Anthony Harrington

Cryptographic access control in a distributed file system

Traditional access control mechanisms rely on a reference monitor to mediate access to protected resources. Reference monitors are inherently centralized and existing attempts to distribute the functionality of the reference monitor suffer from problems of scalability.Cryptographic access control is a new distributed access control paradigm designed for a global federation of information systems. It defines an implicit access control mechanism, which relies exclusively on cryptography to provide confidentiality and integrity of data managed by the system. It is particularly designed to operate in untrusted environments where the lack of global knowledge and control are defining characteristics.The proposed mechanism has been implemented in a distributed file system, which is presented in this paper along with a preliminary evaluation of the proposed mechanism.

A framework for integrating existing and novel intelligent transportation systems

Efficient use and re-use of traffic data depends on an ITS architecture that enables information sharing across a wide variety of intelligent transportation systems and applications. Existing ITS architectures, such as KAREN or the national ITS architecture, can be used to develop systems within a given framework thereby facilitating such inter-system integration. However, these architectures typically include assumptions regarding the overall organization of system functionality that prohibit integration of previously deployed systems without major reengineering. This paper presents a framework for an ITS architecture that has been designed for integrating novel as well as existing intelligent transportation systems and applications. The iTransIT framework supports a number of possible systems interaction paradigms and proposes a layered data model to facilitate data exchange between systems with diverse service requirements and functional organizations. These data layers are defined within a common context model, may be distributed across multiple systems, and exploit the overlapping temporal and spatial aspects of information generated and used by both legacy and future systems.

Route profiling: putting context to work

Intelligent Transportation Systems are characterised by a requirement for detailed information on extensive transport networks. This information is typically gathered from sensors deployed throughout the network and is used for management and maintenance operations.In this paper we present the design and prototype implementation of a context-aware route profiling application intended for use by road management authorities in the Republic of Ireland. Our design allows data from a variety of sources to be combined to generate detailed information on traffic flow and journey times along the national road network. This information can be tagged with relevant context data reflecting the conditions under which sensor data was collected. The set of relevant contextual information includes details on temporal, spatial, weather and road usage pattern contexts.The prototype implementation relies on GPS data from a fleet of probe vehicles. An evaluation of this prototype is presented along with a discussion on the benefits of using context-aware computing techniques in a real world scenario.

Model-driven engineering of planning and optimisation algorithms for pervasive computing environments

This paper presents a model-driven approach to developing pervasive computing applications that exploits design-time information to support the engineering of planning and optimisation algorithms that reflect the presence of uncertainty, dynamism and complexity in the application domain. In particular the task of generating code to implement planning and optimisation algorithms in pervasive computing domains is addressed.

A spatial programming model for real global smart space applications

Global smart spaces are intended to provide their inhabitants with context-aware access to pervasive services and information relevant to large geographical areas. Transportation is one obvious domain for such global smart spaces since applications can be built to exploit the variety of sensor-rich systems that have been deployed to support urban traffic control and highway management as well as within individual vehicles. This paper presents a spatial programming model designed to provide a standardised way to build context-aware global smart space applications using information that is distributed across independent (legacy, sensor-enabled, and embedded) systems by exploiting the overlapping spatial and temporal attributes of the information maintained by these systems. The spatial programming model is based on a topographical approach to modelling space that enables systems to independently define and use potentially overlapping spatial context in a consistent manner and in contrast to topological approaches, in which geographical relationships between objects are described explicitly. Moreover, this approach facilitates the incremental construction of global smart spaces since the underlying systems to be incorporated are largely decoupled. The programming model has been evaluated by building a context-aware service for multi-modal urban journey planning, as part of the development of an overall architecture for intelligent transportation systems in Dublin.

Emergent consensus in decentralised systems using collaborative reinforcement learning

This paper describes the application of a decentralised coordination algorithm, called Collaborative Reinforcement Learning (CRL), to two different distributed system problems. CRL enables the establishment of consensus between independent agents to support the optimisation of system-wide properties in distributed systems where there is no support for global state. Consensus between interacting agents on local environmental or system properties is established through localised advertisement of policy information by agents and the use of advertisements by agents to update their local, partial view of the system. As CRL assumes homogeneity in advertisement evaluation by agents, advertisements that improve the system optimisation problem tend to be propagated quickly through the system, enabling the system to collectively adapt its behaviour to a changing environment. In this paper, we describe the application of CRL to two different distributed system problems, a routing protocol for ad-hoc networks called SAMPLE and a next generation urban traffic control system called UTC-CRL. We evaluate CRL experimentally in SAMPLE by comparing its system routing performance in the presence of changing environmental conditions, such as congestion and link unreliability, with existing ad-hoc routing protocols. Through SAMPLEs ability to establish consensus between routing agents on stable routes, even in the presence of changing levels of congestion in a network, it demonstrates improved performance and self-management properties. In applying CRL to the UTC scenario, we hope to validate experimentally the appropriateness of CRL to another system optimisation problem.

A framework for incremental construction of real global smart space applications

This article describes a standardised way to build context-aware global smart space applications using information that is distributed across independent (legacy, sensor-enabled, and embedded) systems by exploiting the overlapping spatial and temporal attributes of the information maintained by these systems. The framework supports a spatial programming model based on a topographical approach to modelling space that enables systems to independently define and use potentially overlapping spatial context in a consistent manner and in contrast to topological approaches, in which geographical relationships between objects are described explicitly. This approach is supported by an extensible data model that implicitly captures the relationships between information provided by separate underlying systems and facilitates the incremental construction of global smart spaces since the underlying systems to be incorporated are largely decoupled. The framework has been evaluated using a prototype that integrates legacy systems and context-aware services for multi-modal urban journey planning and for visualising traffic congestion.

Towards Delivering Context-Aware Transportation User Services

ITS architectures encourage integration of individual intelligent transportation systems into comprehensive platforms and enable sharing of information across a wide variety of systems and services. This paper presents a spatial programming model that has been designed as part of the iTransIT ITS framework to provide a standardized way to build value-added transportation user services and ultimately to deliver contextual transportation information to users. The spatial programming model is based on a topographical approach to modeling space that enables services to use potentially overlapping spatial context to correlate independently defined distributed information. This programming model has been evaluated by building a context-aware service for multi-modal urban journey planning

Domain Modelling for Ubiquitous Computing Applications

Many Ubiquitous computing applications can be considered as planning and acting problems in environments characterised by uncertainty and partial observability. Such systems rely on sensor data for information about their environment and use stochastic or probabilistic reasoning algorithms to infer system state from sensor data. We propose a domain modelling technique that characterises the sensor and actuator infrastructure and the set of system states in Ubicomp application domains. We capture the location and geometry of all domain model elements and use these spatial properties to tailor system state determination to reflect the quality and spread of the sensor and actuator platform. The domain model is used to support the development of Ubicomp applications and allows us calculate the degree of observability that exists over the state space in the environment. The degree of observability over the state space can act as an input into determining the state inference and action selection algorithms used in Ubicomp systems. In this paper we present the design of our Ubicomp domain model. We show that the proposed model contains information necessary to support Ubicomp application development. The expressiveness of the proposed design has been tested by building a model of an Urban Traffic Control application for Dublin city.