Grid computing is traditionally applied for batch jobs in the scientific and academic computing. This is also the case at WLCG, the global computing infrastructure providing the production and analysis environments for the LHC experiments at CERN. In this paper we envision the next generation Grid computing systems to support High Energy Physics (HEP) online sessions. We refine a resource management framework for enabling on-demand private virtual clusters on the AliEn Grid middleware and run applications on an online computing environment. We describe the software components distributed among the submission node and the site front-end and execution nodes. Our experiment evaluates the scalability of the agents deployed at the execution nodes and measures the performance of PROOF - the de-facto standard software for HEP data analysis - on our Grid environment rather than on a local cluster. Because PROOF generates time-sensitive I/O and requires to handle potentially thousands of network connections, we describe a multiplexed I/O approach as the ideal solution for scalable and high-performing proxy services.

Grid computing has the intrinsic disadvantages of a batch system: the undetermined delay between the time a job is submitted and the time it is completed. Our approach to this problem is iGrid, a framework that proposes to change the Grid from a batch system to a more interactive distributed platform. Agents are deployed on nodes and wait to be contacted by an interactive job to start the computation, thus bypassing the regular Grid scheduler. A CPU fairshare mechanism allows users to get their fair iGrid machine share over a long period. Our prototype implementation scales to all 400 Grid nodes we were granted executing on top a software for data intensive parallel computing

In this technical demonstration we show an integrated web system for video search and annotation based on ontologies. The system is composed by three components: the Orione ontology-based search engine, the Sirio\footnote{Sirio was the hound of Orione. It was a dog so swift that no prey could escape it.} search interface, and the Pan web-based video annotation tool. The system is currently being developed within the EU IM3I project. The goal of the system is to provide an integrated environment for video annotation and retrieval of videos, for both technical and non-technical users. In fact, the search engine has different interfaces that permit different query modalities: free-text, natural language, graphical composition of concepts using Boolean and temporal relations and query by visual example. In addition, the ontology structure is exploited to encode semantic relations between concepts permitting, for example, to expand queries to synonyms and concept specializations. The annotation tool can be used to create ground-truth annotations to train automatic annotations systems, or to complement the results of automatic annotation, e.g. adding geolocalized information.

In this technical demonstration we present a novel web-based tool that allows a user friendly semantic browsing of video collections, based on ontologies, concepts, concept relations and concept clouds. The system is developed as a Rich Internet Application (RIA) to achieve a fast responsiveness and ease of use that can not be obtained by other web application paradigms, and uses streaming to access and inspect the videos. Users can also use the tool to browse the content of social and media sharing sites like YouTube, Flickr and Twitter, accessing these external resources through the ontologies used in the system. The tool has won the second prize in the Adobe YouGC contest, in the RIA category.