GridCertLib: A Single Sign-on Solution for Grid Web Applications and Portals

This paper describes the design and implementation of GridCertLib, a Java library leveraging a Shibboleth-based authentication infrastructure and the SLCS online certificate signing service, to provide short-lived X.509 certificates and Grid proxies. The main use case envisioned for GridCertLib, is to provide seamless and secure access to Grid X.509 certificates and proxies in web applications and portals: when a user logs in to the portal using SAML-based Shibboleth authentication, GridCertLib uses the SAML assertion to obtain a Grid X.509 certificate from the SLCS service and generate a VOMS proxy from it. We give an overview of the architecture of GridCertLib and briefly describe its programming model. Its application to some deployment scenarios is outlined, as well as a report on practical experience integrating GridCertLib into portals for Bioinformatics and Computational Chemistry applications, based on the popular P-GRADE and Django software

Towards a grid-enabled simulation framework for nano-CMOS electronics

The electronics design industry is facing major challenges as transistors continue to decrease in size. The next generation of devices will be so small that the position of individual atoms will affect their behaviour. This will cause the transistors on a chip to have highly variable characteristics, which in turn will impact circuit and system design tools. The EPSRC project "Meeting the Design Challenges of Nano-CMOS Electronics" (Nana-CMOS) has been funded to explore this area. In this paper, we describe the distributed data-management and computing framework under development within Nano-CMOS. A key aspect of this framework is the need for robust and reliable security mechanisms that support distributed electronics design groups who wish to collaborate by sharing designs, simulations, workflows, datasets and computation resources. This paper presents the system design, and an early prototype of the project which has been useful in helping us to understand the benefits of such a grid infrastructure. In particular, we also present two typical use cases: user authentication, and execution of large-scale device simulations

Hierarchical video surveillance architecture: a chassis for video big data analytics and exploration

There is increasing reliance on video surveillance systems for systematic derivation, analysis and interpretation of the data needed for predicting, planning, evaluating and implementing public safety. This is evident from the massive number of surveillance cameras deployed across public locations. For example, in July 2013, the British Security Industry Association (BSIA) reported that over 4 million CCTV cameras had been installed in Britain alone. The BSIA also reveal that only 1.5% of these are state owned. In this paper, we propose a framework that allows access to data from privately owned cameras, with the aim of increasing the efficiency and accuracy of public safety planning, security activities, and decision support systems that are based on video integrated surveillance systems. The accuracy of results obtained from government-owned public safety infrastructure would improve greatly if privately owned surveillance systems ‘expose’ relevant video-generated metadata events, such as triggered alerts and also permit query of a metadata repository. Subsequently, a police officer, for example, with an appropriate level of system permission can query unified video systems across a large geographical area such as a city or a country to predict the location of an interesting entity, such as a pedestrian or a vehicle. This becomes possible with our proposed novel hierarchical architecture, the Fused Video Surveillance Architecture (FVSA). At the high level, FVSA comprises of a hardware framework that is supported by a multi-layer abstraction software interface. It presents video surveillance systems as an adapted computational grid of intelligent services, which is integration-enabled to communicate with other compatible systems in the Internet of Things (IoT)

A classification of emerging and traditional grid systems

The grid has evolved in numerous distinct phases. It started in the early ’90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late ’90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to “glue” different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings. However, third-generation grids’ current architecture doesn’t meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systems’ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area