Performance evaluation testbed for emerging relaying and coding algorithms in Flying Ad Hoc Networks

In this work, a group of mechanisms are exposed to provide quality of experience in flying ad hoc networks using a swarm of drones in a natural disaster service. End-to-end video traffic was analyzed. The metrics used to experimentally measure QoE/QoS are: delay, jitter and packet loss. The experience quality was evaluated before the disaster (C00), at the moment (B00) and after the disaster (I00). The methodology used to perform the design was experimental, and the NS simulator was used to evaluate the behavior of the swarm of drones connected through a flying ad hoc network. To perform data analysis, treatment and repetitions related to video traffic, the response surface methodology (MSR) was used, which is a set of mathematical techniques in order to optimize the obtained responses. The composite core design (DCC) was also used as it was the best fit to our experiment due to its flexibility. Since the quality of the experience was evaluated at three moments, the quality of services was also analyzed with three metrics. The main contributions of the research are a mathematical model of the quality of the experience based on the quality of the service; an experiment design using the end-to-end NS simulator; a methodology for the mathematical and statistical analysis of the data obtained; an algorithm that allows, from service quality metrics, to obtain the quality of the experience for end-to-end video traffic; and a proposal for future work for data analysis in a physical environment and applied to the environmental sector.

In some complex applications, Flying Ad Hoc Network (FANET) can provide important support for multi UAV (Unmanned Aerial Vehicle) cooperation. In FANET each UAV is equivalent to a router, and the wireless link between them forms a network to achieve the purpose of relay communication. Throughput is an important network performance, and the position of UAV nodes affects it. In this paper, we analyze the influencing factors of FANET throughput with UAV position and terminator selection in first; Secondly we construct the mathematical model of throughput optimization of FANET; Thirdly we propose an algorithm based on genetic algorithm to optimize the position of UAV, and then maximize the throughput. Preparing for using genetic algorithm, we design the related details: Numbering Area, Determining the adjacency matrix and correlation matrix, determining the range of UAV node position movement. The key points of the genetic algorithm for FANET is proposed include the following aspects: coding and population initialization, fitness function, and chromosome replication/crossover/mutation and termination criteria. At last, Matlab is used to simulate the proposed algorithm from three aspects: performance, effect of Radius of Position Constraint (RPC) and effect of Radius of Particle Size (RPS). The results show that the throughput can reach the expected goal by controlling the UAV position, and the optimization speed is related to the RPC and RPS.

The advent of flying ad hoc networks (FANETs) has opened an opportunity to create new added-value services. Even though it is clear that these networks share common features with its predecessors, e.g., with mobile ad hoc networks and with vehicular ad hoc networks, there are several unique characteristics that make FANETs different. These distinctive features impose a series of guidelines to be considered for its successful deployment. Particularly, the use of FANETs for telecommunication services presents demanding challenges in terms of quality of service, energy efficiency, scalability, and adaptability. The proper use of models in research activities will undoubtedly assist to solve those challenges. Therefore, in this paper, we review mobility, positioning, and propagation models proposed for FANETs in the related scientific literature. A common limitation that affects these three topics is the lack of studies evaluating the influence that the unmanned aerial vehicles (UAV) may have in the on-board/embedded communication devices, usually just assuming isotropic or omnidirectional radiation patterns. For this reason, we also investigate in this work the radiation pattern of an 802.11 n/ac (WiFi) device embedded in a UAV working on both the 2.4 and 5 GHz bands. Our findings show that the impact of the UAV is not negligible, representing up to a 10 dB drop for some angles of the communication links.

An adaptive and multi-path greedy perimeter stateless routing protocol in flying ad hoc networks

In the last few years, a considerable amount of research effort has been put into creating networks of Unmanned Aerial Vehicles (UAVs). Flying Ad Hoc Networks (FANETs) and Internet of Drones (IoDs) are the result of such efforts. FANETs assume that the member UAV nodes belong to different users. However, in UAV networks that would find their applications in areas such as agriculture, environment monitoring, crowd surveillance and natural disaster situations, all UAVs would belong to the same organization, creating a private UAV network. The number of UAVs used in private UAV networks is relatively small compared to that of FANETs due to the cost. If the packet routing approaches designed for FANETs are used in such networks, the quality of video transmitted through the network will suffer. This is because, while there can be many neighbors for each UAV in a FANET, the movements of UAVs in a private UAV network may cause some UAVs not to have any neighbors. To overcome this problem, a UAV in such a network needs to be controlled differently and an appropriate method of selecting the next hop node is required. The new approach presented in this paper uses mathematical analysis to find the optimum next hop node in a private UAV network by reducing a global optimization problem to a local optimization problem at each UAV node along the path from the source to the destination. Once the best next hop node is found, the UAVs can be controlled accordingly.

