The software architecture for the First Challenge on Generating Instructions in Virtual Environments.

The GIVE Challenge is a new Internet-based evaluation effort for natural language generation systems. In this paper, we motivate and describe the software infrastructure that we developed to support this challenge

Generating Instructions in a 3D Game Environment: Efficiency or Entertainment?

The GIVE Challenge was designed for the evaluation of natural language generation (NLG) systems. It involved the automatic generation of instructions for users in a 3D environment. In this paper we introduce two NLG systems that we developed for this challenge. One system focused on generating optimally helpful instructions while the other focused on entertainment. We used the data gathered in the Challenge to compare the efficiency and entertainment value of both systems. We found a clear difference in efficiency, but were unable to prove that one system was more entertaining than the other. This could be explained by the fact that the set-up and evaluation methods of the GIVE Challenge were not aimed at entertainment

Improving early design stage timing modeling in multicore based real-time systems

This paper presents a modelling approach for the timing behavior of real-time embedded systems (RTES) in early design phases. The model focuses on multicore processors - accepted as the next computing platform for RTES - and in particular it predicts the contention tasks suffer in the access to multicore on-chip shared resources. The model presents the key properties of not requiring the application's source code or binary and having high-accuracy and low overhead. The former is of paramount importance in those common scenarios in which several software suppliers work in parallel implementing different applications for a system integrator, subject to different intellectual property (IP) constraints. Our model helps reducing the risk of exceeding the assigned budgets for each application in late design stages and its associated costs.This work has received funding from the European Space Agency under Project Reference AO=17722=13=NL=LvH, and has also been supported by the Spanish Ministry of Science and Innovation grant TIN2015-65316-P. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.Peer ReviewedPostprint (author's final draft

Evaluator services for optimised service placement in distributed heterogeneous cloud infrastructures

Optimal placement of demanding real-time interactive applications in a distributed heterogeneous cloud very quickly results in a complex tradeoff between the application constraints and resource capabilities. This requires very detailed information of the various requirements and capabilities of the applications and available resources. In this paper, we present a mathematical model for the service optimization problem and study the concept of evaluator services as a flexible and efficient solution for this complex problem. An evaluator service is a service probe that is deployed in particular runtime environments to assess the feasibility and cost-effectiveness of deploying a specific application in such environment. We discuss how this concept can be incorporated in a general framework such as the FUSION architecture and discuss the key benefits and tradeoffs for doing evaluator-based optimal service placement in widely distributed heterogeneous cloud environments