Impact of drone route geometry on information collection in wireless sensor networks

The recent technological evolution of drones along with the constantly growing maturity of its commercialization, has led to the emergence of novel drone-based applications within the field of wireless sensor networks for information collection purposes. In such settings, especially when deployed in outdoor environments with limited external control, energy consumption and robustness are challenging problems for the system’s operation. In the present paper, a drone-assisted wireless sensor network is studied, the aim being to coordinate the routing of information (among the ground nodes and its propagation to the drone), investigating several drone trajectories or route shapes and examining their impact on information collection (the aim being to minimize transmissions and consequently, energy consumption). The main contribution lies on the proposed algorithms that coordinate the communication between (terrestrial) sensor nodes and the drone that may follow different route shapes. It is shown through simulations using soft random geometric graphs that the number of transmitted messages for each drone route shape depends on the rotational symmetry around the center of each shape. An interesting result is that the higher the order of symmetry, the lower the number of transmitted messages for data collection. Contrary, for those cases that the order of symmetry is the same, even for different route shapes, similar number of messages is transmitted. In addition to the simulation results, an experimental demonstration, using spatial data from grit bin locations, further validates the proposed solution under real-world conditions, demonstrating the applicability of the proposed approach.publishedVersio

An overview of VANET vehicular networks

Today, with the development of intercity and metropolitan roadways and with various cars moving in various directions, there is a greater need than ever for a network to coordinate commutes. Nowadays, people spend a lot of time in their vehicles. Smart automobiles have developed to make that time safer, more effective, more fun, pollution-free, and affordable. However, maintaining the optimum use of resources and addressing rising needs continues to be a challenge given the popularity of vehicle users and the growing diversity of requests for various services. As a result, VANET will require modernized working practices in the future. Modern intelligent transportation management and driver assistance systems are created using cutting-edge communication technology. Vehicular Ad-hoc networks promise to increase transportation effectiveness, accident prevention, and pedestrian comfort by allowing automobiles and road infrastructure to communicate entertainment and traffic information. By constructing thorough frameworks, workflow patterns, and update procedures, including block-chain, artificial intelligence, and SDN (Software Defined Networking), this paper addresses VANET-related technologies, future advances, and related challenges. An overview of the VANET upgrade solution is given in this document in order to handle potential future problems

Green internet of things using UAVs in B5G networks: A review of applications and strategies

Recently, Unmanned Aerial Vehicles (UAVs) present a promising advanced technology that can enhance people life quality and smartness of cities dramatically and increase overall economic efficiency. UAVs have attained a significant interest in supporting many applications such as surveillance, agriculture, communication, transportation, pollution monitoring, disaster management, public safety, healthcare, and environmental preservation. Industry 4.0 applications are conceived of intelligent things that can automatically and collaboratively improve beyond 5G (B5G). Therefore, the Internet of Things (IoT) is required to ensure collaboration between the vast multitude of things efficiently anywhere in real-world applications that are monitored in real-time. However, many IoT devices consume a significant amount of energy when transmitting the collected data from surrounding environments. Due to a drone's capability to fly closer to IoT, UAV technology plays a vital role in greening IoT by transmitting collected data to achieve a sustainable, reliable, eco-friendly Industry 4.0. This survey presents an overview of the techniques and strategies proposed recently to achieve green IoT using UAVs infrastructure for a reliable and sustainable smart world. This survey is different from other attempts in terms of concept, focus, and discussion. Finally, various use cases, challenges, and opportunities regarding green IoT using UAVs are presented.This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 847577; and a research grant from Science Foundation Ireland (SFI) under Grant Number 16 / RC / 3918 (Ireland's European Structural and Investment Funds Programmes and the European Regional Development Fund 2014-2020)

Drone Base Station Trajectory Management for Optimal Scheduling in LTE-Based Sparse Delay-Sensitive M2M Networks

