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Journal article : Review

Modern computing: vision and challenges

Abstract:
Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.teler.2024.100116

Authors


Publisher:
Elsevier
Journal:
Telematics and Informatics Reports More from this journal
Volume:
13
Article number:
100116
Publication date:
2024-01-08
Acceptance date:
2024-01-05
DOI:
EISSN:
2772-5030


Language:
English
Keywords:
Subtype:
Review
Pubs id:
1653732
Local pid:
pubs:1653732
Deposit date:
2024-05-02
ARK identifier:

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