Sadrishojaei, M.Navimipour, N.J.Reshadi, M.Hosseinzadeh, M.2023-10-192023-10-19202371868-5137https://doi.org/10.1007/s12652-023-04650-5https://hdl.handle.net/20.500.12469/4842Clustering and routing protocols for Internet of Things (IoT) need to consider energy usage and how to reduce it. Unbalanced power usage is a common concern with current solutions to cluster-based routing problems in the IoT ecosystem. This research developed a swarm intelligence-based clustering technique to achieve a more uniform dispersion of cluster heads. The data packets across cluster heads and the sink are routed via a Jaya algorithm. Based on average remaining energy, number of active nodes, number of nodes that have failed or have been removed from the network, and overall network throughput, this combined clustering and routing method's quality has been assessed. The integrative clustering and routing protocol based on the flower pollination algorithm and Jaya algorithm described here exhibit considerable improvements over the current state-of-the-art. The network throughput and the number of the alive node are essential statistics for evaluating IoT in which battery-powered devices periodically acquire surroundings data and transmit gathered samples to a base station. The proposed strategy improved network throughput and the number of dead nodes by at least 14% and 18%, respectively. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.eninfo:eu-repo/semantics/closedAccessClusteringFlower pollination optimizationInternet of thingsJaya algorithmNetwork lifespanPopulation-based algorithmClustering algorithmsPower management (telecommunication)Routing algorithmsRouting protocolsClustering protocolClusteringsFlower pollination optimizationJaya algorithmLifespansNetwork lifespanNetwork throughputOptimisationsPopulation-based algorithmRouting problemsInternet of thingsAn Energy-Aware Scheme for Solving the Routing Problem in the Internet of Things Based on Jaya and Flower Pollination AlgorithmsArticle113631137281410.1007/s12652-023-04650-52-s2.0-85161258962Q1