Using renewable energy to power roadside units (RSUs) in vehicular ad hoc networks is a desirable green alternative to the conventional electric grid, since it lowers both the carbon footprint and the cost of deployment. This paper investigates the problem of scheduling the downlink communication from renewable energy-powered RSUs toward vehicles, with the objective of maximizing the number of served vehicles. First, an offline setting is considered where the RSUs are assumed to have advance knowledge of the incoming communication requests from vehicles and of the amount of energy to be harvested. The problem is formulated as an integer linear programming model that is shown to be NP-hard and two near-optimal solutions are proposed. The first one is a greedy heuristic that prioritizes communications based on their energy cost and the second is the particle swarm optimization metaheuristic. Then, the problem is considered in an online setting and two different solution approaches are investigated. The first one assumes distributed scheduling control between RSUs and two algorithms are proposed, one based on a stochastic model and the other on simple threshold-based selection of communication requests. The second approach assumes centralized scheduling and two algorithms are also investigated. The first one uses a greedy approach and the second one uses threshold-based selection again. Simulations compare the proposed schedulers and show their efficiency in terms of the number of vehicles served and the service delay. It is concluded that employing energy harvesting RSUs is a viable green alternative to grid-powered ones.

Offline and Online Scheduling Algorithms for Energy Harvesting RSUs in VANETs

Clustering based energy efficient multi-relay scheduling in green vehicular infrastructure

The demand for large-scale sensing capabilities and scalable communication networks to monitor and control entities within smart buildings have fuelled the exponential growth in Wireless Sensor Network (WSN). WSN proves to be an attractive enabler because of its accurate sensing, low installation cost and flexibility in sensor placement. While WSN offers numerous benefits, it has yet to realise its full potential due to its susceptibility to network challenges in the environment that it is deployed. Particularly, spatial challenges in the indoor environment are known to degrade WSN communication reliability and have led to poor estimations of link quality. Existing WSN solutions often generalise all link failures and tackle them as a single entity. However, under the persistent influence of spatial challenges, failing to provide precise solutions may cause further link failures and higher energy consumption of battery-powered devices. Therefore, it is crucial to identify the causes of spatial- related link failures in order to improve WSN communication reliability.
This thesis investigates WSN link failures under the influence of spatial challenges in real-world indoor environments. Novel and effective strategies are developed to evaluate the WSN communication reliability. By distinguishing between spatial challenges such as a poorly deployed environment and human movements, solutions are devised to reduce link failures and improve the lifespans of energy constraint WSN nodes.
In this thesis, WSN test beds using proprietary wireless sensor nodes are developed and deployed in both controlled and uncontrolled office environments. These test beds provide diverse platforms for investigation into WSN link quality. In addition, a new data extraction feature called Network Instrumentation (NI) is developed and implemented onto the communication stacks of wireless sensor nodes to collect ZigBee PRO parameters that are under the influence of environmental dynamics.
To understand the relationships between WSN and Wi-Fi devices communications, an investigation on frequency spectrum sharing is conducted between IEEE 802.15.4 and IEEE 802.11 bgn standards. It is discovered that the transmission failure of WSN nodes under persistent Wi-Fi interference is largely due to channel access failure rather than corrupted packets. The findings conclude that both technologies can co- exist as long as there is sufficient frequency spacing between Wi-Fi and WSN communication and adequate operating distance between the WSN nodes, and between the WSN nodes and the Wi-Fi interference source.
Adaptive Network-based Fuzzy Inference System (ANFIS) models are developed to predict spatial challenges in an indoor environment. These challenges are namely, “no failure”, “failure due to poorly deployed environment” and “failure due to human movement”. A comparison of models has found that the best-produced model represents the properties of signal strength, channel fluctuations, and communication success rates. It is recognised that the interpretability of ANFIS models have reduced due to the “curse of dimensionality”. Hence, Non-Dominated Sorting Genetic Algorithm (NSGA-II) technique is implemented to reduce the complexity of these ANFIS models. This is followed by a Fuzzy rule sensitivity analysis, where the impacts of Fuzzy rules on model accuracy are found to be dependent on factors such as communication range and controlled or uncontrolled environment.
Long-term WSN routing stability is measured, taking into account the adaptability and robustness of routing paths in the real-world environments. It is found that routing stability is subjected to the implemented routing protocol, deployed environment and routing options available. More importantly, the probability of link failures can be as high as 29.9% when a next hop’s usage rate falls less than 10%. This suggests that a less dominant next hop is subjected to more link failures and is short-lived.
Overall, this thesis brings together diverse WSN test beds in real-world indoor environments and a new data extraction platform to extract link quality parameters from ZigBee PRO stack for a representative assessment of WSN link quality. This produces realistic perspectives of the interactions between WSN communication reliability and the environmental dynamics, particularly spatial challenges. The outcomes of this work include an in-depth system level understanding of real-world deployed applications and an insightful measure of large-scale WSN communication performance. These findings can be used as building blocks for a reliable and sustainable network architecture built on top of resource–constrained WSN.

