In recent years, edge and fog computing has emerged as a popular paradigm for reducing network congestion and serving real-time Internet of Things (IoT) based applications by delivering services near end-user devices without demanding high-speed Internet connectivity. This paper delves into the diverse quality of service (QoS) requirements of IoT applications, such as latency and real-time response, and the need to meet these for critical applications. The presence of many diverse, potentially resource-constrained devices in the IoT ecosystem has led to QoS concerns. Edge and fog computing paradigms are characterized by their ability to provide real-time responses and low-latency services. Quality improvement aims to increase efficiency and address the system’s requirements so that it can be run effectively. Therefore, a suitable collection of QoS attributes must be considered before any optimization strategy is implemented. The recent state of the art for QoS techniques in edge and fog computing is evaluated in this work. Thus, we analyzed effective QoS parameters for quality improvements in this work.