Unmanned Aerial Vehicle (UAV) technology is being used increasingly for military and civilian purposes. The primary reason for this increase is that UAVs eliminate the risk to human life in difficult and dangerous missions, are cost effective, and easily are deployed. Developments in UAV technology and decreasing costs have increased UAV usage. However, when multiple UAVs are deployed, inter UAV communication becomes complicated. For this reason, communication in multi-UAV systems is the most important problem that needs to be solved. To enable communication among UAVs without infrastructure support, a Flying Ad Hoc Network (FANET) is used. A FANET provides UAVs to fly in tandem without colliding. To ensure coordinated flight, UAVs require the location information of other UAVs. In this study, we developed a common channel multi-token circulation protocol to share location information in multi-UAV systems that communicate using a FANET. The proposed method ensures that UAVs in multi-UAV systems know each other's coordinate information with minimum error.DOI: 10.5755/j01.eie.25.1.22738

The advancement of automated systems and their capabilities encourage the use of unmanned aerial vehicles (UAVs) to form ad hoc networks. Multi-UAV ad hoc networks are efficient and promising to complete the task, especially for perilous missions. A multi-UAV ad hoc network is also known as Flying Ad hoc Networks (FANETs). There are various issues required to be addressed before the effective use of UAVs to form a stable and reliable network. As UAVs collaborate and coordinate with each other to complete the mission, trust among the nodes (UAVs) is a crucial aspect. In this paper, a novel trust model has been proposed where the genetic algorithm is used to optimize the weights of various parameters to evaluate the direct trust values. Direct trust is aggregated with are commendation to compute final trust value of a node. Further, nodes are classified into various clusters and trust values of uncertain nodes undergo risk assessment. Based on risk assessment, nodes are included in the recommendation or discard list. Hence, malicious nodes are segregated from the network using the discard list. The experimental results show that the proposed model has better adaptability and accuracy to be considered for FANETs. More importantly, the proposed model achieves significant performance improvement too.

As there has been an advancement in avionic systems in recent years, the enactment of unmanned aerial vehicles (UAV) has upgraded. As compared to a single UAV system, multiple UAV systems can perform operations more inexpensively and efficiently. As a result, new technologies between user/control station and UAVs have been developed. FANET (Flying Ad-Hoc Network) is a subset of the MANET (Mobile Ad-Hoc Network) that includes UAVs. UAVs, simply called drones, are used for collecting sensitive data in real time. The security and privacy of these data are of priority importance. Therefore, to overcome the privacy and security threats problem and to make communication between the UAV and the user effective, a competent anonymous mutual authentication scheme is proposed in this work. There are several methodologies addressed in this work such as anonymous batch authentication in FANET which helps to authenticate a large group of drones at the same time, thus reducing the computational overhead. In addition, the integrity preservation technique helps to avoid message alteration during transmission. Moreover, the security investigation section discusses the resistance of the proposed work against different types of possible attacks. Finally, the proposed work is related to the prevailing schemes in terms of communication and computational cost and proves to be more efficient.

Among the technological advances, the use of Unmanned Aerial Vehicles (UAVs) saw an evolution in this last decade, their employment in civil applications, such as firefighting, disaster management, environmental monitoring and policing, is increased recently. The UAVs are connected with Ad- hoc modes like Mobile Ad-hoc Networks (MANETs) and Vehicular Ad-hoc Networks (VANETs), this is another innovation in the wireless network where requirements change largely from long-established networking systems. Furthermore, the cooperative work is required in both civil and military applications to accomplish intensive missions. Flying Ad-hoc Networks (FANETs) have been developed using techniques that assist the transmission of information in real-time. The high mobility and quick topology change in UAV networks caused the difficulty for specialists to insert routing in FANETs. Routing protocols have a useful role to improve the performance of these networks. This paper presents a comparison between the different dynamic routing protocols to attain the high quality of service using the NS3 simulator.

Admission control based on multiple criteria has always been a desirable feature for computer networks. In the past, we presented such a system, but it was based on a centralised decision mechanism, which by itself constitutes a significant limitation. Here, we describe a decentralised version of the initial admission control algorithm, while still keeping the multiple-criteria aspect, with each user being able to specify their Quality of Service (QoS) metrics at the level of the individual. Our scheme decides whether a new call should be allowed to enter the network based on measurements of the QoS metrics on each link of the network before and after the transmission of probe packets. The decision is based on a novel algebra of QoS metrics, inspired by Warshall's algorithm that searches whether there is a feasible path to accommodate the new flow without affecting the existing users. The decision is made at each source node individually, based on either only personal information or also on information exchange among the nodes that are involved. The performance of the algorithm is evaluated in terms of QoS throughout the lifetime of all connections. The experiments presented in this paper were conducted in an actual laboratory test-bed of realistic topology and under highly congested circumstances. The results are particularly encouraging.

