# A Novel SDWSN-Based Testbed for IoT Smart Applications  
Department of Electrical and Electronic Engineering, Auckland University of Technology (AUT), Auckland 1010, New Zealand; [EMAIL_ADDRESS]  
Department of Electrical and Electronic Engineering, Auckland University of Technology (AUT), Auckland 1010, New Zealand; duaa.alhamid@aut. of software-defined wireless sensor networks (SDWSN), in which WSN functions are soft-warized and integrated into the network. The three core functionalities are represented by the terms \"leaf sensor node\", \"router node\", and \"IoT gateway node\", which can be modelled and tested on a virtual platform before physical deployment [6]. Herein, cloud-based virtualization is used to develop and provide specified functional configuration parameters to physical nodes. As a result, the cloud can assist with performance analysis via the virtual unit, where possible reorchestration of network behavior can be deployed and tested prior to real-world implementation, paving the way for the cyber-physical system [7; 8; 9]. This paper intends to focus on generic and adaptive testbed scenarios that can be used in a variety of advanced IoT applications. Herein, we shed more light on the subtleties of general design features of the IoT architecture, where a software-based virtual model can support physical network configuration prior to hardware implementation. The virtual platform represented by the Contiki Cooja network simulator also supports the softwarization concept utilized in this paper by offering the software specifications of the WSN nodes. Furthermore, it offers a network testing environment prior to actual network implementation using Texas Instruments CC2538 (TI CC2538) hardware. Herein, the Contiki firmware is used with both the Cooja tool and the TI CC2538. Mainly, in this paper, we aim to highlight and cover the components involved in the physical network (i.e., testbed) for any form of application. Furthermore, the paper explores use cases for dynamic and stationary networks, as well as how the suggested testbed could support various applications. The physical network implementation is evaluated in this paper as based on the suggested use cases wherein a virtual model is built and tested prior to hardware implementation. To examine the validity of having a virtual model testing in advance, virtual and physical network metrics such as network capacity and performance measures such as packet loss are employed. The proposed system looks into the design from the perspective of virtual and physical network parameters to offer an attempt towards interoperability. The main contributions of this work are summarized as follows:  
* Applying the concepts of \"SDWSN\" and \"virtualization\" to dynamic and stationary networks for various IoT applications such as vehicular networks and environmental monitoring systems. Such networks can be designed and tested on a virtual platform with a variety of functional capabilities to offer network flexibility. A network with nodes that can act as leaf and/or gateway functions, for example, can support the network in rapidly responding to any event through the multiple functions embedded in the nodes. * Proposing a physical testbed with hardware components that use the same virtual network codes. The technique is a cost-effective solution since it takes advantage of virtual testing to test, evaluate, and recover from networks failures. * The key components for the leaf node and the coordinator node (i.e., router or cluster head) such as the communication rate are discussed, mirroring the core aspects employed in the virtual platform. This interactive collaboration between virtualization and physical implementation can support the efficient operation of networks such as dynamic networks. This paper delves into the aspects of physical network implementation design, including the number of nodes, sensing variables, and mobility.