published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy

Routing is the fundamental problem for Wireless Ad hoc networks, including Wireless Mobile Ad hoc networks (MANETs) and Wireless Sensor networks (WSNs). Although the problem has been extensively studied in the past decade, the existing solutions have deficiencies in one or more aspects including efficiency, scalability, robustness, complexity, etc.This dissertation proposes several new solutions for routing in WSNs and MANETs. Spiral is a data-centric routing algorithm for short-term communication in unstructured static WSNs. Spiral is a biased walk that visits nodes near the source before more distant nodes. This results in a spiral-like search path that is not only more likely to find a closer copy of the desired data than random walk, but is also able to compute a shorter route because the network around the source is more thoroughly explored. Compared with existing flooding and random walk approaches, Spiral has a lower search cost than flooding and returns better routes than random walk.Closest Neighbor First Search (CNFS) is a query processing algorithm for mobile wireless sensor networks. It is also walk-based and biased to visit nodes close to the source first. Different from Spiral, CNFS collects topology information as the search progresses. The topology information is used to compute the shortest return path for the query result and to tolerate the network topology changes caused by node mobility, which could otherwise cause the query to fail. CNFS requires fewer messages to process a query than flooding-based algorithms, while tolerating node mobility better than random walk-based algorithms.Address Aggregation-based Routing (AAR) is a novel routing protocol designed for MANETs. It reactively performs route discovery, but proactively maintains an index hierarchy called a Route Discovery DAG (RDD) to make route discovery efficient. The RDD contains aggregated node address information, requiring fewer packets for route discovery than the flooding used in existing protocols, while handling mobility better than pre-computing routes to all nodes. Compared with some existing popular protocols, AAR shows better performance in delivery rate, message overhead, latency and scalability.

The Internet of Things (IoT) represents a networking paradigm where entities are viewed as objects that are identifiable, traceable and connected. This view requires the integration and interoperability of numerous wireless standards. Radio Frequency Identification (RFID) systems and Wireless Sensor Networks (WSNs) are two dominant technologies that jointly constitute a class of hybrid/integrated IoT architectures known as RFID-Sensor Networks (RSNs). Data delivery across such integrated architectures faces challenges in terms of cost-efficiency, scalability and connectivity, among many others. Moreover, IoT-driven solutions are required to address constraints on node mobility, delay-tolerance and resource management, and may have to adhere to an economic model in order to establish incentive-based schemes. Most available RSN solutions are tailored for a single-application and fail to address the aforementioned IoT constraints. To the best of our knowledge, a detailed framework that comprehensively addresses such constraints does not exist. We investigate this promising research direction by proposing a novel framework that incorporates an RSN integrated architecture to improve delivery over heterogeneous topologies. Our framework provides data delivery solutions that adhere to delivery and connectivity considerations of integrated RSN architectures in IoT. Moreover, our data delivery solutions incorporate pricing policies for incentive public sensing applications over the proposed architecture. We show, by theoretical analysis and simulations, that our framework outperforms rival RSN integration approaches, as well as other wireless Ad-hoc data delivery schemes in realizing IoT performance requirements. / Thesis (Ph.D, Computing) -- Queen's University, 2013-05-01 15:09:52.668

As the primary military operating environment shifts from the traditional battlefields to a more diverse urban environment, the use of remote wireless sensors is increasing. Traditional development and procurement methods are not capable of meeting the changing requirements and time constraints of commanders. To minimize the time to develop and deploy new systems, commercial solutions must be examined. The focus of this thesis is on the integration of Commercial Off-the-Shelf (COTS) components into a wireless multimedia sensor network. Because components from multiple vendors were utilized, different operating systems and transmission protocols had to be integrated across the network. The network must be capable of providing a varying Quality of Service (QoS) level depending on the active sensors in the network. To ensure the QoS level is met, an adaptive QoS algorithm was implemented in the wireless IEEE 802.11 router which monitored and measured the outgoing transmission interface; from which, it determined the latency and transmission jitter. Based on the results, the program can adjust the bandwidth as necessary. Finally, a user interface is developed that allows end users to monitor the network. The performance of the network is based on the end-to-end throughput, latency and jitter exhibited by the network.