Web services orchestrations conventionally employ exhaustive comparison of runtime quality of service (QoS) metrics for decision making. The ability to incorporate more complex mathematical packages are needed, especially in case of workflows for resource allocation and queuing systems. By modeling such optimization routines as service calls within orchestration specifications, techniques such as linear programming can be conveniently invoked by non-specialist workflow designers. Leveraging on previously developed QoS theory, we propose the use of a high-level flexible query procedure for embedding optimizations in languages such as Orc. The Optima site provides an extension to the sorting and pruning operations currently employed in Orc. Further, the lack of an objective technique for consolidating QoS metrics is a problem in identifying suitable cost functions. We employ the analytical hierarchy process (AHP) to generate a total ordering of QoS metrics across various domains. With constructs for ensuring consistency over subjective judgements, the AHP provides a suitable technique for producing objective cost functions. Using the Dell Supply Chain example, we demonstrate the feasibility of decision making through optimization routines, specially when the control flow is QoS dependent.KeywordsWeb ServicesQoSOptimizationOrcAHP

Flying Ad-hoc Networks (FANETs) have been employed in modern warfare for monitoring and reconnaissance to produce a healthy living environment for wildlife through multiple Unmanned Aerial Vehicles (UAVs). FANETs allow multiple UAVs to communicate in 3D space to establish an ad-hoc network. FANETs applications, among others, can deliver costeffective services to help future wildlife. However, adopting FANET's technology in wildlife monitoring is difficult due to its challenges in mobility, data routing, energy, and security considerations. Therefore, this paper aims to look at FANET's possible applications in wildlife Monitoring and the implications and issues that come with them.

Cloud systems are transforming the Information Technology trade by facultative the companies to provide admission to their structure and also software products to the membership foundation.Because of the vast range within the delivered Cloud solutions, from the customer's perspective of an aspect, it's emerged as troublesome to decide whose providers they need to utilize and then what's the thought of his or her option.Especially, employing suitable metrics is vital in assessing practices.Nevertheless, to the most popular of our knowledge, there's no methodical explanation relating to metrics for estimating Cloud products and services.QoS (Quality of Service) metrics playing an important role in selecting Cloud providers and also optimizing resource utilization efficiency.While many reports have got to devote to exploitation QoS metrics, relatively not much equipment supports the remark and investigation of QoS metrics of Cloud programs.To guarantee a specialized product is published, describing metrics for assessing the QoS might be an essential necessity.So, this text suggests various QoS metrics for service vendors, especially thinking about the consumer's worry.This article provides the metrics list may stand to help the future study and also assessment within the field of Cloud service's evaluation.

Flying Ad-Hoc Network (FANET) is a special type of Mobile Ad-Hoc Network (MANET) which consists of multiple networked Unmanned Aerial Vehicles (UAVs). Compared to traditional target search using a single UAV, multiple cooperative UAVs within a FANET have the potential to accomplish this work more efficiently, and multi-UAV cooperative target search has attracted increasing research attention in recent years. In this paper, we conduct a comprehensive investigation on efficient and accurate multi-UAV cooperative target search techniques. More specifically, we propose several adaptive mobility models and an innovative information fusion mechanism to improve the search efficiency. Meanwhile, to improve the search accuracy, we introduce a low-overhead decision-making mechanism to reduce chances for false target identifications. The simulation results show that the framework outperforms the baseline framework significantly in terms of both efficiency and accuracy. Our experiments also exhibit how individual mechanisms introduced in our work contribute to the improvements on search efficiency or accuracy, therefore providing more guidance for their adoption in practice.

This paper reports experimental results on self-organizing wireless networks carried by small flying robots. Flying ad hoc networks (FANETs) composed of small unmanned aerial vehicles (UAVs) are flexible, inexpensive and fast to deploy. This makes them a very attractive technology for many civilian and military applications. Due to the high mobility of the nodes, maintaining a communication link between the UAVs is a challenging task. The topology of these networks is more dynamic than that of typical mobile ad hoc networks (MANETs) and of typical vehicle ad hoc networks (VANETs). As a consequence, the existing routing protocols designed for MANETs partly fail in tracking network topology changes. In this work, we compare two different routing algorithms for ad hoc networks: optimized link-state routing (OLSR), and predictive-OLSR (P-OLSR). The latter is an OLSR extension that we designed for FANETs; it takes advantage of the GPS information available on board. To the best of our knowledge, P-OLSR is currently the only FANET-specific routing technique that has an available Linux implementation. We present results obtained by both Media Access Control (MAC) layer emulations and real-world experiments. In the experiments, we used a testbed composed of two autonomous fixed-wing UAVs and a node on the ground. Our experiments evaluate the link performance and the communication range, as well as the routing performance. Our emulation and experimental results show that P-OLSR significantly outperforms OLSR in routing in the presence of frequent network topology changes.