Present and future of one of the largest Grid infrastructures in Europe

This summary paper illustrates the Italian production Grid infrastructure, its mission and its evolution strategy

Business Models for SEEV4-City Operational Pilots: From a generic SEEV4-City business model towards improved specific OP business models

This report, led by Northumbria University, provides a final analysis by project partners regarding Business Models for SEEV4-City Operational pilots. It is part of a collection of reports published by the project covering a variation of specific and cross-cutting analysis and evaluation perspectives and spans 6 operational pilots

e-Science Infrastructure for the Social Sciences

When the term „e-Science“ became popular, it frequently was referred to as “enhanced science” or “electronic science”. More telling is the definition ‘e-Science is about global collaboration in key areas of science and the next generation of infrastructure that will enable it’ (Taylor, 2001). The question arises to what extent can the social sciences profit from recent developments in e- Science infrastructure? While computing, storage and network capacities so far were sufficient to accommodate and access social science data bases, new capacities and technologies support new types of research, e.g. linking and analysing transactional or audio-visual data. Increasingly collaborative working by researchers in distributed networks is efficiently supported and new resources are available for e-learning. Whether these new developments become transformative or just helpful will very much depend on whether their full potential is recognized and creatively integrated into new research designs by theoretically innovative scientists. Progress in e-Science was very much linked to the vision of the Grid as “a software infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources’ and virtually unlimited computing capacities (Foster et al. 2000). In the Social Sciences there has been considerable progress in using modern IT- technologies for multilingual access to virtual distributed research databases across Europe and beyond (e.g. NESSTAR, CESSDA – Portal), data portals for access to statistical offices and for linking access to data, literature, project, expert and other data bases (e.g. Digital Libraries, VASCODA/SOWIPORT). Whether future developments will need GRID enabling of social science databases or can be further developed using WEB 2.0 support is currently an open question. The challenges here are seamless integration and interoperability of data bases, a requirement that is also stipulated by internationalisation and trans-disciplinary research. This goes along with the need for standards and harmonisation of data and metadata. Progress powered by e- infrastructure is, among others, dependent on regulatory frameworks and human capital well trained in both, data science and research methods. It is also dependent on sufficient critical mass of the institutional infrastructure to efficiently support a dynamic research community that wants to “take the lead without catching up”.

A Worldwide Production Grid Service Built on EGEE and OSG Infrastructures â Lessons Learnt and Long-term Requirements

Using the Grid Infrastructures provided by EGEE, OSG and others, a worldwide production service has been built that provides the computing and storage needs for the 4 main physics collaborations at CERN's Large Hadron Collider (LHC). The large number of users, their geographical distribution and the very high service availability requirements make this experience of Grid usage worth studying for the sake of a solid and scalable future operation. This service must cater for the needs of thousands of physicists in hundreds of institutes in tens of countries. A 24x7 service with availability of up to 99% is required with major service responsibilities at each of some ten "Tier1" and of the order of one hundred "Tier2" sites. Such a service - which has been operating for some 2 years and will be required for at least an additional decade - has required significant manpower and resource investments from all concerned and is considered a major achievement in the field of Grid computing. We describe the main lessons learned in offering a production service across heterogeneous Grids as well as the requirements for long-term operation and sustainability

e-Science Infrastructure for the Social Sciences

"When the term 'e-Science' became popular, it frequently was referred to as 'enhanced science' or 'electronic science'. More telling is the definition 'e-Science is about global collaboration in key areas of science and the next generation of infrastructure that will enable it' (Taylor, 2001). The question arises to what extent can the social sciences profit from recent developments in e-Science infrastructure? While computing, storage and network capacities so far were sufficient to accommodate and access social science data bases, new capacities and technologies support new types of research, e.g. linking and analysing transactional or audiovisual data. Increasingly collaborative working by researchers in distributed networks is efficiently supported and new resources are available for e-learning. Whether these new developments become transformative or just helpful will very much depend on whether their full potential is recognized and creatively integrated into new research designs by theoretically innovative scientists. Progress in e-Science was very much linked to the vision of the Grid as 'a software infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources' and virtually unlimited computing capacities (Foster et al. 2000). In the Social Sciences there has been considerable progress in using modern IT-technologies for multilingual access to virtual distributed research databases across Europe and beyond (e.g. NESSTAR, CESSDA - Portal), data portals for access to statistical offices and for linking access to data, literature, project, expert and other data bases (e.g. Digital Libraries, VASCODA/ SOWIPORT). Whether future developments will need GRID enabling of social science databases or can be further developed using WEB 2.0 support is currently an open question. The challenges here are seamless integration and interoperability of data bases, a requirement that is also stipulated by internationalisation and trans-disciplinary research. This goes along with the need for standards and harmonisation of data and metadata. Progress powered by e-infrastructure is, among others, dependent on regulatory frameworks and human capital well trained in both, data science and research methods. It is also dependent on sufficient critical mass of the institutional infrastructure to efficiently support a dynamic research community that wants to 'take the lead without catching up'." (author's abstract

