A Load Balancing Algorithm for Fog Computing Environments

Fog Computing is characterized as an intermediate layer between the Internet of Things layer and the Cloud Computing layer, which pre-processes information closer to the sensors. However, given the increasing demand for numerous IoT applications, even when close to the sensors, Fog nodes tend to be overloaded, compromising the response times of IoT applications that have latency restrictions, and consequently compromising users' quality experience too. In this work, we investigated ways to mitigate this problem in order to keep Fog Computing with a homogeneous distribution of load, even in heterogeneous environments, through the distribution of tasks among several computational nodes that compose Fog Computing, performing a dynamic load balancing in real time. For this, an algorithm model is presented, which takes into account the dynamics and heterogeneity of the computational nodes of Fog Computing, which allocates the tasks to the most appropriate node according to the policies predefined by the network administrator. Results show that in the proposed work the homogeneous distribution of tasks was achieved between the Fog nodes, and there was a decrease in response times when compared to other proposed solution.