An Optimal Scheduling Method in IoT-Fog-Cloud Network Using Combination of Aquila Optimizer and African Vultures Optimization

Today, fog and cloud computing environments can be used to further develop the Internet of Things (IoT). In such environments, task scheduling is very efficient for executing user requests, optimal IoT requests increases productivity IoT-fog-cloud system. this paper, a hybrid meta-heuristic (MH) algorithm developed schedule in networks using Aquila Optimizer (AO) African Vultures Optimization Algorithm (AVOA) called AO_AVOA. AO_AVOA, exploration phase AVOA improved by AO operators obtain best solution during process finding solution. A comparison between AO_AVOA methods AVOA, AO, Firefly (FA), particle swarm optimization (PSO), Harris Hawks (HHO) according performance metrics as makespan throughput shows high ability solve problem networks.