Cooperative data muling using a team of unmanned aerial vehicles

Philosophiae Doctor - PhDUnmanned Aerial Vehicles (UAVs) have recently o ered signi cant technological achievements. The advancement in related applications predicts an extended need for automated data muling by UAVs, to explore high risk places, ensure e ciency and reduce the cost of various products and services. Due to advances in technology, the actual UAVs are not as expensive as they once were. On the other hand, they are limited in their ight time especially if they have to use fuel. As a result, it has recently been proposed that they could be assisted by the ground static sensors which provide information of their surroundings. Then, the UAVs need only to provide actions depending on information received from the ground sensors. In addition, UAVs need to cooperate among themselves and work together with organised ground sensors to achieve an optimal coverage. The system to handle the cooperation of UAVs, together with the ground sensors, is still an interesting research topic which would bene t both rural and urban areas. In this thesis, an e cient ground sensor network for optimal UAVs coverage is rst proposed. This is done using a clustering scheme wherein, each cluster member transmits its sensor readings to its cluster head. A more e cient routing scheme for delivering readings to cluster head(s) for collection by UAVs is also proposed. Furthermore, airborne sensor deployment models are provided for e cient data collection from a unique sensor/target. The model proposed for this consists of a scheduling technique which manages the visitation of UAVs to target. Lastly, issues relating to the interplay between both types of sensor (airborne and ground/underground) networks are addressed by proposing the optimal UAVs task allocation models; which take caters for both the ground networking and aerial deployment. Existing network and tra c engineering techniques were adopted in order to handle the internetworking of the ground sensors. UAVs deployment is addressed by adopting Operational Research techniques including dynamic assignment and scheduling models. The proposed models were validated by simulations, experiments and in some cases, formal methods used to formalise and prove the correctness of key properties

Internet of Things: Least Interference Beaconing Algorithms

The emerging sensor networking applications are predicting the deployment of sensor devices in thousands of computing elements into multi-technology and multi-protocol platforms. Access to information will be available not only anytime and anywhere, but also using anything in a first-mile of the Internet referred to as the internet-of-things (IoT). The management of such a large-scale and heterogeneous network, would benefit from some of the traditional IP-based network management techniques such as load and energy balancing, which can be re-factored to achieve efficient routing of sensor network traffic. Research has shown that minimizing the path interference on nodes was necessary to improve traffic engineering in connection oriented networks. The same principle has been applied in past research in the context of the IoT to reveal that the least interference beaconing protocol (LIBP); a protocol derived from the least interference beaconing algorithm (LIBA) outperforms the Collection Tree Protocol (CTP) and Tiny OS Beaconing (ToB) protocol, in terms of energy efficiency and lifetime of the sensor network. However for the purpose of efficiency and accuracy, it is relevant, useful and critical to revisit or re-examine the LIBA algorithm in terms of correctness and investigate potential avenues for improvement. The main contributions of this research work are threefold. Firstly, we build upon formal methods to verify the correctness of the main principles underlying the LIBA, in terms of energy efficiency and interference minimization. The interference is here defined at each node by the number of routing paths carrying the sensor readings from the motes to the sink of the network that traverse the node. Our findings reveal the limitations in LIBA. Secondly, building upon these limitations, we propose two improvements to the algorithm: an algorithm called LIBA+ that improves the algorithm performance by keeping track of the energy usage of the sensor nodes, and a multi-sink version of the algorithm called LIBAMN that extends the algorithm to account for multiple sinks or gateways. These enhancements present preventive mechanisms to include in IoT platforms in order to improve traffic engineering, the security of network protocols and network stability. Lastly, we present analytical results, which reveal that the LIBA algorithm can be improved by more than 84% in terms of energy balancing. These results reveal that formal methods remain essential in the evaluation and performance improvement of wireless sensor network algorithms and protocols

Internet-of-Things in motion: A UAV coalition model for remote sensing in smart cities

Unmanned aerial vehicles (UAVs) or drones are increasingly used in cities to provide service tasks that are too dangerous, expensive or difficult for human beings. Drones are also used in cases where a task can be performed more economically and or more efficiently than if done by humans. These include remote sensing tasks where drones can be required to form coalitions by pooling their resources to meet the service requirements at different locations of interest in a city. During such coalition formation, finding the shortest path from a source to a location of interest is key to efficient service delivery. For fixed-wing UAVs, Dubins curves can be applied to find the shortest flight path. When a UAV flies to a location of interest, the angle or orientation of the UAV upon its arrival is often not important. In such a case, a simplified version of the Dubins curve consisting of two instead of three parts can be used. This paper proposes a novel model for UAV coalition and an algorithm derived from basic geometry that generates a path derived from the original Dubins curve for application in remote sensing missions of fixed-wing UAVs. The algorithm is tested by incorporating it into three cooperative coalition formation algorithms. The performance of the model is evaluated by varying the number of types of resources and the sensor ranges of the UAVs to reveal the relevance and practicality of the proposed model

