Cloud Computing: Architecture, Intelligent Applications, Security, and Open-Source Case Studies

Abstract

Cloud computing has become a fundamental computing paradigm for delivering scalable computing, storage, networking, and software services. Its flexibility and resource-sharing capabilities have enabled applications in Artificial Intelligence (AI), Machine Learning (ML), cybersecurity, intelligent transportation, energy systems, and distributed computing. This paper presents a concise review of cloud computing architecture, service requirements, intelligent applications, security requirements, and emerging cloud-edge technologies, grounded in twenty-six references spanning foundational cloud computing literature and applied AI/systems research. The paper relates cloud computing to research involving face recognition, electronic toll collection, peer-to-peer energy trading, human-bot detection, federated intrusion detection, intelligent automation, graph algorithms, honeypot-based cybersecurity, and pedestrian trajectory prediction. Two open-source cloud platforms, OpenStack and Apache CloudStack, are examined through real-world case studies. Reported results demonstrate that open-source cloud platforms can operate at substantial scale: OpenStack reports deployments involving more than 40 million cores globally, while its Walmart case study reports more than 170,000 cores across over 30 regions; Apache CloudStack's IKOULA case reports more than 100 hosts across eight zones and more than 6,600 customers. The paper concludes that future cloud systems will increasingly integrate cloud, edge computing, AI, and privacy-preserving distributed learning.