Modeling and evaluating performances of complex edge computing based systems: a firefighting support system case study

The edge computing paradigm enhances the exploitability of cloud computing by providing, in principle, the means to overcome the limitations in terms of responsiveness, bandwidth needs, privacy and availability in critical applications. By moving some of the components of the system towards the physical location in which results are timely needed, it is possible to support mission critical applications and back them up with the flexibility and the resource availability and scalability offered by the cloud, while keeping mission costs lower than with classical approaches. The main point is the fact that the cloud and edge components have to be correctly balanced to allow the best results at the lowest costs: this means that performance evaluation oriented models are crucial in the design, in the deployment and in the execution phases of the lifetime of the system. In this paper we present a modeling approach for complex critical edge computing based systems relying on the use of queuing networks, applied to a novel architecture aiming to support operations in case of medium or large scale incidents that involve firefighting scenarios. The architecture allows to coordinate firemen squads, equipped with sensors and augmented reality devices, to minimize mission problems and to timely exploit local and external information, and supports interoperation with homeland security, police and other forces.