Modern Computing: Vision and Challenges
arXiv:2401.02469 · doi:10.1016/j.teler.2024.100116
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.
Preprint submitted to Telematics and Informatics Reports, Elsevier (2024)
References in corpus (12)
- Mobile Edge Computing: A Survey on Architecture and Computation Offloading
- AI for Next Generation Computing: Emerging Trends and Future Directions
- HealthFog: An Ensemble Deep Learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing Environments
- Data Science: A Comprehensive Overview
- A Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects
- ChatGPT: Vision and Challenges
- Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS
- Magnetic reconnection in the era of exascale computing and multiscale experiments
- Efficient Dropout-resilient Aggregation for Privacy-preserving Machine Learning
- EsDNN: Deep Neural Network based Multivariate Workload Prediction Approach in Cloud Environment
- HUNTER: AI based Holistic Resource Management for Sustainable Cloud Computing
- Quantifying COVID-19 enforced global changes in atmospheric pollutants using cloud computing based remote sensing