Ad hoc networks (Computer networks)

Cognitive radio technology that enables dynamic spectrum access has been
a promising solution for the spectrum scarcity problem. Cognitive radio networks
enable the communication on both licensed and unlicensed channels, having the potential
to better solve the interference and collision issues. Channel assignment is of
great importance in cognitive radio networks. When operating on licensed channels,
the objective is to exploit spectrum holes through cognitive communication, giving
priority to the primary users. In this dissertation, we focus on the development of efficient
channel assignment algorithms and protocols to improve network performance
for cognitive radio wireless networks. The first contribution is on channel assignment
for cognitive radio wireless sensor networks aiming to provide robust topology control,
as well as to increase network throughput and data delivery rate. The approach
is then extended to specific cognitive radio network applications achieving improved
performances.

The scalability of QUIC-TCP was examined by expanding previous
developmental 11-node, 4-flow topology to over 30 nodes with 11 flows to validate
QUIC-TCP for larger networks. The topology was simulated using ns-2 network
simulator with the same ns-2 module of FAST-TCP modified to produce QUIC-TCP
agent that the original development used. A symmetrical topology and a random
topology were examined. Fairness, aggregate throughput and the object of the utility
function were used as validation criteria. It was shown through simulation that QUICTCP
optimized the utility function and demonstrated a good balance between aggregate
throughput and fairness; therefore QUIC-TCP is indeed scalable to larger networks.

This dissertation presents the results of research that led to the development of a novel reputation and trust-based monitoring paradigm for secure and reliable computing in Wireless Sensor Networks (WSNs). WSNs have undergone tremendous technological advances over the last few years. They have caused a giant leap toward "proactive computing," a paradigm where computers anticipate human needs and, when necessary, act on their behalf. Therefore, we cannot deploy such a critical technology without first addressing the security and privacy challenges to ensure that it does not turn against those whom it is meant to benefit. The core application of WSNs is to detect and report events, be it military or civilian applications. The building blocks of a WSN are small, battery-powered, lowcost, self-contained devices called "sensors" that measure factors like light, temperature, pressure, vibration, motion, etc. A WSN usually consists of hundreds of thousands of sensors that operate in unattended, hostile territories to monitor a given geographical area. Once deployed, the wireless sensors self-organize into ad-hoc wireless networks in order to cope with the dynamics of the surveillance field. During the post deployment phase, the wireless sensors aggregate data, then process and generate a report, which is subsequently relayed from one sensor to the next using secure multi-hop routing until the data reaches its desired destination, which is usually the sink. Since sensors operate in unattended and hostile territories, the adversary can capture a sensor node physically and extract all the information stored onboard, including cryptographic keying material. With this unique situation, WSNs are subject to a unique attack referred to as an "Insider Attack," in which the adversary becomes a legitimate member of the network being represented by the captured node.

This research addresses communication security in the highly constrained wireless sensor environment. The goal of the research is twofold: (1) to develop a key management scheme that provides these constrained systems with the basic security requirements and evaluate its effectiveness in terms of scalability, efficiency, resiliency, connectivity, and flexibility, and (2) to implement this scheme on an appropriate routing platform and measure its efficiency.

The Transmission Control Protocol (TCP) is one of the core protocols of the Internet protocol suite, which is used by major Internet applications such as World Wide Web, email, remote administration and file transfer. TCP implements scalable and distributed end-to-end congestion control algorithms to share network resources among competing users. TCP was originally designed primarily for wired networks, and it has performed remarkably well as the Internet scaled up by six orders of magnitude in the past decade. However, many studies have shown that the unmodified standard TCP performs poorly in networks with large bandwidth-delay products and/or lossy wireless links. In this thesis, we analyze the problems TCP exhibits in the wireless communication environment, and develop joint TCP congestion control and wireless-link scheduling schemes for mobile applications. ... Different from the existing solutions, the proposed schemes can be asynchronously implemented without message passing among network nodes; thus they are readily deployable with current infrastructure. Moreover, global convergence/stability of the proposed schemes to optimal equilibrium is established using the Lyapunov method in the network fluid model. Simulation results are provided to evaluate the proposed schemes in practical networks.

The Transmission Control Protocol (TCP) is one of the core protocols of the Internet protocol suite. In the wired network, TCP performs remarkably well due to its scalability and distributed end-to-end congestion control algorithms. However, many studies have shown that the unmodified standard TCP performs poorly in networks with large bandwidth-delay products and/or lossy wireless links. In this thesis, we analyze the problems TCP exhibits in the wireless communication and develop TCP congestion control algorithm for mobile applications. We show that the optimal TCP congestion control and link scheduling scheme amounts to window-control oriented implicit primaldual solvers for underlying network utility maximization. Based on this idea, we used a scalable congestion control algorithm called QUeueIng-Control (QUIC) TCP where it utilizes queueing-delay based MaxWeight-type scheduler for wireless links developed in [34]. Simulation and test results are provided to evaluate the proposed schemes in practical networks.

