Ontologies for Resolution Policy Definition and Policy Conflict Detection

In previous work, the author devised a collection of ontologies to model the generic structure and characteristics of the APPEL policy description language [18] utilised within the ACCENT policy system [1]. Two ontologies, namely genpol.owl and wizpol.owl, were defined using OWL (Web Ontology Language [10]) to describe the generic aspects of the policy language and aspects of how the policy wizard (user interface) uses the language. These generic ontologies are explained in CSM-169 [3], while an ontology modelling a domain-specific implementation of the policy language for call control is described in CSM-170 [4]. This document describes how these ontologies have been extended to define the structure of resolution policies, in addition to standard domain policies. A resolution policy has a similar structural composition to a standard policy, but places restrictions on the characteristics of its components. While a standard policy is used to define how events within the domain are handled, a resolution policy is defined purposely to resolve run-time conflicts between standard domain policies. Conflict arises between a pair of standard domain policies whose actions clash if executed simultaneously. A resolution policy specifies the action to be taken when such conflict occurs. This report distinguishes between a standard policy and a resolution policy in APPEL, outlining the ontology description for each and highlighting subtle differences in their form. In particular, it demonstrates extensions to genpol and wizpol to specify generic resolution policies. Based on the generic extensions, callcontrol.owl was also expanded to include generic call control resolution actions. The call control ontology is described here as a concrete example of a domain-specific resolution policy language definition for the purposes of managing call conflicts. In addition, the report describes generic and domain-specific ontology extensions to aid in policy conflict detection using a filtering technique

A Goal-Directed and Policy-Based Approach to System Management

This thesis presents a domain-independent approach to dynamic system management using goals and policies. A goal is a general, high-level aim a system must continually work toward achieving. A policy is a statement of how a system should behave for a given set of detectable events and conditions. Combined, goals may be realised through the selection and execution of policies that contribute to their aims. In this manner, a system may be managed using a goal-directed, policy-based approach. The approach is a collection of related techniques and tools: a policy language and policy system, goal definition and refinement via policy selection, and conflict filtering among policies. Central to these themes, ontologies are used to model application domains, and incorporate domain knowledge within the system. The ACCENT policy system (Advanced Component Control Enhancing Network Technologies, http://www.cs.stir.ac.uk/accent) is used as a base for the approach, while goals and policies are defined using an extension of APPEL (Adaptable and Programmable Policy Environment and Language, http://www.cs.stir.ac.uk/appel). The approach differs from existing work in that it reduces system state, goals and policies to a numerical rather than logical form. This is more user-friendly as the goal domain may be expressed without any knowledge of formal methods. All developed techniques and tools are entirely domain-independent, allowing for reuse with other event-driven systems. The ability to express a system aim as a goal provides more powerful and proactive high-level management than was previously possible using policies alone. The approach is demonstrated and evaluated within this thesis for the domains of Internet telephony and sensor network/wind turbine management

Ontology Stack for A Policy Wizard

An ontology provides a common vocabulary through which to share information in a particular area of knowledge, including the key terms, their semantic interconnections and certain rules of inference. The ACCENT policy-based management system uses a policy description language called APPEL and supports policy document formation through the use of a comprehensive user interface wizard. Through the use of OWL (the Web Ontology Language), the core aspects of APPEL have been captured and defined in an ontology. Assigned the acronym genpol, this ontology describes the policy language independent of any user interface or domain-specific policy information. A further ontology has been developed to define common interface features implemented by the policy wizard [17]. This ontology, referred to as wizpol, directly extends genpol. It provides additional information to the language itself, whilst retaining freedom from any domain-specific policy details. Combined, both genpol and wizpol act as a base for defining further domain-specific ontologies which may describe policy options tailored for a particular application. This report presents a technical overview of both the generic policy language ontology (genpol) and the wizard policy ontology (wizpol), expressed in the form of graphical depictions of OWL classes and properties

Ontology for Call Control

An ontology provides a common vocabulary through which to share information in a particular area of knowledge, including the key terms, their semantic interconnections and certain rules of inference. Using OWL (The Web Ontology Language), an ontology has been developed describing the domain of (Internet) call control. In particular, the ontology focuses on the use of call control in conjunction with its application within the ACCENT policy-based management system. The structure of the ontology builds heavily on previously developed ontologies genpol [4] and wizpol [20]. These describe generic aspects of the system, including the core policy description language on which it is based. This report presents a technical overview of the ontology for (Internet) call control, illustrated by way of graphical depictions of OWL class and property implementation

An Overview of Ontology Application for Policy-Based Management using POPPET

The use of ontology to describe the key concepts and their interrelationships within a particular area has become a widely recognised and advantageous means of sharing information about the structure of knowledge within a domain. Ontologies provide a way of integrating structured data within an application. This report provides an overview of how the ACCENT policy-based management system [1] was significantly re-engineered to utilise an ontology in place of previously hard-coded, domain-specific information within its user interface. In order to successfully integrate the ontology with the policy system, a new framework named POPPET was developed, responsible for parsing and querying ontological data. Although a substantial alteration in technical structure, the process vastly generalises the policy system, enabling adaptation for policy management within any custom domain. An introduction to the concepts and motivation for ontology creation using OWL is presented, together with general background to the ACCENT policy system. A technical overview is then given covering the developed ontologies, the POPPET system design, and the policy system re-engineering process. Finally, a comparison is made between the new and old policy system structures, and the impact on system performance is evaluated