An approach to understand network challenges of wireless sensor network in real-world environments

Cognitive radio (CR) is a promising technology that provides solution for the spectrum underutilization problems via dynamic spectrum sharing among primary users and secondary users. Game theory has emerged in the last fifteen years as an effective framework for communications problems, which is used to analyze those problems and help to derive solutions. In this paper, we propose a sufficiently opportunistic utilization for spectrum resources by solving two challenges: interference and power consumption. We analyze the spectrum allocation problem under game theoretical framework and we propose an efficient algorithm to examine the design specification issues regarding the choice of optimal power, optimal speed, and optimal amount of information in a wireless network. Our objectives are to regulate the opportunistic spectrum access by the secondary users in order to guarantee the protection on licensed users from harmful interference, more especially, to optimize the quality of communication link, Transmission levels, and battery life of the wireless devices.

Controlling interference and power consumption in cognitive radio based on game theory

The increasing need of wireless communications in emerging scenarios, including aerial and maritime, requires the development of new protocols and the enhancement of existing protocols. To properly validate these developments, we depend on performance evaluation of wireless networks, traditionally considering Simulation and Experimentation activities. Simulations are flexible but usually produce optimistic results, assuming many simplifications to represent complex scenarios such as those related to emerging aerial networks. Testbeds, on the other hand, are increasingly costly to maintain and are frequently unavailable; still, they provide realistic results and are an essential step to achieve proper protocol validation and fine tuning. The problem is that real wireless testbed experiments in emerging networking scenarios are hardly repeatable. Given the same input, they can produce very different output results, since wireless communications are influenced by external random phenomena such as noise, interference, and multipath. Real experiments are also difficult to reproduce. Either the original community testbed can be unavailable – offline or running other experiments – or the custom testbed becomes inaccessible. Without repeatability and reproducibility, the validity of the protocol developed is questionable. Also, there is duplication of effort to develop simulation and real implementation of the protocols, which can be error-prone and lead to non-comparable results. Based on the identified problems and on our experience in different research projects, in this thesis we propose the use of ns-3 as a common platform to enhance and promote the interaction between Simulation and Experimentation. The objective is to foster the synergy between Simulation and Experimentation, improving the process of performance evaluation of wireless networks. This synergy is addressed in both directions, resulting in two related main original contributions: a) from simulation to experimentation – the Fast Prototyping development process; b) from experimentation to simulation – the Trace-based Simulation (TS) approach. The Fast Prototyping development process allows to reuse the ns-3 protocol model implementation in the real prototype for obtaining comparable results, reducing code duplication and potential implementation differences. In addition, it improves the ns-3 emulation functionality and performance, with a 23-fold increase in throughput and a 15-fold decrease in Round-Trip Time (RTT), when compared to the current ns-3 emulation performance in a scenario of interest. The TS approach captures the physical conditions of real experiments (e.g., radio link quality, the positions of the nodes) and relies on ns-3 TCP/IP and MAC simulation capabilities to enable the reproduction of real experiments in simulation. The TS approach was extensively evaluated, producing more accurate results than the pure simulation alternatives; it achieved average gains above 53% and 90th percentile gains above 57% in scenarios of interest. With comparable results using the Fast Prototyping development process, and repeatable and reproducible past real experiments using the TS approach, the interaction between Simulation and Experimentation activities results in an enhanced Simulation-Experimentation synergy that improves the process of performance evaluation of wireless networks.

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Improving the performance evaluation of wireless networks: towards a simulation-experimentation synergy using ns-3

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Wireless communications: Principles and practice, solutions manual