## 1 Introduction  
Wireless sensor networks (WSNs) are a fundamental factor in the growth and development of new applications for IoT networks [1]. WSNs allow for the development of monitoring applications associated with smart cities, factories, and surveillance systems [2; 3]. Implementing multi-hop wireless sensor networks presents a significant challenge due to the energy consumption of the relay nodes and the end-to-end delay [4]. Software-defined networking (SDN) is an architecture proposed for networks in which the processes carried out in the network are grouped into two planes: (i) the control plane that determines the traffic routes and (ii) the data plane that forwards the traffic packets [5]. WSNs are different from the conventional networks that SDN was initially designed for. The use of SDN in WSNs is known as software-defined wireless sensor networking (SDWSN), where all the processes a node performs are executed centrally in the controller [6]. WSNs have limited resources, so developing SDWSNs becomes a challenge due to inherent restrictions in the WSN architecture. Integrating WSN and SDN lies in pursuing enhanced network efficiency, reducing processing delays, and following our previous works [7; 8] in which the network layer performance uses solely link layer information. The SDN paradigm facilitates implementation in WSN due to the low computing capacity of the nodes. The calculation limitations of the nodes of a WSN generate delay times for processing when routing algorithms are executed [9] to find the default route of the nodes. This constraint hinders the application of internet network architecture to WSNs, primarily due to elevated processing delays. Various network architectures are presently employed in developing WSN applications [10], with ongoing adaptation and development of protocolsfor this network type. Consequently, addressing the challenge of minimizing processing delays at WSN nodes remains a significant concern. In addition, the energy consumption for processing affects the lifetime of the nodes because they run on batteries [11]. The 6 LowPAN protocol allows information from the nodes to reach the controller and the controller to configure the nodes remotely [12]. This protocol, derived from IPv6 for WSN, faces extended convergence times in multi-hop scenarios. Employing SDN technology in an SDWSN network facilitates the utilization of a controller for configuring the network, ensuring swift convergence times for the default route of the nodes. The execution of the routing algorithm is not a problem due to the processing capabilities of the controller; however, minimizing the transmission delays to and from the controller with the nodes is a challenge due to the network protocols used in WSN. Routing control between the sensor node and the gateway in a multi-hop topology using SDWSN controllers is critical because it must be adequate, adaptable, and reliable. Several architectures are currently operating for WSNs [10]. SDN allows us to have a unique architecture, resolve processing delays, minimize node energy consumption, and facilitate new application creation. In an SDN, routing management performed by the controller allows for higher QoS and longer network life. Failures in WSNs frequently occur due to connectivity disruptions, power shortages, changes in environmental conditions, and other disruptive events. Therefore, the network must be configured, managed, and maintained for self-healing and fault tolerance. Using a controller results in a robust feature that allows the WSN to provide useful information even when some failed nodes and links modify the network topology. Routing management in the WSN must support node mobility, resulting in topology changes, including handling unreliable wireless links.