This thesis consists of the development of a web based wireless sensor network (WSN) monitoring system using smartphones. Typical WSNs consist of networks of wireless sensor nodes dispersed over predetermined areas to acquire, process, and transmit data from these locations. Often it is the case that the WSNs are located in areas too hazardous or inaccessible to humans. We focused on the need for access to this sensed data remotely and present our reference architecture to solve this problem. We developed this architecture for web-based wireless sensor network monitoring and have implemented a prototype that uses Crossbow Mica sensors and Android smartphones for bridging the wireless sensor network with the web services for data storage and retrieval. Our application has the ability to retrieve sensed data directly from a wireless senor network composed of Mica sensors and from a smartphones onboard sensors. The data is displayed on the phone's screen, and then, via Internet connection, they are forwarded to a remote database for manipulation and storage. The attributes sensed and stored by our application are temperature, light, acceleration, GPS position, and geographical direction. Authorized personnel are able to retrieve and observe this data both textually and graphically from any browser with Internet connectivity or through a native Android application. Web-based wireless sensor network architectures using smartphones provides a scalable and expandable solution with applicability in many areas, such as healthcare, environmental monitoring, infrastructure health monitoring, border security, and others.

A Wireless Sensor Network (WSN) is composed of low-cost electronic devices with sensing, data storage and transmitting capabilities, powered by batteries. There are extensive studies in the field of WSN investigating different algorithms and protocols for data collection. A data collector can be static or mobile. Using a mobile data collector can extend network lifetime and can be used to collect sensor data in hardly accessible locations, partitioned networks, and delay-tolerant networks. The implementation of the mobile data collector in our study consists of combining two different platforms: the Crossbow sensor hardware and the NXT Legos. We developed an application for data collection and sensor querying support. Another important contribution is designing a semi-autonomous robot control. This hardware prototype implementation shows the benefits of using a mobile data collector in WSN. It also serves as a reference in developing future applications for mobile WSNs.

Many emerging mobile networks aim to provide wireless network services without relying on any infrastructure. The main challenge in these networks comes from their self-organized and distributed nature. There is an inherent reliance on collaboration among the participants in order to achieve the aimed functionalities. Therefore, establishing and quantifying trust, which is the driving force for collaboration, is important for applications in mobile networks. This dissertation focuses on evaluating and quantifying trust to stimulate collaboration in mobile networks, introducing uncertainty concepts and metrics, as well as providing the various analysis and applications of uncertainty-aware reputation systems. Many existing reputation systems sharply divide the trust value into right or wrong, thus ignoring another core dimension of trust: uncertainty. As uncertainty deeply impacts a node's anticipation of others' behavior and decisions during interaction, we include it in the reputation system. Specifically, we use an uncertainty metric to directly reflect a node's confidence in the sufficiency of its past experience, and study how the collection of trust information may affect uncertainty in nodes' opinions. Higher uncertainty leads to higher transaction cost and reduced acceptance of communication. We exploit mobility to efficiently reduce uncertainty and to speed up trust convergence. We also apply the new reputation system to enhance the analysis of the interactions among mobile nodes, and present three sample uncertainty-aware applications. We integrate the uncertainty-aware reputation model with game theory tools, and enhance the analysis on interactions among mobile nodes.

Controlling the cooperative behaviors of a fleet of autonomous underwater vehicles in a stochastic, complex environment is a formidable challenge in artificial intelligence. The complexity arises from the challenges of limited navigation and communication capabilities of underwater environment. A time critical cooperative operation by acoustic networks of Multiple Cooperative Vehicles (MCVs) necessitates a robust task allocation mechanism and an efficient path planning model. In this work, we present solutions to investigate two aspects of the cooperative schema for multiple underwater vehicles under realistic underwater acoustic communications: a Location-aided Task Allocation Framework (LAAF) algorithm for multi-target task assignment and a mathematical programming model, the Grid-based Multi-Objective Optimal Programming (GMOOP), for finding an optimal vehicle command decision given a set of objectives and constraints. We demonstrate that, the location-aided auction strategies perform significantly better than the generic auction algorithm in terms of effective task allocation time and information bandwidth requirements. In a typical task assignment scenario, the time needed in the LAAF algorithm is only a fraction compared to the generic auction algorithm. On the other hand; the GMOOP path planning technique provides a unique means for multi-objective tasks by cooperative agents with limited communication capabilities. Under different environmental settings, the GMOOP path planning technique is proved to provide a method with balance of sufficient expressive power and flexibility, and its solution algorithms tractable in terms of mission completion time, with a limited increase of overhead in acoustic communication. Prior to this work, existing multi-objective action selection methods were limited to robust networks where constant communication available.