Unmanned Aerial Vehicle (UAV) deployment and placement are largely dependent upon the available energy, feasible scenario, and secure network. The feasible placement of UAV nodes to cover the cellular networks need optimal altitude. The under or over-estimation of nodes’ air timing leads to of resource waste or inefficiency of the mission. Multiple factors influence the estimation of air timing, but the majority of the literature concentrates only on flying time. Some other factors also degrade network performance, such as unauthorized access to UAV nodes. In this paper, the UAV coverage issue is considered, and a Coverage Area Decision Model for UAV-BS is proposed. The proposed solution is designed for cellular network coverage by using UAV nodes that are controlled and managed for reallocation, which will be able to change position per requirements. The proposed solution is evaluated and tested in simulation in terms of its performance. The proposed solution achieved better results in terms of placement in the network. The simulation results indicated high performance in terms of high packet delivery, less delay, less overhead, and better malicious node detection.

Wireless Sensor Networks have risen as a highly promising technology suitable for precision agriculture implementations, enabling efficient monitoring and control of agricultural processes. In precision agriculture, accurate and synchronized data collection is crucial for effective analysis and decision making. Using principles of information theory, we can define conditions and parameters that influence the efficient transmission and processing of information. Existing technologies have limitations in maintaining consistent time references, handling node failures, and unreliable communication links, leading to inaccurate data readings. Reliable data storage is demanding now-a-days for storing data on local monitoring station as well as in online live server. Sometime internet is not working properly due to congestion and there is frequent packet loss. Current solutions often synchronize records based on database timestamps, leading to record duplication and waste storage. Both databases synchronize each other after internet restoration. By providing synchronization among nodes and data, accuracy and storage will be saved in IoT based WSNs for precision agriculture applications. A prototype Node-MCU internal memory is used as a resource for achieving data synchronization. This proposed work generates record ID from Node MCU EEPROM which helps in records synchronization if there is any packet loss at the local server or at the online server to maintain synchronization accuracy despite unreliable communication links. Experiment shows that for a particular duration Node MCU generated 2364 packets and packet loss at local server was 08 and at online server was 174 packets. Results shows that after synchronization 99.87% packets were synchronized. Using previous technique of timestamp, the redundancy was 70% which reduced to 0% using our proposed technique.

Software-defined networking (SDN) is an evolving technology providing proper segregation between the control part and data-forwarding domain of network devices. The expansion of the Internet of Things (IoTs) and embedded mobile devices increases the volume of traffic at the network backbone and causes processing costs in the control plane. This directly affects the Ternary Content Addressable Memory (TCAM) of the switches because insufficient space makes it more challenging to manage the flow-entries. In this situation, providing services to specific users who newly authenticate after the successful handoff from the previous SDN domain is challenging. This paper proposes a method for implanting the users’ primary domain’s flow-rules in the serving SDN domain. As the TCAM is already suffering from a short space, it is hard to handle the flow-tables of multiple SDN domains in limited TCAM storage. The SDN-based Integration of the Interdomain Flow-rule in the SDN (IIF-SDN) scheme maximizes the proficiency of the switches by effectively storing flow-table and flow-entries. The effectiveness of the proposed scheme is benchmarked with proactive and reactive SDN approaches.