Marcus, Anthony M.

To ensure that a system is robust and will continue operation even when facing
disruptive or traumatic events, we have created a methodology for system architects and
designers which may be used to locate risks and hazards in a design and enable the
development of more robust and resilient system architectures. It uncovers design
vulnerabilities by conducting a complete exploration of a systems’ component
operational state space by observing the system from multi-dimensional perspectives and
conducts a quantitative design space analysis by means of probabilistic risk assessment
using Bayesian Networks. Furthermore, we developed a tool which automated this
methodology and demonstrated its use in an assessment of the OCTT PHM communication system architecture. To boost the robustness of a wireless communication system and efficiently allocate bandwidth, manage throughput, and ensure quality of service on a wireless link, we created a wireless link management architecture which applies sensor fusion to gather and store platform networked sensor metrics, uses time series forecasting to predict the platform position, and manages data transmission for the links (class based, packet scheduling and capacity allocation). To validate our architecture, we developed a link management tool capable of forecasting the link quality and uses cross-layer scheduling and allocation to modify capacity allocation at the IP layer for various packet flows (HTTP, SSH, RTP) and prevent congestion and priority inversion. Wireless sensor networks (WSN) are vulnerable to a plethora of different fault types and external attacks after their deployment. To maintain trust in these systems and
increase WSN reliability in various scenarios, we developed a framework for node fault
detection and prediction in WSNs. Individual wireless sensor nodes sense characteristics
of an object or environment. After a smart device successfully connects to a WSN’s base
station, these sensed metrics are gathered, sent to and stored on the device from each
node in the network, in real time. The framework issues alerts identifying nodes which
are classified as faulty and when specific sensors exceed a percentage of a threshold
(normal range), it is capable of discerning between faulty sensor hardware and anomalous
sensed conditions. Furthermore we developed two proof of concept, prototype
applications based on this framework.

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.