Baghi, Zahra ShokriNavimipour, Nima Jafari2023-10-192023-10-19202331074-53511099-1131https://doi.org/10.1002/dac.5458https://hdl.handle.net/20.500.12469/5600Cloud computing has appeared as a technology allowing a company to employ computing resources such as applications, software, and hardware to calculate over the Internet. Scholars have paid great attention to cloud computing because of its cutting-edge availability, cost decrement, and boundless applications. A cloud database is a data storage site on the web where the optimal path is spotted to access the needed database. So, placing the ideal path to a database is crucial. The cloud database defined the scheduling problem to choose the perfect route. Cloud database path scheduling is a multifaceted procedure consisting of congestion control, routing list, and network flow distribution. It has a postponement in searching for the needed source route from the cloud database. Offering numerous infinite resources with the growing database workload is an NP-Hard optimization problem where the query request needs optimal schedules to respond to the required services. So, we have used a hybrid cuckoo search (CS) and genetic algorithm (GA), motivated by a social bird's phenomenon, to solve this problem. Integrating genetic operators has dramatically enhanced the balance between the capability of searching and utilization.eninfo:eu-repo/semantics/closedAccesscloud computingcloud databasecuckoo search algorithmAllocationgenetic algorithmoptimization algorithmsAllocationschedulingArticle836WOS:00093771410000110.1002/dac.54582-s2.0-85148638822N/AQ2