In modern times, the Internet of Things (IoT) is having a major impact on agriculture. Risk and security parameters are always linked when researching, developing, implementing and deploying IoT-based devices. It is a myth that security does not play a major role in IoT applications in agriculture. Data accuracy and availability is a high-priority requirement for farmers who help achieve high yields. A secure IoT network requires a situational approach, often referred to as dynamic security. An advanced security approach to improving IoT security is adaptive security, a cybersecurity-based approach. The lack of security in a smart farming environment is a very important factor for agricultural growth. In this study, we introduce IoT together with adaptive security operations and integrate it into a smart farming environment. We propose an evaluation framework that can be applied to diverse smart farming environments. Several scenarios of an agricultural environment with smart devices and sensors are described for execution. Storylines with real-time environments are then derived from these scenarios to extend and incorporate adaptive security frameworks and scenarios in IoT-based agriculture.

IEEE 802.11 wireless LAN is proliferating since the increased trend in the wireless network utilization on mobile devices. Accuracy, fast content delivery, and reliable mobility support are essential features of any network to support the changing trend in a wireless network. However, traditional architectures in wireless LAN (WLANs or WiFi) always endured from challenges such as the provision of consistent mobility, real-time packet flow, and seamless handoff. Generally, most of the WLAN only relies on signal strength for handoff which is not sufficient enough for fair selection of an access point (AP) and therefore causes imperfect performance of the network. We present a novel mobility management scheme for WLANs to deal with the mobility management issues, and load balancing by software-defined network (SDN) and network function virtualization (NFV) technologies. The proposed scheme is based on logical AP (LAP) that keeps a connection with the user/mobile terminal (MT) during handoff triggered by either the user or the SDN controller for seamless mobility. It also involves the current state of each AP in addition to traditional parameters of WLAN. We implemented the proposed scheme on a real testbed in a WLAN environment. The evaluation results authenticate that our proposed scheme provides robust handover without throughput degradation and load imbalance among adjacent APs, and allocates the best AP in the neighboring region. Moreover, our proposed scheme is feasible to implement since it did not require any modification at the mobile terminal.

The smart home is a field that uses smart devices and gadgets to automate tasks and operations in the house, and it is expected that this study subject will become a focal point in future civilizations. The adoption of smart home services faces significant obstacles in terms of reliability and stability. The Software Defined Networking (SDN) paradigm offers up novel approaches and trends to embrace smart technologies to tackle the issues of smart homes. To avoid accidents, we developed a vertical SDN-based multi-level structure consisting of two controllers with a parent-child connection. It enables smart homes to make optimal use of current services while also providing new services to smart homes and buildings, opening the path for future smart services. In addition, we created an Application Programming Interface (API) for the smart home to make it easier to use current services and pave the path for future smart services. We designed numerous jobs depending on their categorization to give smart services, which is beneficial for smart homes. Local topologies, cloud topologies, and cloud-local topologies have all been compared in the evaluation section. The performance of POX, NOX, and Flood Light controllers is measured using three performance metrics: mean throughput, Round-Trip Time (RTT), and packet loss across all three topologies. Our findings revealed that the cloud-local topology had the lowest packet loss ratio of 1.4%, while the local and cloud topologies had 1.9% and 2.3%, respectively.