abstract: Cyber Physical Systems (CPSs) are systems comprising of computational systems that interact with the physical world to perform sensing, communication, computation and actuation. Common examples of these systems include Body Area Networks (BANs), Autonomous Vehicles (AVs), Power Distribution Systems etc. The close coupling between cyber and physical worlds in a CPS manifests in two types of interactions between computing systems and the physical world: intentional and unintentional. Unintentional interactions result from the physical characteristics of the computing systems and often cause harm to the physical world, if the computing nodes are close to each other, these interactions may overlap thereby increasing the chances of causing a Safety hazard. Similarly, due to mobile nature of computing nodes in a CPS planned and unplanned interactions with the physical world occur. These interactions represent the behavior of a computing node while it is following a planned path and during faulty operations. Both of these interactions change over time due to the dynamics (motion) of the computing node and may overlap thereby causing harm to the physical world. Lack of proper modeling and analysis frameworks for these systems causes system designers to use ad-hoc techniques thereby further increasing their design and development time. The thesis addresses these problems by taking a holistic approach to model Computational, Physical and Cyber Physical Interactions (CPIs) aspects of a CPS and proposes modeling constructs for them. These constructs are analyzed using a safety analysis algorithm developed as part of the thesis. The algorithm computes the intersection of CPIs for both mobile as well as static computing nodes and determines the safety of the physical system. A framework is developed by extending AADL to support these modeling constructs; the safety analysis algorithm is implemented as OSATE plug-in. The applicability of the proposed approach is demonstrated by considering the safety of human tissue during the operations of BAN, and the safety of passengers traveling in an Autonomous Vehicle. / Dissertation/Thesis / M.S. Computer Science 2010

abstract: Energy efficient design and management of data centers has seen considerable interest in the recent years owing to its potential to reduce the overall energy consumption and thereby the costs associated with it. Therefore, it is of utmost importance that new methods for improved physical design of data centers, resource management schemes for efficient workload distribution and sustainable operation for improving the energy efficiency, be developed and tested before implementation on an actual data center. The BlueTool project, provides such a state-of-the-art platform, both software and hardware, to design and analyze energy efficiency of data centers. The software platform, namely GDCSim uses cyber-physical approach to study the physical behavior of the data center in response to the management decisions by taking into account the heat recirculation patterns in the data center room. Such an approach yields best possible energy savings owing to the characterization of cyber-physical interactions and the ability of the resource management to take decisions based on physical behavior of data centers. The GDCSim mainly uses two Computational Fluid Dynamics (CFD) based cyber-physical models namely, Heat Recirculation Matrix (HRM) and Transient Heat Distribution Model (THDM) for thermal predictions based on different management schemes. They are generated using a model generator namely BlueSim. To ensure the accuracy of the thermal predictions using the GDCSim, the models, HRM and THDM and the model generator, BlueSim need to be validated experimentally. For this purpose, the hardware platform of the BlueTool project, namely the BlueCenter, a mini data center, can be used. As a part of this thesis, the HRM and THDM were generated using the BlueSim and experimentally validated using the BlueCenter. An average error of 4.08% was observed for BlueSim, 5.84% for HRM and 4.24% for THDM. Further, a high initial error was observed for transient thermal prediction, which is due to the inability of BlueSim to account for the heat retained by server components. / Dissertation/Thesis / M.S. Mechanical Engineering 2012

Cyber-physical systems (CPS) are systems that are composed of physical and computational components. CPS components are typically interconnected through a communication network that allows components to interact and take automated actions that are beneficial for the overall CPS. Future Power-Grid is one of the major example of Cyber-physical systems. Traditionally, Power-Grids use a centralized approach to manage the energy produced at power sources or large power plants. Due to the advancement and availability of renewable energy sources such as wind farms and solar systems, there are more number of energy sources connecting to the power grid. Managing these large number of energy sources using a centralized technique is not practical and is computationally very expensive. Therefore, a decentralized way of monitoring and scheduling of energy across the power grid is preferred. In a decentralized approach, computational load is distributed among the grid entities that are interconnected through a readily available communication network like internet. The communication network allows the grid entities to coordinate and exchange their power state information with each other and take automated actions that lead to efficient consumption of energy as well as the network bandwidth. Thus, the future power grid is appropriately called a "Smart-Grid". While Smart-Grids provide efficient energy operations, they also impose several challenges in the design, verification and monitoring phases. The computer network serves as a backbone for scheduling messages between the Smart-Grid entities. Therefore, network delays experienced by messages play a vital role in grid stability and overall system performance. In this work, we study the effects of network delays on Smart-Grid performance and propose adaptive algorithms to efficiently schedule messages between the grid entities. Algorithms proposed in this work also ensure the grid stability and perform network congestion control. Through this work, we derive useful conclusions regarding the Smart-Grid performance and find new challenges that can serve as future research directions in this domain.