Providing connectivity in areas out of reach of the cellular infrastructure is a very active area of research. This connectivity is particularly needed in case of the deployment of machine type communication devices (MTCDs) for critical purposes such as homeland security. In such applications, MTCDs are deployed in areas that are hard to reach using regular communications infrastructure while the collected data is timely critical. Drone-supported communications constitute a new trend in complementing the reach of the terrestrial communication infrastructure. In this study, drones are used as base stations to provide real-time communication services to gather critical data out of a group of MTCDs that are sparsely deployed in a marine environment. Studying different communication technologies as LTE, WiFi, LPWAN and Free-Space Optical communication (FSOC) incorporated with the drone communications was important in the first phase of this research to identify the best candidate for addressing this need. We have determined the cellular technology, and particularly LTE, to be the most suitable candidate to support such applications. In this case, an LTE base station would be mounted on the drone which will help communicate with the different MTCDs to transmit their data to the network backhaul. We then formulate the problem model mathematically and devise the trajectory planning and scheduling algorithm that decides the drone path and the resulting scheduling. Based on this formulation, we decided to compare between an Ant Colony Optimization (ACO) based technique that optimizes the drone movement among the sparsely-deployed MTCDs and a Genetic Algorithm (GA) based solution that achieves the same purpose. This optimization is based on minimizing the energy cost of the drone movement while ensuring the data transmission deadline missing is minimized. We present the results of several simulation experiments that validate the different performance aspects of the technique

Routing protocols for next generation mobile wireless sensor networks

The recent research interest in wireless sensor networks has caused the development of many new applications and subsequently, these emerging applications have ever increasing requirements. One such requirement is that of mobility, which has inspired an entirely new array of applications in the form of mobile wireless sensor networks (MWSNs). In terms of communications, MWSNs present a challenging environment due to the high rate at which the topology may be changing. As such, the motivation of this work is to investigate potential communications solutions, in order to satisfy the performance demands of new and future MWSN applications. As such this work begins by characterising and evaluating the requirement of a large variety of these emerging applications. This thesis focuses on the area of routing, which is concerned with the reliable and timely delivery of data from multiple, mobile sensor nodes to a data sink. For this purpose the technique of gradient routing was identified as a suitable solution, since data can quickly be passed down a known gradient that is anchored at the sink. However, in a mobile network, keeping the gradient up-to-date is a key issue. This work proposes the novel use of a global time division multiple access (GTDMA) MAC as a solution to this problem, which mitigates the need for regularly flooding the network. Additionally, the concept of blind forwarding is utilised for its low overhead and high reliability through its inherent route diversity. The key contribution of this thesis is in three novel routing protocols, which use the aforementioned principles. The first protocol, PHASeR, uses a hop-count metric and encapsulates data from multiple nodes in its packets. The hop-count metric was chosen because it is simple and requires no additional hardware. The inclusion of encapsulation is intended to enable the protocol to cope with network congestion. The second protocol, LASeR, utilises location awareness to maintain a gradient and performs no encapsulation. Since many applications require location awareness, the communications systems may also take advantage of this readily available information and it can be used as a gradient metric. This protocol uses no encapsulation in order to reduce delay times. The third protocol, RASeR, uses the hop-count metric as a gradient and also does not perform encapsulation. The reduced delay time and the relaxed requirement for any existing method of location awareness makes this the most widely applicable of the three protocols. In addition to analytical expressions being derived, all three protocols are thoroughly tested through simulation. Results show the protocols to improve on the state-of-the-art and yield excellent performance over varying speeds, node numbers and data generation rates. LASeR shows the lowest overhead and delay, which comes from the advantage of having available location information. Alternatively, at the expense of increased overhead, RASeR gives comparatively high performance metrics without the need for location information. Overall, RASeR can be suitably deployed in the widest range of applications, which is taken further by including four additional modes of operation. These include a supersede mode for applications in which the timely delivery of the most recent data is prioritised. A reverse flooding mechanism, to enable the sink to broadcast control messages to the sensor nodes. An energy saving mode, which uses sleep cycles to reduce the networks power consumption, and finally a pseudo acknowledgement scheme to increase the reliability of the protocol. These additions enable RASeR to satisfy the needs of some of the most demanding MWSN applications. In order to assess the practicality of implementation, RASeR was also evaluated using a small testbed of mobile nodes. The successful results display the protocols feasibility to be implemented on commercially available hardware and its potential to be deployed in the real world. Furthermore, a key issue in the real world deployment of networks, is security and for this reason a fourth routing protocol was designed called RASeR-S. RASeR-S is based on RASeR, but introduces the use of encryption and suggests a security framework that should be followed in order to significantly reduce the possibility of a security threat. Whilst the main focus of this work is routing, alternative MAC layers are assessed for LASeR. Unlike the other two protocols, LASeR uses available location information to determine its gradient and as such, it is not reliant on the GTDMA MAC. For this reason several MAC layers are tested and the novel idea of dedicated sensing slots is introduced, as well as a network division multiple access scheme. The selected and proposed MACs are simulated and the GTDMA and two proposed protocols are shown to give the best results in certain scenarios. This work demonstrates the high levels of performance that can be achieved using gradient orientated routing in a mobile network. It has also shown that the use of a GTDMA MAC is an efficient solution to the gradient maintenance problem. The high impact of this work comes from the versatility and reliability of the presented routing protocols, which means they are able to meet the requirements of a large number of MWSN applications. Additionally, given the importance of security, RASeR-S has been designed to provide a secure and adaptable routing solution for vulnerable or sensitive applications

