Zlatko Zlatev

Platform-as-a-Service Architecture for Real-Time Quality of Service Management in Clouds

Cloud computing offers the potential to dramatically reduce the cost of software services through the commoditization of information technology assets and on-demand usage patterns. However, the complexity of determining resource provision policies for applications in such complex environments introduces significant inefficiencies and has driven the emergence of a new class of infrastructure called Platform-as-a-Service (PaaS). In this paper, we present a novel PaaS architecture being developed in the EU IST IRMOS project targeting real-time Quality of Service (QoS) guarantees for online interactive multimedia applications. The architecture considers the full service lifecycle including service engineering, service level agreement design, provisioning and monitoring. QoS parameters at both application and infrastructure levels are given specific attention as the basis for provisioning policies in the context of temporal constraints. The generic applicability of the architecture is being verified and validated through implemented scenarios from three important application sectors (film post-production, virtual augmented reality for engineering design, collaborative e-Learning in virtual worlds).

Virtualised e-Learning with real-time guarantees on the IRMOS platform

In this paper we focus on how Quality of Service guarantees are provided to virtualised applications in the Cloud Computing infrastructure that is being developed in the context of the IRMOS1 European Project. Provisioning of proper timeliness guarantees to distributed real-time applications involves the careful use of real-time scheduling mechanisms at the virtual-machine hypervisor level, of QoS-aware networking protocols and of proper design methodologies and tools for stochastic modelling of the application. The paper focuses on how we applied these techniques to a case-study involving a real e-Learning mobile content delivery application that has been integrated into the IRMOS platform and its achieved performance.

Virtualised e-Learning on the IRMOS real-time Cloud

This paper presents the real-time virtualised Cloud infrastructure that was developed in the context of the IRMOS European Project. The paper shows how different concepts, such as real-time scheduling, QoS-aware network protocols, and methodologies for stochastic modelling and run-time provisioning were practically combined to provide strong performance guarantees to soft real-time interactive applications in a virtualised environment. The efficiency of the IRMOS Cloud is demonstrated by two real interactive e-Learning applications, an e-Learning mobile content delivery application and a Virtual World e-Learning application.

Benchmarking knowledge-assisted kriging for automated spatial interpolation of wind measurements

We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of spatial cohesion to be specified and variograms calculated for each region. The variogram calculation itself is automated and spatial regions created via offline automated segmentation of either expert-drawn Google Earth polygons or NASA altitude data. Our use-case is to create interpolated wind maps for input into a bathing water quality model of microbial contamination. We benchmark our knowledge-assisted kriging algorithm against 7 other algorithms on UK met-office wind data (189 sensors). Our wind estimation results are comparable to standard ordinary kriging using variograms created by an expert. When using spatial segmentation we find our kriging error maps reflect better the known spatial features of the interpolated phenomenon. These results are very promising for an automated approach allowing on-demand datasets selection and real-time interpolation of previously unknown measurements. Automation is important in progressing towards a pan-European interpolation service capability.

Sustainable Archiving and Storage Management of Audiovisual Digital Assets

With the advent of end-to-end tapeless production and distribution, the whole concept of what it means to archive audiovisual content is being challenged. The traditional role of the archive as a repository for material after broadcast is changing because of digital file-based technologies and high speed networking. Rather than being at the end of the production chain, the archive is becoming an integral part of the production process and as a result is being absorbed into wider digital storage environments, including those that are distributed or used across organisational boundaries. This paper presents some of the work done in the UK AVATAR-m project on service-oriented approaches to digital permanence and preservation of audiovisual content. Our specific focus is how to specify and then govern federated storage services in a way that ensures the long term safety, security and accessibility of audiovisual assets in a managed and cost effective way.

Context Ontology Modelling for Improving Situation Awareness and Crowd Evacuation from Confined Spaces

Crowd evacuation management at large venues such as airports, stadiums, cruise ships or metro stations requires the deployment and access to a Common Operational Picture (COP) of the venue, with real-time intelligent contextual interpretation of crowd behaviour. Large CCTV and sensor network feeds all provide important but heterogeneous observations about crowd safety at the venue of interest. Hence, these observations must be critically analyzed and interpreted for supporting security managers of crowd safety at venues. Specifically, the large volume of the generated observations needs to be interpreted in context of the venue operational grounds, crowd-gathering event times and the knowledge on crowd expected behaviour. In this paper, a new context ontology modelling approach is introduced. It is based on knowledge about venue background information, expected crowd behaviours and their manifested features of observations. The aim is to improve situation awareness about crowd safety in crisis management and decision-support.

Large Scale Surveillance, Detection and Alerts Information Management System for Critical Infrastructure

A proof-of-concept system for large scale surveillance, detection and alerts information management (SDAIM) is presented in this paper. Various aspects of building the SDAIM software system for large scale critical infrastructure monitoring and decision support are described. The work is currently developped in the large collaborative ZONeSEC project (www.zonesec.eu). ZONeSEC specializes in the monitoring of so-called Wide-zones. These are large critical infrastructure which require 24/7 monitoring for safety and security. It involves integrated in situ and remote sensing together with large scale stationary sensor networks, that are supported by cross-border communication. In ZONeSEC, the specific deployed sensors around the critical infrastructure may include: Accelerometers that are mounted on perimeter fences; Underground acoustic sensors; Optical, thermal and hyperspectral video cameras or radar systems mounted on strategic areas or on airborne UAVs for mission exploration. The SDAIM system design supports the ingestion of the various types of sensors platform wide-zones’ environmental observations and provide large scale distributed data fusion and reasoning with near-real-time messaging and alerts for critical decision-support. On a functional level, the system design is founded on the JDL/DFIG (Joint Directors of Laboratories/Data Fusion Information Group) data and information fusion model. Further, it is technologically underpinned by proven Big Data technologies for distributed data storage and processing as well as on-demand access to intelligent data analytics modules. The SDAIM system development will be piloted and alidated at various selected ZONeSEC project wide-zones [1]. These include water, oil and transnational gas pipelines and motorway conveyed in six European countries.