The ACCENT Policy Wizard

The ACCENT project (Advanced Component Control Enhancing Network Technologies) developed a practical and comprehensive policy system for call control/Internet telephony. The policy system has subsequently been extended for management of sensor networks/wind farms and of home care/telecare. This report focuses on a web-based policy wizard that acts as the primary interface between end users and the policy system. The policy wizard has an intimate knowledge of the APPEL policy language (Adaptable and Programmable Policy Environment and Language). The wizard allows end users to create policies using nearnatural language without knowing or seeing XML, and to upload them to the policy system. The wizard also provides a number of convenience functions such as predefined policy templates, editing and activating existing policies, and defining policy variables. Relative to the version of December 2005, this Technical Report has been updated as follows to reflect changes in the policy wizard: - The whole report has been updated to reflect later work on the PROSEN and MATCH projects. As a result, the ACCENT and APPEL acronyms have changed. Call control, however, remains are the primary illustration of the approach in this report. - Chapter 1 is now named ‘Introduction’, and a brief ‘Conclusion’ chapter has been added in section 4. - Chapter 2 has been updated to sheet screenshots of the new policy wizard. The wizard now handles resolution policies. - The wizard now makes use of ontologies, as described briefly in section 3.1. All domain-specific knowledge is held outside the wizard, so that largely common code can be used across all domains. As a result, the wizard configuration now also refers to the POPPET server. - Section 3.6 describes a new code structure that allows different versions of the wizard to coexist. - A brief explanation has been given in section 3.8 of what is involved in supporting a new application domain with the wizard

An overview of emerging trends in pathogen reduction in the processing of fruit juices

Master of ScienceDepartment of Animal Sciences and Industry Food ScienceElizabeth BoyleUnpasteurized fruit juices have been implicated as the source of foodborne outbreaks due to pathogens such as Salmonella, Escherichia coli O157: H7 and Cryptosporidium parvum. The growth of pathogens can usually be slowed through freezing or largely eliminated through pasteurization. Although pasteurization is often effective in eliminating pathogens, it often yields undesirable flavors that are unlike those of fresh juice. Growing consumer trends towards “healthy” unpasteurized alternatives are fueling the development of alternative processing techniques. Several promising techniques for pathogen reduction in the processing of fruit juices are currently being developed. A new technique that is already being marketed worldwide is hyperbaric processing (HPP) which subjects the fruit juice to a high pressure of up to 1000 MPa. The high-pressure treatment results in up to a 7 log reduction kill in pathogens while preserving the naturally occurring flavor profile, sensory attributes and nutritional benefits. Pulsed electric fields (PEF) and ionizing radiation are also being widely explored as viable techniques to process unpasteurized fruit juices. PEF promises to be a commercially viable energy efficient alternative to pasteurization, adding only $0.03 –$0.05 per liter to final food costs. Although irradiation enjoys support for use in the processing of fruit juice by regulatory agencies, support in public opinion is lacking and hinders its growth as an alternative to pasteurization. Other experimental techniques are also present in the development pipeline. Ultrasonic radiation and high intensity pulsed light radiation are both experimental techniques that are being researched. A particularly exciting alternative is the use of plant-based antimicrobials. Several fruits and spices are known to be natural antimicrobials and are therefore being researched as alternatives to the traditional chemical preservatives

Prevalence and stability of active play, restricted movement and television viewing in infants

This study describes engagement in and stability of physical activity and sedentary behaviours in early life, and assesses associations with sex, maternal education and developmental stage. Maternal-report data at child age 4, 9 and 20 months were collected from 542 families in the Melbourne Infant Feeding Activity and Nutrition Trial Program. Parents estimated average time per day their child spent in active pursuits or pursuits that restricted movement. With increasing age, children generally spent more time in active pursuits and watching television, and less time in situations that restrict movement. Associations were found with age of developmental milestone attainment but not sex or maternal education. Stability over time was strongest for television viewing (β = 0.34–0.38) and time spent outdoors (β = 0.27–0.33). Contrary to guidelines, television viewing increased and showed stability, suggesting a need to target this behaviour very early in life to achieve optimal longer term outcomes

Policy Conflict Filtering for Call Control

Policies exhibit conflicts much as features exhibit interaction. Since policies are defined by end users, the combinatorial problems involved in detecting conflicts are substantially worse than for detecting feature interactions. A new, ontology-driven method is defined for automatically identifying potential conflicts among policies. This relies on domain knowledge to annotate policy actions with their effects. Conflict filtering is performed offline, but supports conflict detection and resolution online. The technique has been implemented in the RECAP tool (Rigorously Evaluated Conflicts Among Policies). Subject to user guidance, this tool filters conflicting pairs of actions and automatically generates resolutions. The approach is generic, but is illustrated with the APPEL policy language for call control. The technique has improved the scalability of conflict handling, and has reduced the effort required of the previous manual approach

APPEL: An Adaptable and Programmable Policy Environment and Language

The Accent project (Advanced Component Control Enhancing Network Technologies) developed a practical and comprehensive policy system for call control/Internet telephony. The policy system has subsequently been extended for management of sensor networks/wind farms and of home care/telecare. This report focuses on Appel (Adaptable and Programmable Policy Environment and Language). It provides an overview of the language, and presents the language in XML schema form. The core language has been instantiated for call control, for sensor networks, and for home care. Sample goals and policies of different kinds are provided to illustrate these applications