Internet of Things offloading: Ongoing issues, opportunities, and future challenges

Internet of Things (IoT) has very remarkable advantages over customary communication technologies. However, IoT suffers from different issues, such as limited battery life, low storage capacity, and little computing capacity. For this reason, in many IoT applications and devices, we require an alternative unit to execute the tasks from the user's device and return results. In general, the problem of limited resources by transferring the computation workload to other devices/systems with better resources is addressed by offloading computation. It can be focused on improving the application, extending battery life, or expanding storage capacity. The offloading operation can be performed based on various quality of service (QoS) parameters that contain computational demands for load balancing, response time, application, energy consumption, latency, and other things. Moreover, the systematic literature review (SLR) method is used to identify, assess, and integrate findings from all relevant studies that address one or more research questions on IoT offloading and conduct a comprehensive study of empirical research on offloading techniques. However, we present a new taxonomy for them based on offloading decision mechanisms and overall architectures. Furthermore, we offer a parametric comparison for the offloading methods. As well, we present the future direction and research opportunities in IoT offloading computation. This survey will assist academics and practitioners to directly understand the progress in IoT offloading.