A Policy Architecture for Enhancing and Controlling Features

Abstract. Features provide extensions to a basic service, but in new systems users require much greater flexibility oriented towards their needs. Traditional features do not easily allow for this.We propose policies as the features of the future. Policies can be defined by the end-user, and allow for the use of rich context information when controlling calls. This paper introduces an architecture for policy definition and call control by policies. We discuss the operation of systems based on such an architecture. An important aspect of the architecture is integral feature interaction handling

Hybrid solutions to the feature interaction problem

In this paper we assume a competitive marketplace where the features are developed by different enterprises, which cannot or will not exchange information. We present a classification of feature interaction in this setting and introduce an on-line technique which serves as a basis for the two novel <i>hybrid</i> approaches presented. The approaches are hybrid as they are neither strictly off-line nor on-line, but combine aspects of both. The two approaches address different kinds of feature interactions, and thus are complimentary. Together they provide a complete solution by addressing interaction detection and resolution. We illustrate the techniques within the communication networks domain

Managing Distributed Feature Interactions in Enterprise SIP Application Servers

Several trends in SIP application server deployments exacerbate the classic problem of feature interaction in large enterprise telephony environments: use of distributed feature servers, mixing of legacy and green-field feature servers, and the co-existence of multiple third-party feature implementations provisioned in the same environment. Next-generation SIP application servers will include an application router (AR) to provide more control over feature sequencing. As we discuss here, the AR can be augmented to incorporate feature interaction detection and resolution logic. We describe a novel design for run-time feature interaction detection and resolution in an environment of distributed feature servers using a SIP application server with application routing function, such as that defined in JSR 289. The approach is based on the algorithm of the Kolberg-Magill (K-M) method for feature interaction detection. Here we extend the notation of the algorithm to cover advanced call control services, enable the algorithm to work in topologies involving B2BUAs and SBCs, and test the approach with a substantial feature set of 32 features

Refining, Implementing, and Evaluating the Extended Continuous Variable-Specific Resolutions of Feature Interactions

Systems that involve feature-oriented software development suffer from feature interactions, in which features affect one another’s behaviour in surprising ways. As the number of features increases, the complexity of examining feature combinations and fixing undesired interactions increases exponentially, such that the workload of resolving interactions comes to dominate feature development. The Feature Interaction Problem results from aiming resolve feature interaction by providing optimal resolutions. Resolution strategies combat the Feature Interaction Problem by offering default strategies that resolve entire classes of interactions, thereby reducing the work of the developer who is charged with the task of resolving interactions. However, most such approaches employ coarse-grained resolution strategies (e.g., feature priority) or a centralized arbitrator. This thesis focuses on evaluating and refining a proposed architecture that resolves features’ conflicting actions on system’s outputs. In this thesis, we extend a proposed architecture based on variable-specific resolution to enable co-resolution of related outputs and to promote smooth continuous resolutions over execution sequences. We implemented our approach within the PreScan simulator for advanced driver assistance systems, and performed a case study involving 15 automotive features that we implemented. We also devised and implemented three resolution strategies for the features’ outputs. The results of the case study show that the approach produces smooth and continuous resolutions of interactions throughout interesting scenarios

A pragmatic approach to service interaction filtering between call control services

Triggered by the deregulation of the telecommunications market, it is expected that the number of services deployed in the telecommunications network will increase dramatically in the near future. It is expected that these services will be interworking. However, as widely reported, interworking services will be subject to the service interaction problem. It is essential to cope with the problem in a developing multi service provider environment as it may substantially delay service deployment and hence form a serious obstacle to rapid service provisioning. In order to cope with the increasing number of services deployed in the network, previous work suggested the application of filtering approaches. This paper suggests such a technique. It is pragmatic in nature and does not require detailed service knowledge. Furthermore, it is shown how the approach can be incorporated into an overall comprehensive service interaction management process. Even though the approach is applied to call control aspects only, it could be extended to cover other areas

