(untitled) (International Journal of Engineering and Computer Science, 2023)
As organizations have begun to adopt battening cloud computing technology, business needs have indicated the actual integration of edge computing into enterprise cloud, offering real-time data processing at low latency conditions. An edge computing system is performance-based, bringing such application processing nearer to the data source, thus bringing minimum reliance on central cloud infrastructure. This document studies distributed intelligence architectural pattern premises from approaches for effective deployment, security considerations, and optimization in performance. Key architectural patterns include cloud-edge hybrid models that merge centralized cloud computing with edge processing in dissemination to improve efficiency and resilience. Also, microservices-based architectures provide modular, scalable, and flexible deployments where enterprises can optimize the allocation of resources and adaptation of systems. AI for edge intelligence further augments real-time analytics through machine learning models at the edge, thus removing stringent and constant cloud connectivity and possible real-time analytics. Security is a further element necessitated by integrating edges into enterprise cloud systems. Other challenges like data encryption, secure communication, and access control should not be left unmonitored as they all have something to do with penetration strength toward safeguarding these systems from possible cyber attacks. Performance optimization strategies such as workload sharing, minimization of network latencies, and intelligent caching mechanisms define the entire system’s efficiency in maintaining its efficiencies. The paper highlights the design considerations for scalable, secure, and high-performance cloud-edge ecosystems through these different architectural patterns. Understanding these strategies leads enterprises to be best positioned to reap the benefits that edge computing offers without losing the flexibility and scalability characteristics of cloud services to the greater spectrum they set toward real-time data processing within the modern demands of business environments