Self-organizing Energy-Minimization Placement of QoE-Constrained Services at the Edge

The wide availability of heterogeneous resources at the Edge of the network is gaining a central role in defining and developing new computing paradigms for both the infrastructures and the applications. However, it becomes challenging to optimize the system’s behaviour, due to the Edge’s highly distributed and dynamic nature. Recent solutions propose new decentralized, self-adaptive approaches to face the needs of this scenario. One of the most challenging aspect is related to the optimization of the system’s energy consumption. In this paper, we propose a fully decentralized solution that limits the energy consumed by the system, without failing to match the users expectations, defined as the services’ Quality of Experience (QoE). Specifically, we propose a scheme where the autonomous coordination of entities at Edge is able to reduce the energy consumption by reducing the number of instances of the applications executed in system. This result is achieve without violating the services’ QoE, expressed in terms of latency. Experimental evaluations through simulation conducted with PureEdgeSim demonstrate the effectiveness of the approach.