Unmanned aerial vehicles (UAVs) have seen remarkable improvements in their flight capabilities and computational power. Their applications span various domains, such as agriculture, military, and communications. To improve communication quality and coverage in UAV-enabled systems, understanding effective placement techniques is crucial. While research has explored optimal UAV placement in two dimensions, there is a need for a comprehensive three-dimensional (3D) analysis, particularly for resource optimization. This article presents a systematic mapping study on 3D placement in UAV-enabled communication systems, incorporating a threat analysis for the reliability of the results. It provides valuable insights for future research on 3D placement optimization techniques, specifically examining optimization objectives, model system features, problem types, and solution strategies. Our research reveals, on one hand, an emphasis on optimizing data rate throughput, power transmission, and ground coverage, and a predominant use of large-scale fading in the air-to-ground channel model; on the other hand, heuristic algorithms prevail as the solution strategy. Moreover, we identify gaps in achieving critical objectives such as the probability of outage, deployment costs, quality of experience, and spectrum optimization. This highlights the need for further exploration in the formulation aspects of the system, which includes small-scale fading, access techniques, and interference management.

Ensuring reliable communication in remote or disaster-affected areas is a technical challenge due to unplanned deployment and mobilization, meaning placement difficulties and high operation costs of conventional telecommunications infrastructures. To address this problem, unmanned aerial vehicles (UAVs) have emerged as an excellent alternative to provide quick connectivity in remote or disaster-affected regions at a reasonable cost. However, the limited battery autonomy of UAVs restricts their flight service time. This paper proposes a communication system based on a tethered UAV (T-UAV) capable of continuous operation through a wired power network connected to a ground station. The communications system is based on low-cost devices, such as Raspberry Pi platforms, and offers wireless IP telephony services, providing high-quality and reliable communication. Experimental tests assessed power consumption, UAV stability, and data transmission performance. Our results prove that the T-UAV, based on a quadcopter drone, operates stably at 16 V and 20 A, ensuring consistent VoIP communications at a height of 10 m with low latency. These experimental findings underscore the potential of T-UAVs as cost-effective alternatives for extending or providing communication networks in remote regions, emergency scenarios, or underserved areas.

Unmanned Aerial Vehicles (UAVs) equipped with communication technologies have gained significant attention as a promising solution for providing wireless connectivity in remote, disaster-stricken areas lacking communication infrastructure. However, enabling UAVs to provide communications (e.g., UAVs acting as flying base stations) in real scenarios requires the integration of various technologies and algorithms. In particular 3D path planning algorithms are crucial in determining the optimal path free of obstacles so that UAVs in isolation or forming networks can provide wireless coverage in a specific region. Considering that most of the existing proposals in the literature only address path planning in a 2D environment, this paper systematically studies existing path-planning solutions in UAVs in a 3D environment in which optimization models (optimal and heuristics) have been applied. This paper analyzes 37 articles selected from 631 documents from a search in the Scopus database. This paper also presents an overview of UAV-enabled communications systems, the research questions, and the methodology for the systematic mapping study. In the end, this paper provides information about the objectives to be minimized or maximized, the optimization variables used, and the algorithmic strategies employed to solve the 3D path planning problem.

Currently, the Message Queuing Telemetry Transport for Sensor Networks (MQTT - SN) protocol has been implemented in operating systems such as TinyOS and Contiki to operate above the network layer, in sensor nodes with low processing capacity, powered by batteries and operating in various topologies. However, minimizing the processes at the node side is necessary to make the MQTT - SN protocol applicable in wireless sensor networks (WSNs) with large-scale linear structures. In this context, this paper presents the development of the MQTT-SN protocol’s finite state machine (FSM) for its operation over IEEE 802.15.4 in linear topologies. For this purpose, an FSM for each of the twelve procedures indicated in the MQTT-SN specification is obtained. Furthermore, each of the FSMs is represented using the specification and description language, and the characteristics of the IEEE 802.15.4 protocol and the sensor node are considered. Through simulation and the exchange of messages between nodes, the operation of the FSMs is verified. Subsequently, implementing the FSMs in WSNs allows for validating the deployment of the MQTT-SN protocol in linear topologies.

Today’s software-defined networking (SDN) applications have many challenges. Its main applications are focused on networks with nodes with high processing capacity. Applying SDN technology in nodes operating on batteries with limited computing capabilities is challenging. In this context, this paper proposes SDN-enabled algorithms for the remote configuration of the default route to be applied in multi-hop wireless sensor networks (WSNs) with tree-type topology using the IEEE 802.15.4 protocol. The routing algorithm to define the default route of each node is executed in an SDN-enabled WSN controller (SDWSN). The SDWSN controller receives information on the state of the network, executes the Djikstra or Kruskal algorithms, and configures the default route of the nodes remotely. The best route selection is based on the battery level of the nodes and the distance between them. The results show that using network protocols to configure the nodes remotely is unnecessary.

In recent years, virtualizing network servicesand functions has enabled optimizing hardware resources onresource-constrained devices, such as CPU, memory, and storage.Traditional virtualization is achieved through virtual machinesusing a layer known as a hypervisor. While this form of virtualization offers advantages such as scalability and portability, it has disadvantages in terms of performance compared to non-virtualized deployments. In this context, alternative virtualization technologies like containers allow virtualization on the same physical infrastructure, improving overall performance, portability, and service scalability. This paper implements the deployment of network services on the Raspberry Pi development platform, which has limited resources. This is achieved through a multi-container virtualization solution using the Docker Compose tool, based on Docker containerization technology. Finally, a performance analysis of the implemented virtualization solution is conducted in terms of resource utilization by each service.