Leveraging the Grid to Provide a Global Platform for Ubiquitous Computing Research

The requirement for distributed systems support for Ubicomp has led to the development of numerous platforms, each addressing a subset of the overall requirements of ubiquitous systems. In contrast, many other scientific disciplines have embraced the vision of a global distributed computing platform, i.e. the Grid. We believe that the Grid has the potential to evolve into an ideal platform for building ubiquitous computing applications. In this paper we explore in detail the areas of synergy between Grid computing and ubiquitous computing and highlight a series of research challenges in this space

M-grid: Using Ubiquitous Web Technologies to create a Computational Grid

There are many potential users and uses for grid computing. However, the concept of sharing computing resources excites security concerns and, whilst being powerful and flexible, at least for novices, existing systems are complex to install and use. Together these represent a significant barrier to potential users who are interested to see what grid computing can do. This paper describes m-grid, a system for building a computational grid which can accept tasks from any user with access to a web browser and distribute them to almost any machine with access to the internet and manages to do this without the installation of additional software or interfering with existing security arrangements

Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues

The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain

The Semantic Grid: A future e-Science infrastructure

e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practice–aspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid