Paul Malone

Flexible Charging for Multi-provider Composed Services using a Federated, Two-phase Rating Process

We present a framework enabling charging for composed services comprised of services offered by multiple providers. In the framework rating engines may generate charge information for individual services and provide this information upon request to other rating engines when these services are used as part of a composed service. Rating engines additionally employ a two-phase rating process which allows potentially complex business agreements between providers to be reflected in composed service charges. Charges can vary depending on the context in which a service is executed, for example, as part of a composed service which includes services offered by a partner provider. Crucially, the process allows rating engines to calculate these varying charges without having to be manually pre-configured with details of the structure of individual composed services. In the paper we provide an overview of the framework, specifying in detail the rating process and inter-rating engine communications, and describe via an example its deployment in a distributed environment supporting the execution of composed services

INTERMON: an architecture for inter-domain monitoring, modelling and simulation

In this paper we present a flexible architecture providing a communication platform between heterogeneous components for inter-domain QoS and traffic analysis in large-scale, multi-domain Internet infrastructures.

Personal cloudlets: implementing a user-centric datastore with privacy aware access control for cloud-based data platforms

This paper presents OPENis Personal Cloudlets framework as a novel approach to enhancing users control and privacy over their data on a data driven, cloud-based platform. We introduce the EU FP7 funded project OPENi, the OPENi concept, and the research objectives that influenced the design and implementation of OPENis Personal Cloudlet Framework. We outline OPENis architecture and describe how through the use of REST based endpoints, object-based access control, OPENi Types, and stateless JSON Web Token (JWT) it allows users share, reuse, and control access to their data across many mobile applications while maintaining cloud scalability. Furthermore we describe how a number of the Personal Cloudlet Frameworks features enhance a users privacy and control, including: the User Dashboard, the Privacy Preserving Data Aggregator, and the fine grained access control mechanism.

A Model for identity in digital ecosystems

In digital ecosystems, where they are no central authorities or single points of failure or control, entities form dynamic relationships to facilitate transactions and knowledge sharing. These relationships are contextual, evolving and not subject to central moderation. The devolved structure of these emergent environments pose unique challenges for identity. In this paper, we build on previous work on identity in digital ecosystems by offering a closer examination of identity requirements and outlining a flexible and extensible identity model framework that uses OASIS SAML-like protocols and metadata to perform the equivalent of operations such as Single Sign-On (SSO). We also introduce an identity model software toolkit, IdentityFlow, that can be used to implement and execute identity protocols; and outline concrete use-cases for SSO protocol implementations.

Distributed accountability model for digital ecosystems

Successful uptake of digital ecosystems requires trust in the underlying platform and in the users of that platform. Accountability mechanisms provide a basis for creating, monitoring and evolving trust. This work analyses the requirements for accountability in digital ecosystems and proposes an accountability model for deployment of digital ecosystems in peer-to-peer networks.

A Distributed Transaction and Accounting Model for Digital Ecosystem Composed Services

This paper addresses two known issues for dynamically composed services in digital ecosystems. The first issue is that of efficient distributed transaction management. The conventional view of transactions is unsuitable as the local autonomy of the participants is vital for the involvement of SMEs. The second issue is that of charging for such distributed transactions, where there will often be dynamically created services whose composition is not known in advance and might involve parts of different transactions. The paper provides solutions for both of these issues, which can be combined to provide for a unified approach to transaction management and accounting of dynamically composed services in digital ecosystems.

Analysis and Representation of Biomedical data with Concept Lattice

As the progress in biology and medical science, especially in DNA technology, large amounts of biomedical data continue to grow inexorably in size, dimension and complexity. We need to develop more scalable and more efficient techniques and methods to analyze and represent the large and high-dimensional biomedical data sets. Formal concept analysis (FCA) is an effective tool for data analysis and knowledge discovery. Concept lattice, which is derived from mathematical order theory and lattice theory, is the core of FCA. Many research works of various areas show that concept lattice structure is an effective platform for data mining, machine learning, information retrieval, software engineering, etc. This paper presents FCA for analysis and representation of biomedical data. Furthermore, we present a new lattice-based algorithm for analysis of large and high-dimensional biomedical data.

Digital Ecosystem for Cross-domain Context Sensing and Trading

There is a need for exchange and trade of contextual information within ubiquitous computing environments between different providers of context-aware services. It is the need of a mobile user to obtain such services wherever he roams during the course of the day, such as home, workplace, leisure and visiting businesses, in a way that is safe and secure for both the user as well as the providers, while generating the maximum benefit from synergetically aggregating pieces of contextual information. A possible method to model the peer-to-peer relationships and complex structure of different interests is the introduction of digital ecosystems. The digital ecosystem is an emerging paradigm for economic and technological innovation. It consists of a self-organising digital infrastructure, aimed at creating a digital environment for networked organisations (or agents) thus supporting the cooperation, knowledge sharing and development of open and adaptive technologies and evolutionary, domain knowledge rich, environments.

ENDORSE: a legal technical framework for privacy preserving data management

The ENDORSE project is concerned with providing assurances for data protection for both data controllers and data subjects. The project will define a rules based language called PRDL (Privacy Rules Definition Language) which can be used to express legislative requirements, organizational privacy policy as well as user consent. ENDORSE will provide a rules engine to ensure that privacy policies expressed in this language are compliant with legislative requirements for the applicable jurisdictions. In addition a set of technology adapters will be developed which will provide transformations from PRDL to target access control and policy configuration instances, which in turn can be used by organizations to ensure that internal data handling practices are in turn compliant. In parallel to this effort a certification methodology will be developed to provide a means of generating a privacy seals. This paper describes an overview of the project, the motivation behind the initiative, its aims and objectives as well as an introduction to the approach taken and technologies foreseen to achieves these aims. The paper also provides a discussion of how the results of the project can be applied in different scenarios.

Personalised Resource Discovery Searching over Multiple Repository Types

The success of the Information Society, with the overabundance of online multimedia information, has become an obstacle for users to discover pertinent resources. For those users, the key is the refinement of resource discovery as the choice and complexity of available online content continues to grow. The work resented in this paper will address this issue by representing complex extensible user and information provider profiles and content metadata using XML and the provision of a middle canonical language to aid in learner-to-content matching, independent of the underlying metadata format. This approach can provide a federated search solution leading to personalise resource discovery based on user requirements and preferences, seamlessly searching over multiple repository types. The novelty of the work includes the complex extensible user profiles, information provider profiles, the canonical language and the federated search strategy. Although, the work presented is focused on E-Learning, the general ideas could be applied to any resource discovery or information retrieval