A wireless sensor network (WSN) consists of a large number of networked sensor nodes deployed to sense and report a particular phenomenon to a base station. Currently, most WSNs use radio frequency (RF) communications, and this accounts for a significant amount of energy expended. Free space optical (FSO) communications using modulating retroreflectors is potentially attractive for WSNs, due to the lower communications energy required. However, for FSO communications, line of sight (LOS) is required between the transmitter and the receiver. In this thesis, a hybrid Radio Frequency/Free Space Optical (RF/FSO) WSN is proposed. FSO links are used for communications, with RF links providing backup in the absence of LOS. This network has the potential to lower the overall energy consumption of a traditional RF-only WSN. Chapter 1 introduces the WSN and outlines the motivation for the RF/FSO WSN. Chapters 2 and 3 describe the RF and FSO link models used for the RF/FSO WSN. Chapter 4 describes how the WSN networks are configured. The energy model for the sensor node is discussed in Chapter 5. Chapter 6 discusses how network traffic and energy consumption are modelled. The results of the RF/FSO WSN simulations are presented in Chapter 7. Chapter 8 discusses the conclusions from the thesis and suggests areas for future work. Simulations show that for the wide range of scenarios considered, the RF/FSO WSN consumes less energy and has a lifetime at least twice as long as the RF-only WSN. For low and average optical blocking conditions, the RF/FSO WSN is also able to offer at least the same level of network coverage as the RF-only WSN.

Recent developments in robot technology have contributed to the advancement of autonomous behaviours in human-robot systems; for example, in following instructions received from an interacting human partner. Nevertheless, increasingly many systems are moving towards more seamless forms of interaction, where factors such as implicit trust and persuasion between humans and robots are brought to the fore. In this context, the problem of attaining, through suitable computational models and algorithms, more complex strategic behaviours that can influence human decisions and actions during an interaction, remains largely open. To address this issue, this thesis introduces the problem of decision shaping in strategic interactions between humans and robots, where a robot seeks to lead, without however forcing, an interacting human partner to a particular state. Our approach to this problem is based on a combination of statistical modeling and synthesis of demonstrated behaviours, which enables robots to efficiently adapt to novel interacting agents. We primarily focus on interactions between autonomous and teleoperated (i.e. human-controlled) NAO humanoid robots, using the adversarial soccer penalty shooting game as an illustrative example. We begin by describing the various challenges that a robot operating in such complex interactive environments is likely to face. Then, we introduce a procedure through which composable strategy templates can be learned from provided human demonstrations of interactive behaviours. We subsequently present our primary contribution to the shaping problem, a Bayesian learning framework that empirically models and predicts the responses of an interacting agent, and computes action strategies that are likely to influence that agent towards a desired goal. We then address the related issue of factors affecting human decisions in these interactive strategic environments, such as the availability of perceptual information for the human operator. Finally, we describe an information processing algorithm, based on the Orient motion capture platform, which serves to facilitate direct (as opposed to teleoperation-mediated) strategic interactions between humans and robots. Our experiments introduce and evaluate a wide range of novel autonomous behaviours, where robots are shown to (learn to) influence a variety of interacting agents, ranging from other simple autonomous agents, to robots controlled by experienced human subjects. These results demonstrate the benefits of strategic reasoning in human-robot interaction, and constitute an important step towards realistic, practical applications, where robots are expected to be not just passive agents, but active, influencing participants.

Wireless sensors can be worn on soldiers or installed on vehicles to form distributed sensor networks to locate the source of sniper fire. A two-step source localization process is proposed for this sniper detection task. The time difference of arrival (TDOA) for the acoustic signals received by the sensors is first estimated using the generalized cross correlation (GCC) method. The estimated TDOA values are then used by the hybrid spherical interpolation/maximum likelihood (SI/ML) estimation method to estimate the shooter location. A simulation model has been developed in MATLAB to study the performance of the hybrid SI/ML estimation method. A wireless sensor network is simulated in NS-2 to study the network throughput, delay and jitter. Simulation results indicate that the estimation accuracy can be increased by increasing the number of sensors or the inter-sensor spacing. The constraint of small inter-sensor spacing on wearable sensors is found to degrade the estimation accuracy, but vehicular configuration providing larger inter-sensor spacing can help improve the estimation accuracy. The sensor topology should be well represented in all three dimensions to obtain desired estimation accuracy. The estimation accuracy is not adversely affected by sensor node failures or location perturbations. The NS-2 simulation results indicate that the wireless sensor network has low delay and can support fast information exchange needed in counter-sniper applications.

The applications of wireless sensor networks (WSNs) have risen in recent years both in the civilian and military sectors. While a number of WSN-based systems have been proposed and developed, vast majority of them focus on capability demonstration rather than the issues of deployment. As a result, even though the systems can serve useful purposes, they are very hard to deploy. The objective of this thesis is to focus on the deployment issues of WSNs. In addition, this thesis assesses the optimal configurations and environment that enables the sensor networks to thrive in a C4ISR environment. This thesis presents a technology review of the ZigBee and the IEEE 802.15.4 standards which form the core technology in WSNs. The thesis also discusses the IEEE 802.15.4 Physical and Media Access Control Layers that comprise the bottom two layers of WSNs. This thesis also provides a brief introduction to the hardware and software that deal with WSN technology. Lastly, this thesis evaluates the military applications of WSNs. It is hoped that the military can employ wireless sensors to increase situational awareness, attain information superiority, and improve decision-making.