Efficient algorithms for MAC layer duty cycling and frame delivery in wireless sensor network

In Wireless Sensor Networks, with small, limited capacity devices now more prevalent, the issue of Neighbour Discovery has shifted. These devices utilise duty cycling methods in order to conserve battery power. Hence, the main issue is now that these devices may be awake at the same time in order to discover each other. When mobility increases complexity further. Rather than attempt to negate the issue of mobility, instead this thesis seeks to utilise a predictable sink mobility pattern in order to influence the duty cycling of static nodes. Literature demonstrates a move towards Mobility Awareness in Neighbour Discovery in mobile Wireless Sensor Networks. However, there is a gap identified with sink mobility in use. Therefore, this thesis aims to establish to what extent the mobility pattern of a Mobile Sink Node in a Wireless Sensor Network may be exploited at the MAC layer, to influence the performance of static nodes. Such that network efficiency may be improved with energy consumption reduced and balanced across nodes. This study proposes three novel lightweight algorithms, with processing which does not add to the energy consumption within sensor nodes, these being Mobility Aware Duty Cycling Algorithm (MADCAL), Mobility Aware Duty Cycling and Dynamic Preambling Algorithm (MADCaDPAL) and Dynamic Mobility and Energy Aware Algorithm (DMEAAL). These located in the MAC layer of static nodes and utilising knowledge of predictable sink node mobility. This is in order to create a dynamic communication threshold between static nodes on the sink path and the sink itself. Subsequently lessening competition for sink communication between nodes. In MADCAL this threshold is used to influence the sleep function in order that static nodes only awake and move to Clear Channel Assessment once the sink is within their threshold, improving energy consumption by up to 15%. The MADCaDPAL algorithm takes this approach further, using the threshold to directly influence Clear Channel Assessment and the sending of preambles, as such, closing off the threshold when the sink leaves it. This shows energy consumption lessening by close to 80% with a significant improvement in frame delivery to the sink. Finally, the DMEAAL algorithm utilises previous results to influence energy consumption in real-time by utilising a cross-layer approach, comparing current consumption to optimal target energy consumption and adjusting the threshold for each static node accordingly. This shows benefit in evening out results across nodes, thus improving network lifetime. All algorithms are achieved without the energy-consuming beacon messaging associated with Neighbour Discovery. Analysis and simulation results, tested on a lightweight implementation of a carrier-sense multiple-access-based MAC protocol, show a significant improvement in energy consumption and frame delivery in both controlled and random environments. In utilising a cross-layer approach to access energy consumption in static nodes, is it also shown to be possible to even out energy consumption across nodes by altering the communication threshold in real-time. As such, improving network lifetime by removing spikes in energy consumption in individual nodes