Decentralized Algorithms for Efficient Energy Management over Cloud-Edge Infrastructures

This paper presents an innovative approach to overcoming the limitations of traditional cloud-centric architectures in the evolving Internet of Things (IoT) landscape. We introduce a set of novel decentralized algorithms boosting Mobile Edge Computing (MEC), a paradigm shift towards placing computational resources near data sources, thus boosting real-time processing and energy efficiency. Our approach addresses the challenges of managing distributed Cloud-edge infrastructures in high-mobility environments, such as drone networks. Utilizing the Random Waypoint Model to anticipate device trajectories, our algorithms ensure effective resource allocation, enhanced load balancing, and improved Quality of Service (QoS). An in-depth complexity analysis further improves the scalability and performance of our method, demonstrating their ability to optimize energy efficiency and minimize latency, offering optimized offloading strategies in dynamic IoT environments.