Scalable Storage for Digital Libraries

I propose a storage system optimised for digital libraries. Its key features are its heterogeneous scalability; its integration and exploitation of rich semantic metadata associated with digital objects; its use of a name space; and its aggressive performance optimisation in the digital library domain

Aviation System Analysis Capability Executive Assistant Design

In this technical document, we describe the design developed for the Aviation System Analysis Capability (ASAC) Executive Assistant (EA) Proof of Concept (POC). We describe the genesis and role of the ASAC system, discuss the objectives of the ASAC system and provide an overview of components and models within the ASAC system, and describe the design process and the results of the ASAC EA POC system design. We also describe the evaluation process and results for applicable COTS software. The document has six chapters, a bibliography, three appendices and one attachment

A flexible experimental laboratory for distributed generation networks based on power inverters

In the recently deregulated electricity market, distributed generation based on renewable sources is becoming more and more relevant. In this area, two main distributed scenarios are focusing the attention of recent research: grid-connected mode, where the generation sources are connected to a grid mainly supplied by big power plants, and islanded mode, where the distributed sources, energy storage devices, and loads compose an autonomous entity that in its general form can be named a microgrid. To conduct a successful research in these two scenarios, it is essential to have a flexible experimental setup. This work deals with the description of a real laboratory setup composed of four nodes that can emulate both scenarios of a distributed generation network. A comprehensive description of the hardware and software setup will be done, focusing especially in the dual-core DSP used for control purposes, which is next to the industry standards and able to emulate real complexities. A complete experimental section will show the main features of the system.Peer ReviewedPostprint (published version

Multi-agent based architecture for digital libraries

Digital Libraries (DL) generally contain a collection of independently maintained data sets, in different formats, which may be queried by geographically dispersed users. The general problem of managing such large digital data archives is particularly challenging when the system must cope with data which is processed on demand. This dissertation proposes a Multi-Agent System (MAS) architecture for the utilisation of an active DL that provides computing services in addition to data-retrieval services, so that users can initiate computing jobs on remote supercomputers for processing, mining, and filtering of the data in the library. The system architecture is based on a collaborative set of agents, where each agent undertakes a pre-defined role, and is responsible for offering a particular type of service. The integration of services is based on a user defined query which can range in complexity from simple queries, to specialised algorithms which are transmitted to image processing archives as mobile agents. The proposed architecture enables new information sources and services to be integrated into the system dynamically, supports autonomous and dynamic on-demand data processing based on collaboration between agents, capable of handling a large number of concurrent users. Focus is based on the management of mobile agents which roam through the servers that constitute the DL to serve user queries. A new load balancing scheme is proposed for managing agent load among the available servers, based on the system state information and predictions about lifetime of agent tasks and server status. The system architecture is further extended by defining a gateway to provide interoperability with other heterogeneous agent-based systems. Interoperability in this sense enables agents from different types of platforms to communicate between themselves and use services provided by other systems. The novelty of the proposed gateway approach lies in the ability to adapt an existing legacy system for use with the agent-based approach (and one that adheres to FIPA standards). A prototype has been developed as a proof-of-concept to outline the principles and ideas involved, with reference to the Synthetic Aperture Radar Atlas (SARA) DL composed of multi-spectral remote-sensing imagery of the Earth. Although, the work presented in this dissertation has been evaluated in the context of SARA DL, the proposed techniques suggest useful guidelines that may be employed by other active archival systems

Ray: A Distributed Execution Engine for the Machine Learning Ecosystem

In recent years, growing data volumes and more sophisticated computational procedures have greatly increased the demand for computational power. Machine learning and artificial intelligence applications, for example, are notorious for their computational requirements. At the same time, Moores law is ending and processor speeds are stalling. As a result, distributed computing has become ubiquitous. While the cloud makes distributed hardware infrastructure widely accessible and therefore offers the potential of horizontal scale, developing these distributed algorithms and applications remains surprisingly hard. This is due to the inherent complexity of concurrent algorithms, the engineering challenges that arise when communicating between many machines, the requirements like fault tolerance and straggler mitigation that arise at large scale and the lack of a general-purpose distributed execution engine that can support a wide variety of applications.In this thesis, we study the requirements for a general-purpose distributed computation model and present a solution that is easy to use yet expressive and resilient to faults. At its core our model takes familiar concepts from serial programming, namely functions and classes, and generalizes them to the distributed world, therefore unifying stateless and stateful distributed computation. This model not only supports many machine learning workloads like training or serving, but is also a good t for cross-cutting machine learning applications like reinforcement learning and data processing applications like streaming or graph processing. We implement this computational model as an open-source system called Ray, which matches or exceeds the performance of specialized systems in many application domains, while also offering horizontally scalability and strong fault tolerance properties

Application of Web Services to a Simulation Framework

The Joint Semi-Automated Forces (JSAF) simulator is an excellent tool for military training and a great testbed for new SAF behaviors. However, it has the drawback that behaviors must be ported into its own Finite State Machine (FSM) language. Web Services is a growing technology that seamlessly connects service providers to service consumers. This work attempts to merge these two technologies by modeling SAF behaviors as web services. The JSAF simulator is then modeled as a web service consumer. This approach allows new Semi-Automated Forces (SAF) behaviors to be developed independently of the simulator, which provides the developer with greater flexibility when choosing a programming language, development environment, and development platform. In addition to new SAF behaviors, this approach also supports any external component that can be modeled as a web service. Furthermore, these services are often run over a network, which distributes the computational load across several computers. Finally, hosting copies of a single service on several machines, a concept similar to file-sharing mirrors, offers an environment for load-balancing. This means if several entities are running the same behavior, a single server does not perform the computation for every entity. Instead, each entity is assigned to a specific server, increasing the quality of service seen by the system. A Web Services framework linking JSAF with several services is designed and implemented. Suppression of Enemy Air Defense (SEAD) behaviors written in MATLAB and a behavior recognition system are integrated with JSAF. These behaviors and the recognition tool were developed by other researchers, independent of this work. Results show that offloading computation to other machines is beneficial, especially when the simulation system is under heavy load. Preliminary results also indicate that load-balancing performs much better than using a single server