NetJobs: A new approach to network monitoring for the Grid using Grid jobs

With grid computing, the far-fl�ung and disparate IT resources act as a single "virtual datacenter". Grid computing interfaces heterogeneous IT resources so they are available when and where we need them. Grid allows us to provision applications and allocate capacity among research and business groups that are geographically and organizationally dispersed. Building a high availability Grid is hold as the next goal to achieve: protecting against computer failures and site failures to avoid downtime of resource and honor Service Level Agreements. Network monitoring has a key role in this challenge. This work is concerning the design and the prototypal implementation of a new approach to Network monitoring for the Grid based on the usage of Grid scheduled jobs. This work was carried out within the Network Support task (SA2) of the Enabling Grids for E-sciencE (EGEE) project. This thesis is organized as follows: Chapter 1: Grid Computing From the origins of Grid Computing to the latest projects. Conceptual framework and main features characterizing many kind of popular grids will be presented. Chapter 2: The EGEE and EGI projects This chapter describes the Enabling Grids for E-sciencE (EGEE) project and the European Grid Infrastructure (EGI). EGEE project (2004-2010) was the�flagship Grid infrastructure project of the EU. The third and last two-year phase of the project (started on 1 May 2008) was financed with a total budget of around 47 million euro, with a further estimated 50 million euro worth of computing resources contributed by the partners. A total manpower of 9,000 Person Months, of which over 4,500 Person Months has been contributed by the partners from their own funding sources. At its close, EGEE represented a worldwide infrastructure of approximately to 200,000 CPU cores, collaboratively hosted by more than 300 centres around the world. By the end of the project, around 13 million jobs were executed on the EGEE grid each month. The new organization, EGI.eu, has then been created to continue the coordination and evolution of the European Grid Infrastructure (EGI) based on EGEE Grid. Chapter3: gLite Middleware Chapter three gives an overview on the gLite Grid Middleware. gLite is the middleware stack for grid computing used by the EGEE and EGI projects with in a very large variety of scientifi�c domains. Born from the collaborative efforts of more than 80 people in 12 different academic and industrial research centers as part of the EGEE Project, gLite provides a complete set of services for building a production grid infrastructure. gLite provides a framework for building grid applications tapping into the power of distributed computing and storage resources across the Internet. The gLite services are currently adopted by more than 250 Computing Centres and used by more than 15000 researchers in Europe and around the world. Chapter 4: Network Activity in EGEE/EGI Grid infrastructures are distributed by nature, involving many sites, normally in different administrative domains. Individual sites are connected together by a network, which is therefore a critical part of the whole Grid infrastructure; without the network there is no Grid. Monitoring is a key component for the successful operation of any infrastructure, helping in the discovery and diagnosis of any problem which may arise. Network monitoring is able to contribute to the day-to-day operations of the Grid by helping to provide answers to specific questions from users and site administrators. This chapter will discuss all the effort lavished by EGEE and EGI in the Grid Network domain. Chapter 5: Grid Network Monitoring based on Grid Jobs Net Jobs is a prototype of a light weight solution for the Grid network monitoring. A job-based approach has been used in order to prove the feasibility of this non intrusive solution. It is currently configured to monitor eight production sites spread from Italy to France but this method could be applied to the vast majority of Grid sites. The prototype provides coherent RTT, MTU, number of hops and TCP achievable bandwidth tests