Enhancing Cost and Latency Efficiency Through Service Placement in Containerized Fog-Cloud Computing Environments

As the demand for resource-intensive applications grows in fog-cloud computing environments, optimizing service placement becomes paramount to achieve efficient latency and cost savings. This paper presents a novel approach for latency and cost-aware placement of services in containerized fog platforms. By leveraging dynamic resource provisioning and workload scheduling algorithms, our solution aims to minimize both latency and cost while meeting service level objectives. We evaluate the effectiveness of our method through simulations and empirical studies. The results demonstrates significant latency and cost reductions compared to traditional placement strategies. This research contributes to the advancement of efficient resource management techniques in fog-cloud environments and provides practical insights for designing latency and cost-effective service placement solutions in containerized architectures.