Declarative Data Analytics: a Survey

The area of declarative data analytics explores the application of the declarative paradigm on data science and machine learning. It proposes declarative languages for expressing data analysis tasks and develops systems which optimize programs written in those languages. The execution engine can be either centralized or distributed, as the declarative paradigm advocates independence from particular physical implementations. The survey explores a wide range of declarative data analysis frameworks by examining both the programming model and the optimization techniques used, in order to provide conclusions on the current state of the art in the area and identify open challenges.Comment: 36 pages, 2 figure

Extending the Finite Domain Solver of GNU Prolog

International audienceThis paper describes three significant extensions for the Finite Domain solver of GNU Prolog. First, the solver now supports negative integers. Second, the solver detects and prevents integer overflows from occurring. Third, the internal representation of sparse domains has been redesigned to overcome its current limitations. The preliminary performance evaluation shows a limited slowdown factor with respect to the initial solver. This factor is widely counterbalanced by the new possibilities and the robustness of the solver. Furthermore these results are preliminary and we propose some directions to limit this overhead

WSACT : a model for Web Services access control incorporating trust

Today, organisations that seek a competitive advantage are adopting virtual infrastructures that share and manage computing resources. The trend is towards implementing collaborating applications that are supported by web services technology. Even though web services technology is rapidly becoming a fundamental development paradigm, adequate security constitutes the main concern and obstacle to its adoption as an industry solution. An important issue to address is the development of suitable access control models that are able to not only restrict access to unauthorised users, but also to discriminate between users that originate from different collaborating parties. In web services environments, access control is required to cross the borders of security domains, in order to be implemented between heterogeneous systems. Traditional access control systems that are identity-based do not provide a solution, as web services providers have to deal with unknown users, manage a large user population, collaborate with others and at the same time be autonomous of nature. Previous research has pointed towards the adoption of attribute-based access control as a means to address some of these problems. This approach is still not adequate, as the trustworthiness of web services requestors cannot be determined. Trust in web services requestors is thus an important requirement to address. For this reason, the thesis investigated trust, as to promote the inclusion of trust in the web services access control model. A cognitive approach to trust computation was followed that addressed uncertain and imprecise information by means of fuzzy logic techniques. A web services trust formation framework was defined that aims to populate trust concepts by means of automated, machine-based trust assessments. The structure between trust concepts was made explicit by means of a trust taxonomy. This thesis presents the WSACT – or the Web Services Access Control incorporating Trust –model. The model incorporates traditional role-based access control, the trust levels of web services requestors and the attributes of users into one model. This allows web services providers to grant advanced access to the users of trusted web services requestors, in contrast to the limited access that is given to users who make requests through web services requestors with whom a minimal level of trust has been established. Such flexibility gives a web services provider the ability to foster meaningful business relationships with others, which portrays humanistic forms of trust. The WSACT architecture describes the interacting roles of an authorisation interface, authorisation manager and trust manager. A prototype finally illustrates that the incorporation of trust is a viable solution to the problem of web services access control when decisions of an autonomous nature are to be made.Thesis (PhD (Computer Science))--University of Pretoria, 2008.Computer Scienceunrestricte

Contelog: A Formal Declarative Framework for Contextual Knowledge Representation and Reasoning

Context-awareness is at the core of providing timely adaptations in safety-critical secure applications of pervasive computing and Artificial Intelligence (AI) domains. In the current AI and application context-aware frameworks, the distinction between knowledge and context are blurred and not formally integrated. As a result, adaptation behaviors based on contextual reasoning cannot be formally derived and reasoned about. Also, in many smart systems such as automated manufacturing, decision making, and healthcare, it is essential for context-awareness units to synchronize with contextual reasoning modules to derive new knowledge in order to adapt, alert, and predict. A rigorous formalism is therefore essential to (1) represent contextual domain knowledge as well as application rules, and (2) efficiently and effectively reason to draw contextual conclusions. This thesis is a contribution in this direction. The thesis introduces first a formal context representation and a context calculus used to build context models for applications. Then, it introduces query processing and optimization techniques to perform context-based reasoning. The formal framework that achieves these two tasks is called Contelog Framework, obtained by a conservative extension of the syntax and semantics of Datalog. It models contextual knowledge and infers new knowledge. In its design, contextual knowledge and contextual reasoning are loosely coupled, and hence contextual knowledge is reusable on its own. The significance is that by fixing the contextual knowledge, rules in the program and/or query may be changed. Contelog provides a theory of context, in a way that is independent of the application logic rules. The context calculus developed in this thesis allows exporting knowledge inferred in one context to be used in another context. Following the idea of Magic sets from Datalog, Magic Contexts together with query rewriting algorithms are introduced to optimize bottom-up query evaluation of Contelog programs. A Book of Examples has been compiled for Contelog, and these examples are implemented to showcase a proof of concept for the generality, expressiveness, and rigor of the proposed Contelog framework. A variety of experiments that compare the performance of Contelog with earlier Datalog implementations reveal a significant improvement and bring out practical merits of current stage of Contelog and its potential for future extensions in context representation and reasoning of emerging applications of context-aware computing