Special issue on big data computing service and machine learning applications

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-04-03 DOI:10.1016/j.future.2025.107836

Katerina Potika , Magdalini Eirinaki , Monica Vitali , Anna Bernasconi , Hiroyuki Fujioka

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引用次数: 0

Abstract

This Special Issue addresses the evolving landscape of big data generated by sensors, devices, and services. The shift from centralized cloud infrastructures to distributed systems that involve cloud, edge, and Internet of Things (IoT) devices requires innovative approaches to managing and analyzing big data. The key challenges include privacy, security, energy efficiency, data quality, and trust. This Special Issue invited researchers to submit innovative solutions covering topics such as: Big Data Analytics and Machine Learning; Integrated, Heterogeneous, and Distributed Infrastructures for Big Data Management; Big Data Platforms and Technologies; Real-time Big Data Services and Applications; Big Data Security and Privacy Preservation; Big Data Quality and Trust; Trustworthy data sharing; Sustainability and Energy-Efficiency of Big Data; Storage and Computation; Big Data and Analytics for Healthcare; Big Data Applications and Experiences. This initiative expands on discussions from the IEEE Big Data Service (BDS) 2023 conference held in Athens Greece, reaching a broader audience of researchers.

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大数据计算服务与机器学习应用特刊

本期特刊探讨了由传感器、设备和服务产生的大数据的发展前景。从集中式云基础设施到涉及云、边缘和物联网（IoT）设备的分布式系统的转变需要创新的方法来管理和分析大数据。关键的挑战包括隐私、安全、能源效率、数据质量和信任。本期特刊邀请研究人员提交创新解决方案，涵盖主题包括：大数据分析和机器学习；面向大数据管理的集成、异构、分布式基础设施大数据平台与技术；实时大数据服务与应用；大数据安全与隐私保护；大数据质量与信任；可信数据共享；大数据的可持续性和能源效率存储与计算；医疗保健领域的大数据与分析大数据应用与体验。该倡议扩展了在希腊雅典举行的IEEE大数据服务（BDS） 2023会议的讨论，吸引了更广泛的研究人员。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.