A General Purpose Framework for Wireless Sensor Network Applications

Wireless sensor networks are becoming a basis for a rapidly increasing range of applications. Habitat, flood, and wildfire monitoring are interesting examples of such applications. Each application has different requirements in terms of node functionalities, network size, complexity and cost; therefore, it is worthwhile time investment to design and implement a general purpose framework for wireless sensor networks that would be adaptable to any monitoring application of interest with a minimum amount of effort. In this manuscript, we propose a basic structure for such a framework and highlight a number of challenges anticipated during the course of this doctoral research

Reliability Modeling for the Advanced Electric Power Grid

The advanced electric power grid promises a self-healing infrastructure using distributed, coordinated, power electronics control. One promising power electronics device, the Flexible AC Transmission System (FACTS), can modify power flow locally within a grid. Embedded computers within the FACTS devices, along with the links connecting them, form a communication and control network that can dynamically change the power grid to achieve higher dependability. The goal is to reroute power in the event of transmission line failure. Such a system, over a widespread area, is a cyber-physical system. The overall reliability of the grid is a function of the respective reliabilities of its two major subsystems, namely, the FACTS network and the physical components that comprise the infrastructure. This paper presents a mathematical model, based on the Markov chain imbeddable structure, for the overall reliability of the grid. The model utilizes a priori knowledge of reliability estimates for the FACTS devices and the communications links among them to predict the overall reliability of the power grid

A case study in quantitative analysis of cyber-physical systems: reliability of the Smart Grid

A cyber-physical system is the integration of a physical infrastructure with a cyber infrastructure, which provides control over its physical counterpart. The goal is to improve certain aspects of the physical infrastructure, such as its reliability. The Smart Grid, in which intelligent cyber control is added to improve the operation of the traditional power grid, is a prime example of a cyber-physical system. Quantitative models are needed in order to better understand the benefits and risks of adding intelligence to physical systems. To this end, we have developed an integrated cyber-physical reliability model, with a focus on the Smart Grid as our case study. By understanding operational semantics of the Smart Grid, we analyzed the effects of failures in both the physical and cyber infrastructures. Moreover, for the cyber infrastructure, we studied several failure modes, which reflect the various ways in which the cyber components can fail, both in hardware and in software. We further refined our model by using software fault injection in the cyber infrastructure, which revealed additional failure modes. The original contribution of this dissertation is the development of a quantitative reliability model for the Smart Grid, which reflects the effect of physical failures (transmission line outages) and cyber failures (software errors) in a unified model. This work can be extended to other cyber-physical critical infrastructure systems, and serves as a first step towards development of a generalized quantitative reliability model for cyber-physical systems --Abstract, page iii

Reliability modeling for the advanced electric power grid

The advanced electric power grid promises a self-healing infrastructure using distributed, coordinated, power electronics control. One promising power electronics device, the Flexible AC Transmission System (FACTS), can modify the power flow locally within a power grid. Embedded computers within the FACTS devices, along with the links connecting them, form a communication and control network that can dynamically change the grid to achieve higher dependability. The goal is to reroute power distribution in the event of transmission line failure --Abstract, page iii

Integrated Cyber-Physical Fault Injection for Reliability Analysis of the Smart Grid

The term Smart Grid broadly describes emerging power systems whose physical operation is managed by significant intelligence. The cyber infrastructure providing this intelligence is composed of power electronics devices that regulate the flow of power in the physical portion of the grid. Distributed software is used to determine the appropriate settings for these devices. Failures in the operation of the Smart Grid can occur due to malfunctions in physical or cyber (hardware or software) components. This paper describes the use of fault injection in identifying failure scenarios for the Smart Grid. Software faults are injected to represent failures in the cyber infrastructure. Physical failures are concurrently represented, creating integrated cyber-physical failure scenarios that differentiate this work from related studies. The effect of these failure scenarios is studied in two cases: with and without fault detection in the distributed software. The paper concludes by utilizing the information gained to refine and improve the accuracy of the quantitative reliability model presented in our earlier work

Reliability Modeling for the Advanced Electric Power Grid

The advanced electric power grid promises a self-healing infrastructure using distributed, coordinated, power electronics control. One promising power electronics device, the Flexible AC Transmission System (FACTS), can modify power flow locally within a grid. Embedded computers within the FACTS devices, along with the links connecting them, form a communication and control network that can dynamically change the power grid to achieve higher dependability. The goal is to reroute power in the event of transmission line failure. Such a system, over a widespread area, is a cyber-physical system. The overall reliability of the grid is a function of the respective reliabilities of its two major subsystems, namely, the FACTS network and the physical components that comprise the infrastructure. This paper presents a mathematical model, based on the Markov chain imbeddable structure, for the overall reliability of the grid. The model utilizes a priori knowledge of reliability estimates for the FACTS devices and the communications links among them to predict the overall reliability of the power grid

The Advanced Electric Power Grid: Complexity Reduction Techniques for Reliability Modeling

The power grid is a large system, and analyzing its reliability is computationally intensive, rendering conventional methods ineffective. This paper proposes techniques for reducing the complexity of representations of the grid, resulting in a mathematically tractable problem to which our previously developed reliability analysis techniques can be applied. The IEEE118 bus system is analyzed as an example, incorporating cascading failure scenarios reported in the literature

Reliability Modeling for the Advanced Electric Power Grid: A Proposal for Doctoral Research

The advanced electric power grid is a cyber-physical system comprised of physical components such as power generators and transmission lines, and cyber components that control the operation of the grid. The objective of the proposed doctoral research is to develop a reliability model for the grid that reflects interdependencies among cyber and physical failures, through capturing the semantics of the system operation. We investigate several failure modes for devices that carry out cyber control of the grid, and examine the effect of their failure in terms of physical power flow in the grid. We propose the use of fault injection into the software of the cyber layer to refine the model, as well as the development of statistical methods to determine confidence levels for our model