01621nas a2200193   4500000000100000000000100001008004100002260001500043100002000058700001700078700001800095700002200113700001800135700002000153245006800173856004500241490001000286520113100296       2021                            d  cApril 20211 aPiotr Fröhlich1 aErol Gelenbe1 aJerzy Fiołka1 aJacek Chęciński1 aMateusz Nowak1 aZdzisław Filus00aSmart SDN Management of Fog Services to Optimize QoS and Energy  uhttps://www.mdpi.com/1424-8220/21/9/31050 v21(9)3 aThe short latency required by IoT devices that need to access specific services have led to the development of Fog architectures that can serve as a useful intermediary between IoT systems and the Cloud. However, the massive numbers of IoT devices that are being deployed raise concerns about the power consumption of such systems as the number of IoT devices and Fog servers increase. Thus, in this paper, we describe a software-defined network (SDN)-based control scheme for client–server interaction that constantly measures ongoing client–server response times and estimates network power consumption, in order to select connection paths that minimize a composite goal function, including both QoS and power consumption. The approach using reinforcement learning with neural networks has been implemented in a test-bed and is detailed in this paper. Experiments are presented that show the effectiveness of our proposed system in the presence of a time-varying workload of client-to-service requests, resulting in a reduction of power consumption of approximately 15% for an average response time increase of under 2%.