Exploring abstract interfaces in system-on-chip integration

Modern mobile devices are marvels of computation. They can encode high defnition video, processing and compressing over 350MB/s of image data in real time. They have no trouble driving displays with as much resolution as a full laptop, and smartphone manufacturers boast of running games with console quality graphics. Mobile devices pack all of this computational power into a 12\ handheld package by integrating a number of specialized hardware accelerators (IP) along with conventional CPU and GPUs in a system on chip (SoC). Unfortunately, creating these specialized systems is becoming increasingly expensive. Since hardware accelerators come from a number of different sources and design cycles, different accelerator blocks will often contain incompatible hardware interfaces. Therefore, a large portion of SoC design cost comes in the form of designers manually interfacing each accelerator into a system. This work includes everything from building custom logic to wire up a block, to developing the drivers and API needed to take advantage of the hardware. My research focuses on generating these interfaces, including the physical hardware used to tie IP blocks into a system and the associated software collateral. Leveraging recent trends such as High Level Synthesis and other hardware generator methodologies, I propose an IP interface abstraction and parameterization designed to describe the interface of most current IP blocks. By encoding this knowledge at a higher level of abstraction, I am able to construct and demonstrate a hardware generator that maps an interface protocol description into synthesizable register transfer language (RTL), and that can automatically create hardware bridges between different interconnect standards. iv To ease the integration of the next generation of IP blocks-blocks that are automatically generated based of of user specification. I propose a set of interface primitives. \hen integrated into an IP generator, these primitives can automatically generate an interface that my interface system can tie to the rest of the system. I also demonstrate how the information stored in these types of primitives can be used to automatically generate a low level software driver that manages access to the IP blocks. Finally, I show how the simulation environment provided with an IP generator can be used to provide a domain appropriate application programming interface (API) to drive the software. Using an image signal processor generator as my platform, I demonstrate the construction of a map between the simulation software and hardware driver that enables a full one-button flow from algorithm development to applications running on specialized hardware within a working system

Solution analysis of universal wireless joint point technologies for heterogeneous tactical networks

The scope of this thesis is to analyze the feasibility of having different wireless mesh network architectures transfer data to a wired network via a joint (universal) access point (UAP). Additionally this thesis analyzes the feasibility of using similar joint (universal) access point technology to allow heterogeneous wireless mesh network devices in close proximally to the UAP transmit data to/from each other via the UAP. This research also includes evaluating COTS tools for possible implementation of a joint access point as well as seeking partnership with private industry to assist in research efforts and/or the development or joint (universal) access point solution(s). The thesis concludes with a recommendation on application of universal joint point technology, to include recommendations for implementation of such technology in the Tactical Network Topology (TNT) environment.http://archive.org/details/solutionnalysiso109452951Approved for public release; distribution is unlimited

Portable Waveform Development for Software Defined Radios

This work focuses on the question: "How can we build waveforms that can be moved from one platform to another?\u27\u27 Therefore an approach based on the Model Driven Architecture was evaluated. Furthermore, a proof of concept is given with the port of a TETRA waveform from a USRP platform to an SFF SDR platform

Bootstrapping Cognitive Radio Networks

Cognitive radio networks promise more efficient spectrum utilization by leveraging degrees of freedom and distributing data collection. The actual realization of these promises is challenged by distributed control, and incomplete, uncertain and possibly conflicting knowledge bases. We consider two problems in bootstrapping, evolving, and managing cognitive radio networks. The first is Link Rendezvous, or how separate radio nodes initially find each other in a spectrum band with many degrees of freedom, and little shared knowledge. The second is how radio nodes can negotiate for spectrum access with incomplete information. To address the first problem, we present our Frequency Parallel Blind Link Rendezvous algorithm. This approach, designed for recent generations of digital front-ends, implicitly shares vague information about spectrum occupancy early in the process, speeding the progress towards a solution. Furthermore, it operates in the frequency domain, facilitating a parallel channel rendezvous. Finally, it operates without a control channel and can rendezvous anywhere in the operating band. We present simulations and analysis on the false alarm rate for both a feature detector and a cross-correlation detector. We compare our results to the conventional frequency hopping sequence rendezvous techniques. To address the second problem, we model the network as a multi-agent system and negotiate by exchanging proposals, augmented with arguments. These arguments include information about priority status and the existence of other nodes. We show in a variety of network topologies that this process leads to solutions not otherwise apparent to individual nodes, and achieves superior network throughput, request satisfaction, and total number of connections, compared to our baselines. The agents independently formulate proposals based upon communication desires, evaluate these proposals based upon capacity constraints, create ariii guments in response to proposal rejections, and re-evaluate proposals based upon received arguments. We present our negotiation rules, messages, and protocol and demonstrate how they interoperate in a simulation environment

A Hierarchical Architectural Framework for Securing Unmanned Aerial Systems

Unmanned Aerial Systems (UAS) are becoming more widely used in the new era of evolving technology; increasing performance while decreasing size, weight, and cost. A UAS equipped with a Flight Control System (FCS) that can be used to fly semi- or fully-autonomous is a prime example of a Cyber Physical and Safety Critical system. Current Cyber-Physical defenses against malicious attacks are structured around security standards for best practices involving the development of protocols and the digital software implementation. Thus far, few attempts have been made to embed security into the architecture of the system considering security as a holistic problem. Therefore, a Hierarchical, Embedded, Cyber Attack Detection (HECAD) framework is developed to provide security in a holistic manor, providing resiliency against cyber-attacks as well as introducing strategies for mitigating and dealing with component failures. Traversing the hardware/software barrier, HECAD provides detection of malicious faults at the hardware and software level; verified through the development of an FPGA implementation and tested using a UAS FCS

Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

This book presents the latest solutions in fuel cell (FC) and renewable energy implementation in mobile and stationary applications. The implementation of advanced energy management and optimization strategies are detailed for fuel cell and renewable microgrids, and for the multi-FC stack architecture of FC/electric vehicles to enhance the reliability of these systems and to reduce the costs related to energy production and maintenance. Cyber-security methods based on blockchain technology to increase the resilience of FC renewable hybrid microgrids are also presented. Therefore, this book is for all readers interested in these challenging directions of research

AI-based smart sensing and AR for gait rehabilitation assessment

Health monitoring is crucial in hospitals and rehabilitation centers. Challenges can affect the reliability and accuracy of health data. Human error, patient compliance concerns, time, money, technology, and environmental factors might cause these issues. In order to improve patient care, healthcare providers must address these challenges. We propose a non-intrusive smart sensing system that uses a SensFloor smart carpet and an inertial measurement unit (IMU) wearable sensor on the user’s back to monitor position and gait characteristics. Furthermore, we implemented machine learning (ML) algorithms to analyze the data collected from the SensFloor and IMU sensors. The system generates real-time data that are stored in the cloud and are accessible to physical therapists and patients. Additionally, the system’s real-time dashboards provide a comprehensive analysis of the user’s gait and balance, enabling personalized training plans with tailored exercises and better rehabilitation outcomes. Using non-invasive smart sensing technology, our proposed solution enables healthcare facilities to monitor patients’ health and enhance their physical rehabilitation plans.info:eu-repo/semantics/publishedVersio