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To avoid this situation, the authors proposed an optimal artificial bee colony algorithm-based Unmanned Aerial Vehicle (UAV) routing algorithm for efficient data communication between doctors and patients. This proposed method worked in three stages.

In recent decades, wireless body area networks have played an important role in health care applications. It facilitates the transmission of the patients' health data analysis report to the appropriate doctors.

In the first phase, biological sensors are connected to the human body via a controller node and collected data is transmitted via Bluetooth to the Personal Device Assistant (PDA). In the second phase, collected data will be transmitted via the Internet of things using an artificial bee colony algorithm. The second aids in determining the best route. In the third phase, unmanned aerial vehicles will use the best path to send collected data to doctors, caregivers, ambulances and cloud storage servers.

The simulation results show that the network's performance is superior when compared to existing approaches. The proposed algorithm achieves a high throughput, a lower delay, a higher link rate and a higher delivery rate.

The purpose of this paper is to propose the basis for the unification of unmanned aerial vehicle (UAV) group control protocols for the fast deployment of communication network on territories unsuitable for stationary nodes placement.

The paper proposes the application of active data (AD) conception in which the data exist in a form of executable code allowing data packets to control its own propagation through network. The implementation is illustrated for some scenarios of UAV data communication network deployment, i.e., transmission of the AD using navigation functions and dynamic reconfiguration of the nodes.

The conception of AD expands the range of possible UAV group operations due to on-the-fly adaptation abilities to changes in existing or forthcoming group behavior protocols. This allows the real-time change of data transmission formats, frequency ranges, modulation types, radio network topologies which, in turn, provides the ability to dynamically form the special data transmission networks from a general purpose device temporarily reconfiguring them for data transmission task between transmitter and receiver beyond radio visibility range.

The paper includes use cases for some situation of UAV data communication network deployment.

The paper aims to expand the UAV group control principles by implementing by rapid adaptation to changes in existing or forthcoming group behavior protocols.

The paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, this paper aims to propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the system to distribute to solve the problem of control and communication failure at the same time.

In the paper, the authors propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network-integrated system.

The results show that the integrated system has good robustness and fault tolerance performance indicators for flight control and wireless signal transmission when confronted with external disturbances, internal actuator failures and wireless network associated failures and the flight control curve of the quadrotor unmanned aerial vehicle (UAV) is generally smooth and stable, even if it encounters external disturbances and actuator failures, its fault tolerance performance is very good. Then in the range of 400–800 m wireless communication distance, the success rate of wireless signal loop transmission is stable at 80%–100% and the performance is at least relatively improved by 158.823%.

This paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, based on the robust fault-tolerant control algorithm, the authors propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the system and through the Riccati equation and linear matrix inequation method, the designed distributed robust H_∞ adaptive fault-tolerant controller further optimizes the fault suppression factor γ, so as to break through the limitation of only one Lyapunov matrix for different fault modes to distribute to solve the problem of control and communication failure at the same time.

Flying ad hoc networks (FANETs) have a major effect in various areas such as civil projects and smart cities. The facilities of installation and low cost of unmanned aerial vehicles (UAVs) have created a new challenge for researchers. Cluster head (CH) selection and load balancing between the CH are the most critical issues in the FANETs. For CH selection and load balancing in FANETs, this study used efficient clustering to address both problems and overcome these challenges. This paper aims to propose a novel CH selection and load balancing scheme to solve the low energy consumption and low latency in the FANET system.

This paper tried to select the CH and load balancing with the help of low-energy adaptive clustering hierarchy (LEACH) algorithm and bat algorithm (BA). Load balancing and CH selection are NP-hard problems, so the metaheuristic algorithms can be the best answer for these issues. In the LEACH algorithm, UAVs randomly generate numerical, and these numbers are sorted according to those values. To use the load balancing, the threshold of CH has to be considered; if the threshold is less than 0.7, the BA starts working and begins to find new CH according to the emitted pulses.

