A Comprehensive Study of Resource Provisioning and Optimization in Edge Computing

Efficient resource provisioning, allocation, and computation offloading are critical to realizing low-latency, scalable, and energy-efficient applications in cloud, fog, and edge computing. Despite its importance, integrating Software Defined Networks (SDN) for enhancing resource orchestration, task scheduling, and traffic management remains a relatively underexplored area with significant innovation potential. This paper provides a comprehensive review of existing mechanisms, categorizing resource provisioning approaches into static, dynamic, and user-centric models, while examining applications across domains such as IoT, healthcare, and autonomous systems. The survey highlights challenges such as scalability, interoperability, and security in managing dynamic and heterogeneous infrastructures. This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes. Furthermore, proposes future directions, including AI-driven optimization techniques and hybrid orchestration models. By addressing these emerging opportunities, this work serves as a foundational reference for advancing resource management strategies in next-generation cloud, fog, and edge computing ecosystems. This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.