Reducing latency in fog computing through resource allocation optimization using cuckoo search algorithm
Aya Akram Sadeq, Soukaena Hassan Hashim, Shatha H. Jafer · 2023
The rapid growth of Internet of Things (IoT) applications has introduced various challenges, including quality of service, latency, disconnections, and delay. Despite the emergence of fog computing, these challenges persist. This abstract presents a new resource allocation mechanism to effectively tackle the latency challenges in fog computing. Our approach involves distributing requests and scheduling tasks using a queuing mechanism with three proposed lists: block, wait, and scheduling that based on loaded factors to select available nodes. To optimize resource allocation, we introduce the cuckoo search algorithm that measures the distance between users and fog nodes to select the nearest and available nodes for request processing, this algorithm significantly reduces latency. Our evaluation demonstrates the effectiveness of our approach by comparing latency measurements with and without the cuckoo search algorithm. The results exhibit a remarkable reduction in latency, with the algorithm cutting the distance in half, leading to an overall latency reduction. The proposed resource allocation mechanism, combined with the use of the cuckoo search algorithm, delivers tangible improvements in latency, thereby enhancing the overall performance of fog computing systems.