Efficient Machine Learning Systems in Edge Cloud Environments

IF 0.7 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Journal of Web Engineering Pub Date : 2024-11-01

In-Young Ko;Michael Mrissa;Juan Manuel Murillo;Abhishek Srivastava

引用次数: 0

Abstract

The international workshop on Big Data-Driven Edge Cloud Services (BECS) aims to provide a platform for scholars and practitioners to share their experiences and present ongoing work in developing data-driven AI applications and services within distributed computing environments, commonly referred to as the edge cloud.

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来源期刊

Journal of Web Engineering 工程技术-计算机：理论方法

CiteScore

1.80

自引率

12.50%

发文量

审稿时长

9 months

期刊介绍： The World Wide Web and its associated technologies have become a major implementation and delivery platform for a large variety of applications, ranging from simple institutional information Web sites to sophisticated supply-chain management systems, financial applications, e-government, distance learning, and entertainment, among others. Such applications, in addition to their intrinsic functionality, also exhibit the more complex behavior of distributed applications.