An improved throttling algorithm for fog computing networks with an additional management layer

An emerging networking technique called fog computing extends cloud computing capabilities to the edge network's borders. It is employed to get around the limitations of cloud computing, like latency and bandwidth problems. Fog computing is suitable for IoT systems and applications that require real-time processing, reliable network access, low latency, and strong security. In this work, the objective is to design and implement a fog computing environment to simulate the behavior of a multi-user healthcare application, which represents the monitoring of elderly care homes in Mosul city. Several algorithms were employed to examine the effects of load balancing inside fog computing networks. These algorithms are Random, Round-Robin, and the modified Throttled algorithm, which is modified by adding an extra management layer to be more suitable for fog computing networks. The response time results obtained from implementing this modified method were superior to those of the random algorithm and closely resembled the response time results of the round-robin algorithm. In case QoS1 with 25 clients, the result was (0.246037794) second without the load balancing algorithm, (0.124323358) second in the Random algorithm, (0.115641477) second in the Round-Robin algorithm, and (0.114981575) second for the modified throttled algorithm. thus, making it applicable for fog computing networks and cloud computing networks.