This paper explores a unified framework for resource management, load optimization, and secure deployment in cloud-based distributed systems. Drawing upon contemporary and seminal works in cloud computing, distributed frameworks, virtualization technologies, and practical application contexts such as e‑learning, small- and medium‑sized enterprises (SMEs), and real-time video streaming, we articulate a comprehensive conceptual model that integrates resource allocation, workload balancing, data security, and energy efficiency. The proposed model leverages theoretical underpinnings from distributed systems and cloud virtualization, as well as empirical insights from recent studies, to address critical challenges including dynamic resource provisioning, load surges, data security over encrypted data, and overhead in framework initialization. Through a detailed methodological exposition and descriptive analysis of synthesized findings, we identify best practices and latent gaps, discuss limitations, and chart a roadmap for future experimental validation and extensions. The unified framework advances state-of-the-art understanding by bridging fragmented research streams into a cohesive architecture for resilient, efficient, and scalable cloud deployments.

Cloud computing, distributed systems, resource management

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