Scalable compute continuum

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 : 2025-05-01 Epub Date: 2025-01-16 DOI:10.1016/j.future.2024.107697
Valeria Cardellini , Patrizio Dazzi , Gabriele Mencagli , Matteo Nardelli , Massimo Torquati
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Abstract

The Compute Continuum paradigm addresses the challenges of heterogeneous and dynamic computing resources, facilitating distributed application execution while enhancing data locality, performance, availability, adaptability, and energy efficiency. By integrating IoT, edge, and cloud resources into a cohesive continuum, applications can operate closer to data sources and end users. This approach supports refined adaptation strategies tailored to specific infrastructure components, enabling reduced latency, optimized bandwidth use, and improved privacy. To fully realize the Compute Continuum’s potential, autonomous and proactive management is essential, leveraging interdisciplinary methods from optimization theory, control theory, machine learning, and artificial intelligence. This special issue highlights advancements in three key areas: resource characterization and scheduling, middleware for application deployment and reconfiguration, and applications in the Compute Continuum. These contributions highlight innovative solutions for resource optimization, dynamic management, and real-world implementations, showcasing the potential of the Compute Continuum to revolutionize distributed computing across diverse domains.
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可扩展计算连续体
Compute Continuum范式解决了异构和动态计算资源的挑战,促进了分布式应用程序的执行,同时增强了数据的局域性、性能、可用性、适应性和能源效率。通过将物联网、边缘和云资源集成到一个内聚的连续体中,应用程序可以更接近数据源和最终用户。此方法支持针对特定基础设施组件定制的精细适应策略,从而减少延迟、优化带宽使用并改进隐私。为了充分发挥Compute Continuum的潜力,自主和主动管理至关重要,需要利用优化理论、控制理论、机器学习和人工智能等跨学科方法。本期专题突出了三个关键领域的进展:资源表征和调度、用于应用程序部署和重新配置的中间件,以及Compute Continuum中的应用程序。这些贡献突出了资源优化、动态管理和实际实现的创新解决方案,展示了Compute Continuum在跨不同领域彻底改变分布式计算的潜力。
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来源期刊
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.
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