A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft

Design and Implementation of a Measurement-Based Policy-Driven Resource Management Framework For Converged Networks

This paper presents the design and implementation of a measurement-based QoS and resource management framework, CNQF (Converged Networks QoS Management Framework). CNQF is designed to provide unified, scalable QoS control and resource management through the use of a policy-based network management paradigm. It achieves this via distributed functional entities that are deployed to co-ordinate the resources of the transport network through centralized policy-driven decisions supported by measurement-based control architecture. We present the CNQF architecture, implementation of the prototype and validation of various inbuilt QoS control mechanisms using real traffic flows on a Linux-based experimental test bed.Comment: in Ictact Journal On Communication Technology: Special Issue On Next Generation Wireless Networks And Applications, June 2011, Volume 2, Issue 2, Issn: 2229-6948(Online

Model-driven engineering approach to design and implementation of robot control system

In this paper we apply a model-driven engineering approach to designing domain-specific solutions for robot control system development. We present a case study of the complete process, including identification of the domain meta-model, graphical notation definition and source code generation for subsumption architecture -- a well-known example of robot control architecture. Our goal is to show that both the definition of the robot-control architecture and its supporting tools fits well into the typical workflow of model-driven engineering development.Comment: Presented at DSLRob 2011 (arXiv:cs/1212.3308

Proximal business intelligence on the semantic web

This is the post-print version of this article. The official version can be accessed from the link below - Copyright @ 2010 Springer.Ubiquitous information systems (UBIS) extend current Information System thinking to explicitly differentiate technology between devices and software components with relation to people and process. Adapting business data and management information to support specific user actions in context is an ongoing topic of research. Approaches typically focus on providing mechanisms to improve specific information access and transcoding but not on how the information can be accessed in a mobile, dynamic and ad-hoc manner. Although web ontology has been used to facilitate the loading of data warehouses, less research has been carried out on ontology based mobile reporting. This paper explores how business data can be modeled and accessed using the web ontology language and then re-used to provide the invisibility of pervasive access; uncovering more effective architectural models for adaptive information system strategies of this type. This exploratory work is guided in part by a vision of business intelligence that is highly distributed, mobile and fluid, adapting to sensory understanding of the underlying environment in which it operates. A proof-of concept mobile and ambient data access architecture is developed in order to further test the viability of such an approach. The paper concludes with an ontology engineering framework for systems of this type – named UBIS-ONTO

Managing data through the lens of an ontology

Ontology-based data management aims at managing data through the lens of an ontology, that is, a conceptual representation of the domain of interest in the underlying information system. This new paradigm provides several interesting features, many of which have already been proved effective in managing complex information systems. This article introduces the notion of ontology-based data management, illustrating the main ideas underlying the paradigm, and pointing out the importance of knowledge representation and automated reasoning for addressing the technical challenges it introduces