PriCL: Creating a Precedent A Framework for Reasoning about Privacy Case Law

We introduce PriCL: the first framework for expressing and automatically reasoning about privacy case law by means of precedent. PriCL is parametric in an underlying logic for expressing world properties, and provides support for court decisions, their justification, the circumstances in which the justification applies as well as court hierarchies. Moreover, the framework offers a tight connection between privacy case law and the notion of norms that underlies existing rule-based privacy research. In terms of automation, we identify the major reasoning tasks for privacy cases such as deducing legal permissions or extracting norms. For solving these tasks, we provide generic algorithms that have particularly efficient realizations within an expressive underlying logic. Finally, we derive a definition of deducibility based on legal concepts and subsequently propose an equivalent characterization in terms of logic satisfiability.Comment: Extended versio

An Architectural Approach to Ensuring Consistency in Hierarchical Execution

Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. This work shows how the combination of a hierarchy and persistent assertions of knowledge can lead to difficulty in maintaining logical consistency in asserted knowledge. We explore the problematic consequences of persistent assumptions in the reasoning process and introduce novel potential solutions. Having implemented one of the possible solutions, Dynamic Hierarchical Justification, its effectiveness is demonstrated with an empirical analysis

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Scalable Reliable SD Erlang Design

This technical report presents the design of Scalable Distributed (SD) Erlang: a set of language-level changes that aims to enable Distributed Erlang to scale for server applications on commodity hardware with at most 100,000 cores. We cover a number of aspects, specifically anticipated architecture, anticipated failures, scalable data structures, and scalable computation. Other two components that guided us in the design of SD Erlang are design principles and typical Erlang applications. The design principles summarise the type of modifications we aim to allow Erlang scalability. Erlang exemplars help us to identify the main Erlang scalability issues and hypothetically validate the SD Erlang design