Mohammadi Ramin, Akleylek Sedat, Ghaffari Ali
Ondokuz Mayis University, Department of Computational Sciences, Samsun, Türkiye.
Department of Computer Engineering, Ondokuz Mayis University Samsun, Samsun, Türkiye.
PeerJ Comput Sci. 2023 Jul 10;9:e1424. doi: 10.7717/peerj-cs.1424. eCollection 2023.
The Internet of Things (IoT) includes billions of different devices and various applications that generate a huge amount of data. Due to inherent resource limitations, reliable and robust data transmission for a huge number of heterogenous devices is one of the most critical issues for IoT. Therefore, cluster-based data transmission is appropriate for IoT applications as it promotes network lifetime and scalability. On the other hand, Software Defined Network (SDN) architecture improves flexibility and makes the IoT respond appropriately to the heterogeneity. This article proposes an SDN-based efficient clustering scheme for IoT using the Improved Sailfish optimization (ISFO) algorithm. In the proposed model, clustering of IoT devices is performed using the ISFO model and the model is installed on the SDN controller to manage the Cluster Head (CH) nodes of IoT devices. The performance evaluation of the proposed model was performed based on two scenarios with 150 and 300 nodes. The results show that for 150 nodes ISFO model in comparison with LEACH, LEACH-E reduced energy consumption by about 21.42% and 17.28%. For 300 ISFO nodes compared to LEACH, LEACH-E reduced energy consumption by about 37.84% and 27.23%.
物联网（IoT）包含数十亿种不同的设备和各种应用程序，它们会生成海量数据。由于固有的资源限制，为大量异构设备进行可靠且稳健的数据传输是物联网面临的最关键问题之一。因此，基于集群的数据传输适用于物联网应用，因为它能延长网络寿命并提高可扩展性。另一方面，软件定义网络（SDN）架构提高了灵活性，并使物联网能够对异构性做出适当响应。本文提出了一种基于SDN的物联网高效聚类方案，该方案使用改进的旗鱼优化（ISFO）算法。在所提出的模型中，使用ISFO模型对物联网设备进行聚类，并将该模型安装在SDN控制器上，以管理物联网设备的簇头（CH）节点。基于具有150个和300个节点的两种场景对所提出模型进行了性能评估。结果表明，对于150个节点，与LEACH、LEACH-E相比，ISFO模型分别将能耗降低了约21.42%和17.28%。对于300个节点，与LEACH、LEACH-E相比，ISFO模型分别将能耗降低了约37.84%和27.23%。