A System for Controlling, Monitoring and Programming the Home

As technology becomes ever more pervasive, the challenges of home automation are increasingly apparent. Seamless home control, home monitoring and home programming by the end user have yet to enter the mainstream. This could be attributed to the challenge of developing a fully autonomous and extensible home system that can support devices and technologies of differing protocols and functionalities. In order to offer programming facilities to the user, the underlying rule system must be fully independent, allowing support for current and future devices. Additional challenges arise from the need to detect and handle conflicts that may arise among user rules and yield undesirable results. Non-technical individuals typically struggle when faced with a programming task. It is therefore vital to encourage and ease the process of programming the home. This thesis presents Homer, a home system that has been developed to support three key features of a home system: control, monitoring and programming. Homer supports any third-party hardware or software service that can expose its functionality through Java and conform to the Homer interface. Stand-alone end user interfaces can be written by developers to offer any of Homer's functionality. Where policies (i.e. rules) for the home are concerned, Homer offers a fully independent policy system. The thesis presents a custom policy language, Homeric, that has been designed specifically for writing home rules. The Homer policy system detects overlaps and conflicts among rules using constraint satisfaction and the effect on environment variables. The thesis also introduces the notion of perspectives to ease user interactivity. These have been integrated into Homer to accommodate the range of ways in which a user may think about different aspects and features of their home. These perspectives include location, device type, time and people-oriented points of view. Design guidelines are also discussed to aid end user programming of the home. The work presented in this thesis demonstrates a system that supports control, monitoring and programming of the home. Developers can quickly and easily add functionality to the home through components. Conflicts can be detected amongst rules within the home. Finally, design guidelines and a prototype interface have been developed to allow both technically minded and non-technical people to program their home

Development and Evaluation of a Holistic Framework and Maturity Assessment Tools for Data Governance in Cloud Computing Environments

Cloud computing is an emerging technology that is changing the way that public sector organisations consume Information and Communication Technology (ICT) in different countries. The adoption rate of cloud computing services is still very low to none in many countries. Saudi Arabia, for instance, despite their huge investments in the Digital Transformation, as part of the recent Vision 2030, the loss of governance and control of data is one of their major barriers facing the adoption of cloud computing services. Cloud Data Governance, is not only a Saudi concern, it is actually a worldwide challenge, which is under researched and mostly not practiced. This research attempted, for the first time to unlock this challenge in Saudi Arabia, more specifically, for the Public Sector, by advancing research in this field and proposing means by which Cloud Data Governance programmes can be implemented. In this research, existing data governance frameworks were analysed – these frameworks were limited as they lacked consideration of the cloud computing perspective. Hence, the purpose of this research is to develop a generalised Strategy Framework that can be utilised to design, deploy and sustain an effective cloud data governance programme; it also aims to provide knowledge for organisations that wish to apply a cloud data governance programme, to empower them to control their data in cloud environments. Understanding data governance taxonomy and its key dimensions for non-cloud and cloud computing was an important step in developing the proposed Framework. To support the development of the proposed Framework, the Analytic Theory and concept of Critical Success Factors (CSFs) were adopted. The Framework includes a number of complex operations, therefore, to ensure an effective Cloud Data Governance programme, organisations need to have means by which they can assess their current state and define their requirements. To facilitate this, a Maturity Model was proposed together with an Assessment Matrix. The proposed Framework and Maturity Model alongside the Assessment Matrix, were then validated and evaluated for the Public Sector in Saudi Arabia, as a Case Study. Mixed research methods, Qualitative and Quantitative, were adopted for this purpose, where the State of the Art of cloud adoption, data governance and cloud data governance, in the Saudi Public Sector were all analysed. Moreover, a number of Barriers and Critical Success Factors were identified for the case study. For validation purposes, the Focus Group approach was adopted, with appropriate representations from the Saudi Public Sector. The Structural Equation Modelling was adopted for the evaluation of the proposed Framework, using quantitative results from the questionnaire. The Evaluation of the Assessment Matrix was done by developing a Tool, which allows organisations to identify their levels of maturity for cloud data governance programmes, and define requirements for target levels