The ambitious goals of Fifth Generation (5G) mobile networks for higher system capacity, massive number of devices and flexibility in operations demand the network architecture to be much more flexible, efficient and autonomous. The design of Radio Access Network (RAN) is undergoing architectural transformations to increase the flexibility of deployment and programmability by leveraging Network Functions Virtualization (NFV), Software Defined Networking (SDN), and Cloud Computing. Hence, efficient resource management strategies with enhanced service quality play a vital role in realizing true benefits of 5G RAN. In this work, we propose a novel and dynamic resource management framework called «KORA» for 5G Cloud Radio Access network (C-RAN) considering spatio-temporal traffic heterogeneity exhibited at Remote Radio Units (RRUs). To minimize net energy consumption in the cloud data center and to maximize the service quality to end users, we formulate an Integer Linear Programming model (ILP) for KORA that performs efficient consolidation and relocation of Control Units (CUs) in 5G C-RAN. To alleviate the computational heaviness of the ILP optimization model, we propose a light-weight heuristic algorithm that is scalable and applicable to real-world dense deployments spanning a large set of CUs. By simulations, we compare and contrast between various distinctive features of 5G C-RAN architecture under study as well as evaluate the efficacy of our proposed KORA framework. The heuristic algorithm can save 27% of relocations and 33% of GBR flows from disruption, at increased energy consumption of 6.6% in data center as compared to KORA. © 2018 IEEE.