AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades

Project results presentation (deliverable D18)

This document is a report which collects together the CYCLOPS project results for dissemination to different interested audiences such as Grid communities and Civil Protection agencies. It also reports on national and international initiatives and projects, SMEs, training activities and related projects. The structure of this document shows the approach used in the project. Following an introduction, it describes a set of related projects, namely grid- based technologies/EGEE, risk management, and GMEs-based services. It then presents the business of Civil Protection and the use cases selected. These highlight the grid requirements for Grid-based CP applications. The research strategies and enhancements needed for the EGEE infra-structure are identified, based on the use cases. Dissemination of training and knowledge to different communities are also key points of the project.FP

Optimising resource costs of cloud computing for education

International audienceThere is a growing interest around the utilisation of cloud computing in education. As organisations involved in the area typically face severe budget restrictions, there is a need for cost optimisation mechanisms that explore unique features of digital learning environments. In this work, we introduce a method based on Maximum Likelihood Estimation that considers heterogeneity of IT infrastructure in order to devise resource allocation plans that maximise platform utilisation for educational environments. We performed experiments using modelled datasets from real digital teaching solutions and obtained cost reductions of up to 30%, compared with conservative resource allocation strategies