The proposed method compares with three algorithms, called bio-inspired clustering scheme FANETs, Grey wolf optimization and ant colony optimization in the NS3 simulator. The proposed algorithm has a good efficiency with respect to the network lifetime, energy consumption and cluster building time.

This study aims to extend the UAV group control concepts to include CH selection and load balancing to improve UAV energy consumption and low latency.

In the final step, the trust model is applied to the on-demand federated multipath distance vector routing protocol (AOMDV) to introduce path trust as a foundation for routing selection in the route discovery phase, construct a trusted path, and implement a path warning mechanism to detect malicious nodes in the route maintenance phase, respectively.

A trust-based on-demand multipath distance vector routing protocol is being developed to address the problem of flying ad-hoc network being subjected to internal attacks and experiencing frequent connection interruptions. Following the construction of the node trust assessment model and the presentation of trust evaluation criteria, the data packet forwarding rate, trusted interaction degree and detection packet receipt rate are discussed. In the next step, the direct trust degree of the adaptive fuzzy trust aggregation network compute node is constructed. After then, rely on the indirect trust degree of neighbouring nodes to calculate the trust degree of the node in the network. Design a trust fluctuation penalty mechanism, as a second step, to defend against the switch attack in the trust model.

When compared to the lightweight trust-enhanced routing protocol (TEAOMDV), it significantly improves the data packet delivery rate and throughput of the network significantly.

Additionally, it reduces the amount of routing overhead and the average end-to-end delay.

This paper aims to present an approach for a bio‐inspired decentralization topology control mechanism, called force‐based genetic algorithm (FGA), where a genetic algorithm (GA) is run by each holonomic autonomous vehicle (HAV) in a mobile ad hoc network (MANET) as software agent to achieve a uniform spread of HAVs and to provide a fully connected network over an unknown geographical terrain. An HAV runs its own FGA to decide its next movement direction and speed based on local neighborhood information, such as obstacles and the number of neighbors, without a centralized control unit or global knowledge.

The objective function used in FGA is inspired by the equilibrium of the molecules in physics where each molecule tries to be in the balanced position to spend minimum energy to maintain its position. In this approach, a virtual force is assumed to be applied by the neighboring HAVs to a given HAV. At equilibrium, the aggregate virtual force applied to an HAV by its neighbors should sum up to zero. If the aggregate virtual force is not zero, it is used as a fitness value for the HAV. The value of this virtual force depends on the number of neighbors within the communication range of R_com and the distance among them. Each chromosome in our GA‐based framework is composed of speed and movement direction. The FGA is independently run by each HAV as a topology control mechanism and only utilizes information from neighbors and local terrain to make movement and speed decisions to converge towards a uniform distribution of HAVs. The authors developed an analytical model, simulation software and several testbeds to study the convergence properties of the FGA.

The paper finds that coverage‐centric, bio‐inspired, mobile node deployment algorithm ensures effective sensing coverage for each mobile node after initial deployment. The FGA is also an energy‐aware self‐organization framework since it reduces energy consumption by eliminating unnecessary excessive movements. Fault‐tolerance is another important feature of the GA‐based approach since the FGA is resilient to losses and malfunctions of HAVs. Furthermore, the analytical results show that the authors' bio‐inspired approach is effective in terms of convergence speed and area coverage uniformity. As seen from the experimental results, the FGA delivers promising results for uniform autonomous mobile node distribution over an unknown geographical terrain.

The proposed decentralized and bio‐inspired approach for autonomous mobile nodes can be used as a real‐time topology control mechanism for commercial and military applications since it adapts to local environment rapidly but does not require global network knowledge.

This paper aims to present a comprehensive review in major research areas of unmanned air vehicles (UAVs) navigation, i.e. three degree-of-freedom (3D) path planning, routing algorithm and routing protocols. The paper is further aimed to provide a meaningful comparison among these algorithms and methods and also intend to find the best ones for a particular application.

