It has been proofed that Reconfigurable Computing System possesses the potential to promote system efficiency. Fine-Grain Reconfigurable Computing System, which integrates the co-design of software and hardware, is the prevailing current in system designing with low clock rate and high efficiency. The thesis focuses on computing-oriented Fine-Grain Reconfigurable Computing System of software-hardware interwork, and setting up invoking working model for software program and hardware module as well. The designing of software and hardware can be integrated into one program, which deals with the hardware as a function. By quick computing of hardware, it can promote system efficiency. This interwork mechanism can be combined into traditional instruction execute pipeline. It composes manageable Fine-Grain for Reconfigurable Computing System as a new processor architecture, which brings up new command to support execution of software-hardware interwork mechanism. The model architecture is verified by algorithms of multimedia application, such as Motion Estimation and DCT. In addition, it presents the optimizing model by analysis and comparison of software and hardware efficiency.

At present the scale of multimedia and communication systems has become more and more complicated due to the fast development of them. In order to improve the capability of real-time processing and shorten system development time, the ability to reconfigure system architecture becomes an important and flexible design consideration. In this thesis, we propose a reconfigurable processing unit, FMRPU, which is a fine-grain multi-context reconfigurable processing unit targeting at high-throughput and data-parallel applications. It contains 64 reconfigurable logic arrays, 16 switch boxes, and connects with each other via three hierarchical-level connectivities. To avoid the excessive routing path to be the bottleneck of mapped circuits, we design the data stream switch to rearrange data streams. According to the simulation results, the longest routing path of FMRPU only takes 6.5 ns at 0.35 processes, which is able to construct the required logic circuit efficiently. Compare with same kind devices in dealing with Motion Estimation operations, the performance is raise to 17% and is excellent to other same kind architectures in executing other DSP algorithms.

Reconfigurable computing systems require supports from powerful computer aided design tools to help users developing the interactions between software programs and hardware circuits. The placement and routing support for reconfigurable processing units is also the key to the efficiency of the computing system. In this thesis, we implemented the placement and routing tool for the FMRPU (Fine-grain Multi-context Reconfigurable Processing Unit). The routing resource among the Logic Arrays supports only 8-bit aligned data width, so the routing of the FMRPU can¡¦t completely imitate from the pattern used by LUT-based routing. Thus we proposed an operation-based design model which accepts a data flow graph that describes the operations of the circuit. After compressing the graph, the tool uses Simulated Annealing algorithm with either Maze Route or Center-of-Gravity Route to map the compressed graph into FMRPU. Through the placement and routing tool we implemented, we have successfully mapped several algorithms used in multi-media applications, such as FFT and DCT, into FMRPU.

This Diploma Thesis introduces the basic concepts of reputation and trust, reputation systems and problems of multi-contextual models of reputation. It also describes practical aspects of multi-contextual models in web environment. Described contextual models are then used for design and implementation of real web application.

The field of artificial intelligence, research on knowledge representation and reasoning has originated a large variety of formats, languages, and formalisms. Over the decades many different tools emerged to use these underlying concepts. Each one has been designed with some specific application in mind and are even used nowadays, where the internet is seen as a service to be sufficient for the age of Industry 4.0 and the Internet of Things. In that vision of a connected world, with these many different formalisms and systems, a formal way to uniformly exchange information, such as knowledge and belief is imperative. That alone is not enough, because even more systems get integrated into the online world and nowadays we are confronted with a huge amount of continuously flowing data. Therefore a solution is needed to both, allowing the integration of information and dynamic reaction to the data which is provided in such continuous data-flow environments. This work aims to present a unique and novel pair of formalisms to tackle these two important needs by proposing an abstract and general solution. We introduce and discuss reactive Multi-Context Systems (rMCS), which allow one to utilise different knowledge representation formalisms, so-called contexts which are represented as an abstract logic framework, and exchange their beliefs through bridge rules with other contexts. These multiple contexts need to mutually agree on a common set of beliefs, an equilibrium of belief sets. While different Multi-Context Systems already exist, they are only solving this agreement problem once and are neither considering external data streams, nor are they reasoning continuously over time. rMCS will do this by adding means of reacting to input streams and allowing the bridge rules to reason with this new information. In addition we propose two different kind of bridge rules, declarative ones to find a mutual agreement and operational ones for adapting the current knowledge for future computations. The second framework is more abstract and allows computations to happen in an asynchronous way. These asynchronous Multi-Context Systems are aimed at modelling and describing communication between contexts, with different levels of self-management and centralised management of communication and computation. In this thesis rMCS will be analysed with respect to usability, consistency management, and computational complexity, while we will show how asynchronous Multi-Context Systems can be used to capture the asynchronous ideas and how to model an rMCS with it. Finally we will show how rMCSs are positioned in the current world of stream reasoning and that it can capture currently used technologies and therefore allows one to seamlessly connect different systems of these kinds with each other. Further on this also shows that rMCSs are expressive enough to simulate the mechanics used by these systems to compute the corresponding results on its own as an alternative to already existing ones. For asynchronous Multi-Context Systems, we will discuss how to use them and that they are a very versatile tool to describe communication and asynchronous computation.

A distinctive feature of run-time reconfigurable systems is the ability to change the configuration of programmable resources during execution. This opens a number of possibilities such as virtualisation of computational resources, simplified routing and in certain applications lower power. Seamless run-time reconfiguration requires rapid configuration. Commodity programmable devices have relatively long configuration time, which makes them poor candidates for run-time reconfigurable systems. Reducing this reconfiguration time to the order of nano seconds will enable rapid run-time reconfiguration. Having multiple configuration planes and switching between them while processing data is one approach towards achieving rapid reconfiguration. An experimental context switching programmable device, called the Context Switching Reconfigurable Computer (CSRC), has been created by BAE Systems, which provided opportunities to explore context-switching strategies for run-time reconfigurable systems. The work presented here studies this approach for run-time reconfiguration, by applying the concepts to develop applications on a context switching reconfigurable system. The work also discusses the advantages and disadvantages of such an approach and ways of leveraging the concept for efficient computing. / Master of Science

This Ph.D. thesis deals with trust modelling for distributed systems especially to multi-context trust modelling for multi-agent distributed systems. There exists many trust and reputation models but most of them do not dealt with the multi-context property of trust or reputation. Therefore, the main focus of this thesis is on analysis of multi-context trust based models and provides main assumptions for new fully multi-contextual trust model on the bases of them. The main part of this thesis is in providing new formal multi-context trust model which are able to build, update and maintain trust value for different aspects (contexts) of the single entity in the multi-agent system. In our proposal, trust value can be built on the bases of direct interactions or on the bases on recommendations and reputation. Moreover we assume that some context of one agent is not fully independent and on the bases of trust about one of them we are able to infer trust to another's. Main contribution of this new model is increasing the efficiency in agent decision making in terms of optimal partner selection for interactions. Proposed model was verified by implementing prototype of multi-agent system when trust was used for agents' decision making and acting.