Balancing Computing and Networking in Autonomous Edge Clouds

In the ever-changing environment of edge cloud systems, it is necessary to allocate diverse cloud resources in an efficient manner, at the same time, reducing energy consumption. A simple distributed resource allocation model is proposed in a previous study that utilizes a pseudo cost function of resource load, and it is shown that a convex function allows energy saving by pooling idle edge servers. In this paper, we extend this cost model beyond simple load, and present a method to balance computation and communication by merging multiple constraints into the cost function. We show trade-offs among soft constraints along with energy saving effects by simulation, using specific scenarios with computational and communication constraints. Our simulation results show that the combination of a convex function with a polynomial penalty function works well for balancing energy saving and other soft constraints.