Multi-Objective Optimal Deployment of SDN-Fog Infrastructures and IoT Applications

The Internet of Things has brought digitalization to intensive domains through the automation of their real-world processes. However, the criticality of these processes is reflected in high Quality of Service (QoS) requirements for the application to work properly. Moreover, business-level QoS, such as the operational cost, are also key to the feasibility of these applications. This QoS depends on three, closely-related dimensions: the application software, the computing devices and the communication network, which provide high flexibility to obtain different performances at different costs. Thus, to achieve optimal QoS in these scenarios, the application, computing and networking dimensions must be optimized, considering their crucial interplay in a joint effort. Furthermore, this solution must allow multi-objective optimization, finding the optimal trade-off between operational cost and application performance. In this paper, we present Multi-Objective SDN Fog Optimization (MO-SFO), a holistic framework that allows for the optimization of both the response time and the deployment cost. MO-SFO is evaluated over an emulated smart city case study, showing the cost and performance trade-off achieved in different topologies.