Load Balancing by Efficient Resource Allocation for Edge Devices

Fog computing is backed by widely dispersed fog nodes; from the cloud, it extends and is distributed, bringing networking power and processing, closer to IoT devices. The data majorly needs to be processed, inferred, stored, and sent to the cloud servers that negatively affect latency, security, mobility, and dependability in cloud-only systems. The cloud supports the ultra-low latency needs of delay-sensitive applications. However, the fog layer’s proximity to IoT devices can significantly reduce latency and satisfy these requirements. A new generation of applications and services is produced as a result of fog computing’s constant interaction with and support of the cloud. As load balancing is a crucial issue, a load balancing approach can considerably improve QoS parameters in a fog network. In fog networks, load balancing divides the incoming load among the available fog nodes using a technique in order to prevent over- or under-loading of the fog nodes. This method can reduce reaction time, cost, and latency while maximizing throughput, performance, and resource utilization.