The major UAV navigation research areas are further classified into different categories based on methods and models. Each category is discussed in detail with updated research work done in that very domain. Performance evaluation criteria are defined separately for each category. Based on these criteria and research challenges, research questions are also proposed in this work and answered in discussion according to the presented literature review.

The research has found that conventional and node-based algorithms are a popular choice for path planning. Similarly, the graph-based methods are preferred for route planning and hybrid routing protocols are proved better in providing performance. The research has also found promising areas for future research directions, i.e. critical link method for UAV path planning and queuing theory as a routing algorithm for large UAV networks.

The proposed work is a first attempt to provide a comprehensive study on all research aspects of UAV navigation. In addition, a comparison of these methods, algorithms and techniques based on standard performance criteria is also presented the very first time.

This paper aims to find methods to enhance position estimates for mobile terminals by cooperating with each other.

The main methods used are, on the one hand, mathematical modelling of the system, drone mobility, communication and positioning errors, and on the other hand, detailed discrete event simulation, which the author uses to evaluate the positioning errors. In the simulation runs, important parameters like signal speed, terminal velocity, area size and error correlation were varied. The author details the influence of these parameters on the theoretically possible error enhancement with respect to the traditional non-cooperative method.

Simulation results show that using cooperation is useful and can indeed significantly enhance the accuracy of position estimates, even in difficult situations. However, there are limits and the accuracy cannot always be enhanced.

Future research might use more sophisticated processing methods to further enhance position estimates. Limitations are given by the use of discrete time models in an inherently continuous system. Discretization errors are, however, kept low by using small time steps.

It has been shown that the positioning of drone swarms can be significantly enhanced once drones cooperate with each other. This might improve maneuverability of drones in all situations where drone swarms are used.

It has been proven by using simulation that cooperative positioning can yield positioning enhancements, even in difficult situations, when using wireless communication. In this light, future research can come up with practical implementations of such a cooperative approach.

While the use of long-endurance remotely piloted aircraft systems (LE-RPAS) is frequently associated with military operations, their core capabilities of long-range, low-cost and high-quality optics and communications systems have considerable potential benefit in supporting the work of humanitarian logisticians. The purpose of this paper is, therefore, to demonstrate how LE-RPAS could be used to improve the logistic response to a rapid onset disaster.

Using the response to the Cyclone Pam that struck Vanuatu in March 2015 as an example, this paper provides an overview of how LE-RPAS could be used to support the post-disaster needs assessment and subsequent response processes. In addition, it provides a high-level route map to develop the people, process and technology requirements that would support the operational deployment of the LE-RPAS capabilities.

On the basis of the analysis of the published literature and the resultant assessment of the benefits of LE-RPAS to support humanitarian logistic (HL) operations, it is concluded that a formal “proof of concept” trial should be undertaken, and the results be made available to the humanitarian community.

This paper is conceptual in nature, but has been developed through an analysis of the literature relating to remotely piloted aircraft systems (RPAS) and HLs. A route map through which the paper’s conclusions can be validated is also offered.

LE-RPAS have great potential to provide a swifter understanding of the impact of a disaster, particularly those where the location is remote from the main centres of population. This would allow the affected country’s National Disaster Management Organisation, together with those of supporting countries, to react more efficiently and effectively. In particular, it would allow a swifter transition from a “guess-based” push approach to one that more accurately reflects the disaster’s impact – i.e. a pull-based logistic response.

Given the military genesis of RPAS, it will be important to ensure that those engaged in their operation are sensitive to the implications of this. In particular, it will be essential to ensure that any humanitarian operations involving RPAS are undertaken in an ethical way that respects, for example, the privacy and safety of the affected population.

While there is some emerging discussion on the humanitarian-related use of RPAS in the literature, this generally reflects the operation of small aircraft with limited range and payload capabilities. Useful though such RPAS unquestionably are, this paper expands the discussion of how such systems can support the humanitarian logistician by considering the benefits and challenges of operating long-endurance aircraft.