abstract: There has been exciting progress in the area of Unmanned Aerial Vehicles (UAV) in the last decade, especially for quadrotors due to their nature of easy manipulation and simple structure. A lot of research has been done on achieving autonomous and robust control for quadrotors. Recently researchers have been utilizing linear temporal logic as mission specification language for robot motion planning due to its expressiveness and scalability. Several algorithms have been proposed to achieve autonomous temporal logic planning. Also, several frameworks are designed to compose those discrete planners and continuous controllers to make sure the actual trajectory also satisfies the mission specification. However, most of these works use first-order kinematic models which are not accurate when quadrotors fly at high speed and cannot fully utilize the potential of quadrotors. This thesis work describes a new design for a hierarchical hybrid controller that is based on a dynamic model and seeks to achieve better performance in terms of speed and accuracy compared with some previous works. Furthermore, the proposed hierarchical controller is making progress towards guaranteed satisfaction of mission specification expressed in Linear Temporal Logic for dynamic systems. An event-driven receding horizon planner is also utilized that aims at distributed and decentralized planning for large-scale navigation scenarios. The benefits of this approach will be demonstrated using simulations results. / Dissertation/Thesis / Masters Thesis Computer Science 2016

Computational power of mobile devices has been continuously improving in the recent years. One of the benefits which it brings, is feasibility of new kinds of distributed systems, such as Ensemble-Based Component Systems (EBCS). For practical reasons, EBCS systems are usually tested using simulations before being released. However, it can be difficult to interpret the simulation output, as it is usually contained in XML format, which is more suited to be read by machines than by people. We provide a visualizing application, which creates a graphical representation of such a simulation output. Out of the box, it is able to visualize data from applications built on top of the JDEECo component model, but it can be easily modified to accept output from different EBCS applications. It is able to visualize both components and ensembles and provides a scripting interface to modify the graphical output. In addition, it has an extensibility mechanism for adding new functionalities. Our benchmarking shows that the application is expected to run reasonably fast in typical scenarios.

The cyber-physical systems (CPS), such as smart grid and intelligent transportation system, permeate into our modern societies recently. The infrastructures in such systems are closely interconnected and related, e.g., the intelligent transportation system is based on the reliable communication system, which requires the stable electricity provided by power grid for the proper function. We call such mutually related systems interdependent networks. This thesis addresses the cascading failure issue in interdependent cyber physical system. We consider CPS as a system that consists of physical-resource and computational-resource networks. The failure in physical-resource network might cause the failures in computational-resource network, and vice versa. This failure may recursively occur and cause a sequence of failures in both networks. In this thesis, we propose two novel interdependence models that better capture the interdependent networks. Then, we study the effect of cascading failures using percolation theory and present the detailed mathematical analysis on failure propagation in the system. By calculating the size of functioning parts in both networks, we analyze the robustness of our models against the random attacks and failures. The cascading failures in smart grid is also investigated, where two types of cascading failures are mixed. We estimate how the node tolerance parameter T (ratio of capacity to initial workload) affect the system performance. This thesis also explores the small clusters. We give insightful views on small cluster in interdependent networks, under different interdependence models and network topologies.

The conceptual evolution of smart cities is highly motivated by the advancement of information and communication technologies (ICTs). The purpose of a smart city is to facilitate the best quality of life to its inhabitants. Its implementation has to be supported by the compliant utilities and networked infrastructures. In the current world, it can only be achieved by applying ICTs in an extensive manner. The move towards the smart city's seamless connectivity widens the scope of cyber security concerns. Smart city infrastructures to face a high risk of targeted attacks due to extended cyber-physical vulnerabilities. This creates many challenging research issues relevant to the design and implementation of cyber security solutions. Networks associated with city infrastructures vary from a small indoor one to a large geographically distributed one. The context of a network is an essential consideration for security solutions. This thesis investigates a set of optimal security placement problems for enhancing monitoring in smart city infrastructures. It develops solutions to such placement problems from a resource management perspective. Economy and quality-of-security service (QoSS) are two major design goals. Such goals are translated into three basic performance metrics: (i) coverage, (ii) tolerance, and (iii) latency. This thesis studies security placement problems pertaining to three different types of networks: (i) wireless sensor network (WSN), (ii) supervisory control and data acquisition (SCADA) backbone, and (iii) advanced metering infrastructure (AMI) wide area network (WAN). In a smart city, WSNs are deployed to support real time monitoring and safety alert (RTMSA) applications. They are highly resource constrained networks. For WSNs, placement problems for an internally configured security monitor named watchdog have been studied. On the other hand, a smart grid is a key driver for smart cities. SCADA and AMI are two major components of a smart grid. They are associated with two different types of geographically distributed networks. For SCADA backbones, placement problems for a specially designed security device named trust system have been studied. For AMI-WANs, placement problems for a cloud-based managed security service have been studied. This thesis proposes a number of promising solution schemes to such placement problems. It includes evaluation results that demonstrate the enhancements of the proposed schemes.

