Scheduling IoT Application Tasks using Flamingo Search Algorithm in Cloud Computing

The cloud computing paradigm is quickly developing to meet the requirements of new (IoT) and computing. As a consequence, there has been a dramatic increase in the need for cloud services due to the popularity of IoT-based requests. To successfully meet application objectives while efficiently utilising computing capacity, intelligent scheduling algorithms are obligatory to schedule IoT request tasks on computer resources. In this work, Also present Flamingo Search (FS), a original swarm intelligence optimization procedure enthused by the flamingo's migratory and resourceful ways. to equip FSA with the exploitation skills necessary for an optimization procedure, a mathematical model of flamingo behaviour is constructed. Next, To outline the optimal parameter selection period and examine how changing the input parameters affects the search consequences of FSA. To show how useful and effective the given FSA approach is, experiments are run utilising workloads taken from the Parallel Workload Archive. Furthermore, evaluation findings reveal that our solution can enhance the throughput presentation of computing.