A hierarchical control for application placement and load distribution in Edge Computing

Edge Computing (EC) extends computing functionalities from remote cloud data centers to the proximity of end-user devices at the network edges, thereby reducing application response time . However, existing solutions face challenges in scalability, efficient resource management, and near real-time adaptation in dynamic environments. In this paper, we jointly investigate the application placement and load distribution challenges in an EC-enabled mobile network. We propose a hierarchical distributed Limited Look-Ahead Control (LLC) approach that mitigates centralized control bottlenecks by breaking down the overall decision problem into a series of local problems solved cooperatively through a two-tier architecture. The global controller processes system-wide information and sets local constraints, while local controllers make autonomous decisions coordinated through mutual information exchange. Utilizing LLC allows for anticipation and adaptation to load fluctuations. Even though the results indicate that the trade-off between system performance and scalable decisions depends on how the overall problem is decomposed, our distributed solution significantly reduces the controller’s execution time compared to a centralized approach. • Limited Look-ahead Control can equip the Edge system for predicted load fluctuations. • Decentralized hierarchical control leads to faster execution time. • Centralized solution costs more as base station resources are placed closer to users. • The size and number of Edge clusters can affect deadline violation numbers. • Co-op control lowers deadline violation but raises migration costs vs. non-co-op ones.