Teaching about Madrid: A Collaborative Agents-Based Distributed Learning Course

Interactive art courses require a huge amount of computational resources to be running on real time. These computational resources are even bigger if the course has been designed as a Virtual Environment with which students can interact. In this paper, we present an initiative that has been develop in a close collaboration between two Spanish Universities: Universidad Politécnica de Madrid and Universidad Rey Juan Carlos with the aim of join two previous research project: a Collaborative Awareness Model for Task-Balancing-Delivery (CAMT) in clusters and the “Teaching about Madrid” course, which provides a cultural interactive background of the capital of Spain

Design of a generic platform for efficient and scalable cluster computing based on middleware technology

In this paper, we address the design of a generic and scalable platform for cluster computing. The architecture of the platform is based on middleware technology in order to ensure easy distribution of the software components along the participating workstations and to exploit advanced communication techniques, such as event notification and object registration. The computational tasks are referred to as Intelligent Agents, which are software agents that are capable of executing particular algorithms on input data. The developed platform offers advanced features such as transparent load balancing, task scheduling, run time compilation of agent code and migration of tasks. The architecture of the platform will be outlined front a computational point of view and each component will be described in detail. Furthermore, the engineering aspects of the platform will be covered. lit addition. a sample scenario for computational tasks in the area of telecommunication network design and management will be described