Clustered data muling in the internet of things in motion

This paper considers a case where an Unmanned Aerial Vehicle (UAV) is used to monitor an area of interest. The UAV is assisted by a Sensor Network (SN), which is deployed in the area such as a smart city or smart village. The area being monitored has a reasonable size and hence may contain many sensors for efficient and accurate data collection. In this case, it would be expensive for one UAV to visit all the sensors; hence the need to partition the ground network into an optimum number of clusters with the objective of having the UAV visit only cluster heads (fewer sensors). In such a setting, the sensor readings (sensor data) would be sent to cluster heads where they are collected by the UAV upon its arrival. This paper proposes a clustering scheme that optimizes not only the sensor network energy usage, but also the energy used by the UAV to cover the area of interest. The computation of the number of optimal clusters in a dense and uniformly-distributed sensor network is proposed to complement the k-means clustering algorithm when used as a network engineering technique in hybrid UAV/terrestrial networks. Furthermore, for general networks, an efficient clustering model that caters for both orphan nodes and multi-layer optimization is proposed and analyzed through simulations using the city of Cape Town in South Africa as a smart city hybrid network engineering use-case

An Enhanced Heterogeneous Gateway-Based Energy-Aware Multi-Hop Routing Protocol for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) continue to provide essential services for various applications such as surveillance, data gathering, and data transmission from hazardous environments to safer destinations. This has been enhanced by the energy-efficient routing protocols that are mostly designed for such purposes. Gateway-based Energy-Aware Multi-hop Routing protocol (MGEAR) is one of the homogenous routing schemes that was recently designed to more efficiently reduce the energy consumption of distant nodes. However, it has been found that the protocol has a high energy consumption rate, lower stability period, and poorer data transmission to the Base station (BS) when it was deployed for a longer period of time. In this paper, an enhanced Heterogeneous Gateway-based Energy-Aware multi-hop routing protocol (HMGEAR) is proposed. The proposed routing scheme is based on the introduction of heterogeneous nodes in the existing scheme, selection of the head based on the residual energy, introduction of multi-hop communication strategy in all the regions of the network, and implementation of energy hole elimination technique. All these strategies are aiming at reducing energy consumption and extend the life of the network. Results show that the proposed routing scheme outperforms two existing ones in terms of stability period, throughputs, residual energy, and the lifetime of the network

Trajectory planing for cooperating unmanned aerial vehicles in the IoT

The use of Unmanned Aerial Vehicles (UAVs) in data transport has attracted a lot of attention and applications, as a modern traffic engineering technique used in data sensing, transport, and delivery to where infrastructure is available for its interpretation. Due to UAVs’ constraints such as limited power lifetime, it has been necessary to assist them with ground sensors to gather local data, which has to be transferred to UAVs upon visiting the sensors. The management of such ground sensor communication together with a team of flying UAVs constitutes an interesting data muling problem, which still deserves to be addressed and investigated. This paper revisits the issue of traffic engineering in Internet-of-Things (IoT) settings, to assess the relevance of using UAVs for the persistent collection of sensor readings from the sensor nodes located in an environment and their delivery to base stations where further processing is performed. We propose a persistent path planning and UAV allocation model, where a team of heterogeneous UAVs coming from various base stations are used to collect data from ground sensors and deliver the collected information to their closest base stations. This problem is mathematically formalised as a real-time constrained optimisation model, and proven to be NP-hard. The paper proposes a heuristic solution to the problem and evaluates its relative efficiency through performing experiments on both artificial and real sensors networks, using various scenarios of UAVs settings

Prevalence of Dental Traumas and Mouthguard use Among Contact Sports’ Players in Kigali, Rwanda

Background Dental traumas are widely prevalent in contact sports and are among the main public oral health concerns. They are attributed to nonuse and/or insufficient use of mouth guards, as protective means, for players in the game. Objectives The study aims to assess the prevalence of dental traumas among the contact sports and to determine the significance of using mouth guards in the prevention of such traumas. Methodology This was a cross sectional study conducted on the selected sports games in Kigali city, Rwanda. Data were collected using semi-structured questionnaires and analysed for any associations between independent variables and dependent variable with chi-square and logistic regression tests. Statistical Package for Social Sciences (SPSS) version 21 was used for the analysis. Results The prevalence of dental trauma was 58.9% among contact sports players in Kigali. Most respondents had information about mouth guards (94.7%) and many of them (62.2%) affirmed they could prevent dental traumas. This study has shown a significant association between dental traumas and mouth-guard use where players who did not use mouthguards were 5.8 times more likely to have dental traumas compared to those who used them regularly [OR=5.81;95% CI=2.44-13.82; p<0.001]. Conclusion A high prevalence of dental traumas was observed among the players despite the proven protection of using mouthguards. Therefore, putting emphasis on regular use of mouthguards would result in a huge reduction of risk and keep those traumas to a minimum. Rwanda J Med Health Sci 2022;5(3):315-32