1 was held in conjunction with the 23rd International Conference on Web Engineering (ICWE 2023),2 which was held in Alicante, Spain on June 6–9, 2023.

This special issue of the Journal of Web Engineering focuses on address- ing the challenges related to the development and provision of highly efficient AI applications and services in edge cloud environments. For this issue, we have selected papers from BECS 2023 that emphasize the creation of high-performance edge-cloud infrastructure and the development of AI applications optimized for such infrastructure.

Downloads

Download data is not yet available.

Downloads

Published

2023-12-26

How to Cite

Ko, I.-Y. ., Mrissa, M. ., Murillo, J. M. ., & Srivastava, A. . (2023). Editorial: Efficient AI Applications in Edge-Cloud Environments. Journal of Web Engineering, 22(06), v-viii. Retrieved from https://journals.riverpublishers.com/index.php/JWE/article/view/24677

Issue

2023: Vol 22 Iss 6

Section

BECS 2023