BM_Virtual Enterprise Architecture Reference Model for Concurrent Engineering: An experiment

In order to test the potential of Virtual Enterprise (VE) organizational principles for Concurrent Engineering (CE) team work organization, an experiment applying the BM_Virtual Enterprise Architecture Reference Model (BM_VEARM) is organized. Three CE teams are asked to create a web site. The teams have been organized as follows: 1) CE distributed team (virtual team according to literature); 2) CE agile team (agile organization according to BM_VEARM) and 3) CE virtual team (virtual organization according to BM_VEARM), in order to complete the required task. The main objective of the experiment is to show that the three organization models of CE teams work effectively, and analyse the performance according to previously defined criteria. In this paper the results in terms of product quality are presented. The experiment has shown that better product quality, for the product quality aspects analysed, is achieved in cases when VE organization is applied

High-Performance Cloud Computing: A View of Scientific Applications

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape

Cloudbus Toolkit for Market-Oriented Cloud Computing

This keynote paper: (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of Cloud applications and deployment on private or public Clouds, in addition to supporting market-oriented resource management; (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party Cloud brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape

Planning strategically, designing architecturally : a framework for digital library services

In an era of unprecedented technological innovation and evolving user expectations and information seeking behaviour, we are arguably now an online society, with digital services increasingly common and increasingly preferred. As a trusted information provider, libraries are in an advantageous position to respond, but this requires integrated strategic and enterprise architecture planning, for information technology (IT) has evolved from a support role to a strategic role, providing the core management systems, communication networks, and delivery channels of the modern library. Further, IT components do not function in isolation from one another, but are interdependent elements of distributed and multidimensional systems encompassing people, processes, and technologies, which must consider social, economic, legal, organisational, and ergonomic requirements and relationships, as well as being logically sound from a technical perspective. Strategic planning provides direction, while enterprise architecture strategically aligns and holistically integrates business and information system architectures. While challenging, such integrated planning should be regarded as an opportunity for the library to evolve as an enterprise in the digital age, or at minimum, to simply keep pace with societal change and alternative service providers. Without strategy, a library risks being directed by outside forces with independent motivations and inadequate understanding of its broader societal role. Without enterprise architecture, it risks technological disparity, redundancy, and obsolescence. Adopting an interdisciplinary approach, this conceptual paper provides an integrated framework for strategic and architectural planning of digital library services. The concept of the library as an enterprise is also introduced

A formal verification framework and associated tools for enterprise modeling : application to UEML

The aim of this paper is to propose and apply a verification and validation approach to Enterprise Modeling that enables the user to improve the relevance and correctness, the suitability and coherence of a model by using properties specification and formal proof of properties