Architecting system of systems: artificial life analysis of financial market behavior

This research study focuses on developing a framework that can be utilized by system architects to understand the emergent behavior of system architectures. The objective is to design a framework that is modular and flexible in providing different ways of modeling sub-systems of System of Systems. At the same time, the framework should capture the adaptive behavior of the system since evolution is one of the key characteristics of System of Systems. Another objective is to design the framework so that humans can be incorporated into the analysis. The framework should help system architects understand the behavior as well as promoters or inhibitors of change in human systems. Computational intelligence tools have been successfully used in analysis of Complex Adaptive Systems. Since a System of Systems is a collection of Complex Adaptive Systems, a framework utilizing combination of these tools can be developed. Financial markets are selected to demonstrate the various architectures developed from the analysis framework --Introduction, page 3

Creating an Agent Based Framework to Maximize Information Utility

With increased reliance on communications to conduct military operations, information centric network management becomes vital. A Defense department study of information management for net-centric operations lists the need for tools for information triage (based on relevance, priority, and quality) to counter information overload, semi-automated mechanisms for assessment of quality and relevance of information, and advances to enhance cognition and information understanding in the context of missions [30]. Maximizing information utility to match mission objectives is a complex problem that requires a comprehensive solution in information classification, in scheduling, in resource allocation, and in QoS support. Of these research areas, the resource allocation mechanism provides a framework to build the entire solution. Through an agent based mindset, the lessons of robot control architecture are applied to the network domain. The task of managing information flows is achieved with a hybrid reactive architecture. By demonstration, the reactive agent responds to the observed state of the network through the Unified Behavior Framework (UBF). As information flows relay through the network, agents in the network nodes limit resource contention to improve average utility and create a network with smarter bandwidth utilization. While this is an important result for information maximization, the agent based framework may have broader applications for managing communication networks

Modeling network traffic on a global network-centric system with artificial neural networks

This dissertation proposes a new methodology for modeling and predicting network traffic. It features an adaptive architecture based on artificial neural networks and is especially suited for large-scale, global, network-centric systems. Accurate characterization and prediction of network traffic is essential for network resource sizing and real-time network traffic management. As networks continue to increase in size and complexity, the task has become increasingly difficult and current methodology is not sufficiently adaptable or scaleable. Current methods model network traffic with express mathematical equations which are not easily maintained or adjusted. The accuracy of these models is based on detailed characterization of the traffic stream which is measured at points along the network where the data is often subject to constant variation and rapid evolution. The main contribution of this dissertation is development of a methodology that allows utilization of artificial neural networks with increased capability for adaptation and scalability. Application on an operating global, broadband network, the Connexion by Boeingʼ network, was evaluated to establish feasibility. A simulation model was constructed and testing was conducted with operational scenarios to demonstrate applicability on the case study network and to evaluate improvements in accuracy over existing methods --Abstract, page iii

Proceedings, MSVSCC 2013

Proceedings of the 7th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 11, 2013 at VMASC in Suffolk, Virginia

Advanced Primary Controllers for Inverter Based Power Sources: Microgrids and Wind Power Plants

The aim of this doctoral thesis is to present the research activity fulfilled during the Ph.D. studies. The research project of the candidate was focused on two main cores. The first core is centred in the microgrid area; in particular in islanded microgrid modelling and control. Firstly, the model was compared with experimental results collected in some facilities available at University of Genoa. Then traditional controllers for islanded microgrid are analysed and explored, proposing a new stability estimation procedure for droop controlled microgrid. Finally, a new control strategy based on Model Predictive Control (MPC) is proposed in order to collect many functionalities in just one control layer. MPC is widely used in MG environment, but just for power and energy management at tertiary level; instead here it is here proposed with an inedited use. Some experimental validations about this new methodology are obtained during a research period in Serbia and Denmark. The second core is related with synthetic inertia for wind turbine connected to the main grid, i.e. frequency support during under-frequency transients. This aspect is very important today because it represents a way to increase grid stability in low inertia power systems. The importance of this feature is shared by all the most important Transmitter System Operators (TSO) all over the world

The AFIT ENgineer, Volume 5, Issue 2

In this issue: Quantum information science (QIS) research at AFIT Engineers Week Returns to AFIT AFIT Joins U.S. Space Command’s Academic Engagement Enterprise Digital Innovation and Integration Center of Excellence (DIICE) FY22 External Sponsor Funding summar

SUPPORTING MISSION PLANNING WITH A PERSISTENT AUGMENTED ENVIRONMENT

Includes supplementary materialIncludes Supplementary MaterialThe Department of the Navy relies on current naval practices such as briefs, chat, and voice reports to provide an overall operational assessment of the fleet. That includes the cyber domain, or battlespace, depicting a single snapshot of a ship’s network equipment and service statuses. However, the information can be outdated and inaccurate, creating confusion among decision-makers in understanding the service and availability of equipment in the cyber domain. We examine the ability of a persistent augmented environment (PAE) and 3D visualization to support communications and cyber network operations, reporting, and resource management decision-making. We designed and developed a PAE prototype and tested the usability of its interface. Our study examined users’ comprehension of 3D visualization of the naval cyber battlespace onboard multiple ships and evaluated the PAE’s ability to assist in effective mission planning at the tactical level. The results are highly encouraging: the participants were able to complete their tasks successfully. They found the interface easy to understand and operate, and the prototype was characterized as a valuable alternative to their current practices. Our research provides close insights into the feasibility and effectiveness of the novel form of data representation and its capability to support faster and improved situational awareness and decision-making in a complex operational technology (OT) environment between diverse communities.Lieutenant, United States NavyLieutenant, United States NavyApproved for public release. Distribution is unlimited

Space station data system analysis/architecture study. Task 2: Options development, DR-5. Volume 2: Design options

The primary objective of Task 2 is the development of an information base that will support the conduct of trade studies and provide sufficient data to make key design/programmatic decisions. This includes: (1) the establishment of option categories that are most likely to influence Space Station Data System (SSDS) definition; (2) the identification of preferred options in each category; and (3) the characterization of these options with respect to performance attributes, constraints, cost and risk. This volume contains the options development for the design category. This category comprises alternative structures, configurations and techniques that can be used to develop designs that are responsive to the SSDS requirements. The specific areas discussed are software, including data base management and distributed operating systems; system architecture, including fault tolerance and system growth/automation/autonomy and system interfaces; time management; and system security/privacy. Also discussed are space communications and local area networking