Cyber-Physical Systems (CPS) are physical entities whose operations are monitored, coordinated, and controlled by a computing and communication core. These systems are highly heterogeneous and complex. Their numerous components and cross domain complexity make attacks easy to propagate and security difficult to implement. Consequently, to secure these systems, they need to be built in a systematic and holistic way, where security is an integral part of the development lifecycle and not just an activity after development. These systems present a multitude of implementation details in their component units, so it is fundamental to use abstraction in the analysis and construction of their architecture. In particular, we can apply abstraction through the use of patterns. Pattern-based architectural modeling is a powerful way to describe the system and analyze its security and the other non-functional aspects. Patterns also have the potential to unify the design of their computational, communication, and control aspects. Architectural modeling can be performed through UML diagrams to show the interactions and dependencies between different components and its stakeholders. Also, it can be used to analyze security threats and describe the possible countermeasures to mitigate these threats. An important type of CPS is a maritime container terminal, a facility where cargo containers are transported between ships and land vehicles; for example, trains or trucks, for onward transportation, and vice versa. Every cargo port performs four basic functions: receiving, storing, staging and loading for both, import and export containers. We present here a set of patterns that describe the elements and functions of a cargo port system, and a Reference Architecture (RA) built using these patterns. We analyze and systematically enumerate the possible security threats to a container terminal in a cargo port using activity diagrams derived from selected use cases of the system. We describe these threats using misuse patterns, and from them select security patterns as defenses. The RA provides a framework to determine where to add these security mechanisms to stop or mitigate these threats and build a Security Reference Architecture (SRA) for CPS. An SRA is an abstract architecture describing a conceptual model of security that provides a way to specify security requirements for a wide range of concrete architectures. The analysis and design are given using a cargo port as our example, but the approach can be used in other domains as well. This is the first work we know where patterns and RAs are used to represent cargo ports and analyze their security. / Includes bibliography. / Dissertation (PhD)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

Cyber-physical systems (CPS), integrating advanced computation, communication, and control technologies with the physical process, are widely applied in industry applications such as smart production and manufacturing systems, robotic and automotive control systems, and smart grids. Due to possible exposure to unreliable networks and complex physical environments, CPSs may simultaneously face multiple cyber and physical issues including cyber threats (e.g., malicious cyber attacks) and resource constraints (e.g., limited networking resources and physical constraints). As one of the essential topics in designing efficient CPSs, the controller design for CPSs, aiming to achieve secure and resource-aware control objectives under such cyber and physical issues, is very significant yet challenging. Emphasizing optimality and system constraint handling, model predictive control (MPC) is one of the most widely used control paradigms, notably famous for its successful applications in chemical process industry. However, the conventional MPC methods are not specifically tailored to tackle cyber threats and resource constraints, thus the corresponding theory and tools to design the secure and resource-aware controller are lacking and need to be developed. This dissertation focuses on developing MPC-based methodologies to address the i) secure control problem and ii) resource-aware control problem for CPSs subject to cyber threats and resource constraints. In the resource-aware control problem of CPSs, the nonlinear system with additive disturbance is considered. By using an integral-type event-triggered mechanism and an improved robustness constraint, we propose an integral-type event-triggered MPC so that smaller sampling frequency and robustness to the additive disturbance can be obtained. The sufficient conditions for guaranteeing the recursive feasibility and the closed-loop stability are established. For the secure control problem of CPSs, two aspects are considered. Firstly, to achieve the secure control objective, we design a secure dual-mode MPC framework, including a modified initial feasible set and a new positively invariant set, for constrained linear systems subject to Denial-of-Service (DoS) attacks. The exponential stability of the closed-loop system is guaranteed under several conditions. Secondly, to deal with cyber threats and take advantage of the cloud-edge computing technology, we propose a model predictive control as a secure service (MPCaaSS) framework, consisting of a double-layer controller architecture and a secure data transmission protocol, for constrained linear systems in the presence of both cyber threats and external disturbances. The rigorous recursive feasibility and robust stability conditions are established. To simultaneously address the secure and resource-aware control problems, an event-triggered robust nonlinear MPC framework is proposed, where a new robustness constraint is introduced to deal with additive disturbances, and a packet transmission strategy is designed to tackle DoS attacks. Then, an event-triggered mechanism, which accommodates DoS attacks occurring in the communication network, is proposed to reduce the communication cost for resource-constrained CPSs. The recursive feasibility and the closed-loop stability in the sense of input-to-state practical stable (ISpS) are guaranteed under the established sufficient conditions. / Graduate

When designing a complex Cyber-Physical System it is often impossible to foresee all potential situations in advance and prepare corresponding tactics to adapt to the changes in dynamic environment. This greatly hurts the system's resilience and dependability. All kinds of trouble can rise from situations that lie beyond the expected "envelope of adaptability" from malfunction of one component to failure of the whole system. Self-adaptation approaches are typically limited in choosing a tactic from a fixed set of tactics. Meta-adaptation strategies extend the limits of system's inherent adaptation by creating new tactics at runtime. This thesis elaborates and provides implementations of selected meta-adaptation strategies for IRM-SA in jDEECo as well as their evaluation in a scenario based on a firefighter coordination case study. Powered by TCPDF (www.tcpdf.org)