Improved QoS in Fog Computing by Efficient Resource Allocation in an Internet of Things Environment

Abstract

Large-scale application migration to fog computing is now being seen in the IT industry. The IoT is a prototype for connecting everyday objects to the web, such as sensors, gadgets (including those used in healthcare), and smart cameras. By analysing the data produced by the device, the IoT proposes a paradigm that simplifies infrastructure management and disaster recovery, hence improving the quality of life for humans.Fog Computing is a new computing paradigm that has emerged in recent years to meet the needs of latency-sensitive, geographically dispersed applications with high computational requirements. Fog computing is popular because it may be deployed near to the IoT nodes. Fog computing expands the computational, storage, and network capabilities of the cloud and serves as an intermediary layer between IoT devices and sensors. The nature of fog nodes makes resource management more difficult in fog. With fog computing, services and resources may be made available outside the cloud, close to the end devices. The inclusion of several heterogeneous devices, some of which may be mobile, makes ensuring adequate quality of service (QoS) in a fog system very difficult. Several quality-of-service considerations are accounted for, and QoS-aware techniques are provided in various portions of the fog system. So, in this article, we take a look at what's been done so far to ensure quality of service in fog computing. FogQSYM (Fog Queuing System) is an analytical model for Fog applications that helps to partition the application into many tiers and efficiently distribute resources based on factors such as memory, network speed, and processing power. When the infrastructure is built with lightweight computing devices, effectively allocating resources in the fog environment becomes a challenge. In a unified fog computing setting, we discuss how to assign tasks and locate virtual machines.