Energy-efficient modeling in WSN-assisted IoT based on software defined network

Abstract

Consolidating the Internet of Things (IoT) and Software Defined Networks (SDN) has been a great concern among researchers. In IoT, Wireless Sensor Network (WSN) is important communication component. Due to the large volume of data generated in IoT and the limitations of WSN, load distribution in these networks is a serious challenge. The Base Station (BS) in these networks may experience a lot of delay due to high processing. Also, data of applications in these networks must inform to users with the lowest delay. Therefore, in addition to load distribution, reducing response time is also one of the factors that must be considered. Therefore, load distribution among BS’s seems to be crucial Considering several BSs and their relationships with the network nodes and preventing them from overloading through load distribution may solve the problem. This can be implemented by applying the common nodes that belong to several BSs. That is, to reduce the load of the overloaded BS, the common node in the cluster corresponding to BS and the other BSs is selected to send common node load to the other BSs. The common node is selected through the load-balancing node-finder algorithm. Load transfer is done through the forwarding node, which is specified in the proposed routing process. The Colored Petri Nets (CPN) s are applied to implement the proposed method. Here, queue length, residual energy, nodes, BSs, and delay time are simulated in three scenarios. The results show that most of the nodes are applied in the proposed algorithm to implement load balancing between the nodes and BSs. The results show the proposed SDN-based algorithm reduces the residual energy to 18%, the queue length to 9.5%, and the delay to 35%. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.