Abstract
Speedup in distributed executions of Constraint Logic Programming (CLP) applications are directed related to a good constraint partitioning algorithm. In this work we study different mechanisms to distribute constraints to processors based on straightforward mechanisms such as Round-Robin and Block distribution, and on a more sophisticated automatic distribution method, Grouping-Sink, that takes into account the connectivity of the constraint network graph. This aims at reducing the communication overhead in distributed environments. Our results show that Grouping-Sink is, in general, the best alternative for partitioning constraints as it produces results as good or better than Round-Robin or Blocks with low communication rate.

Abstract
One of the challenges in Grid computing research is to provide a means to automatically submit, manage, and monitor applications whose main characteristic is to be composed of a large number of tasks. The large number of explicit tasks, generally placed on a centralized job queue, can cause several problems: (1) they can quickly exhaust the memory of the submission machine; (2) they can deteriorate the response time of the submission machine due to these demanding too many open ports to manage remote execution of each of the tasks; (3) they may cause network traffic congestion if all tasks try to transfer input and/or output files across the network at the same time; (4) they make it impossible for the user to follow execution progress without an automatic tool or interface; (5) they may depend on fault-tolerance mechanisms implemented at application level to ensure that all tasks terminate successfully. In this work we present and validate a novel architectural model, GRAND (Grid Robust ApplicatioN Deployment), whose main objective is to deal with the submission of a large numbers of tasks. Copyright (c) 2006 John Wiley & Sons, Ltd.

Abstract
Several international Projects and Collaborations have emerged in the last years due to the increasing demand for Grid resources. One important aspect of these initiatives deals with the gridification of computing intensive scientific applications otherwise difficult to run efficiently. The EELA Project (E-Infrastructure shared between Europe and Latin America) is a collaboration of Latin America and Europe Institutions which has developed a performance e-Infrastructure for e-Science applications in the fields of Biomedicine, High Energy Physics, e-Learning and Climate. Nowadays many groups have already ported their applications on the EELA Grid and are obtaining first results. This paper describes the first year of EELA and the progress achieved so far.

Abstract
In this paper we present the development, implementation and simulation of a simple Distributed Hash Table (DHT) protocol for a Peer to peer (P2P) overlay network inspired by small world [3, 2] concepts. Our simulation and implementation, done on the Peersim [10] java network simulator, showed results consistent with other state of the art DHT implementations with a more simple and pragmatic approach for the graph construction algorithm. We present the results Of Simulating this protocol on large P2P networks and compare them with the results obtained in Symphony [14], another small world inspired DHT.

Abstract
Programming contests should be capable of being appealing to both the contestants and the general public. We feel that the use of graphical user interfaces and computer graphics could help achieve this goal, providing new ways of viewing the task. We describe experiments we made with games (Tic-Tac-Toe, Snake and Ataxx, an Othello-like game), which were made available to students with graphical components, and discuss the results. We also present a simple graphic library where simple drawings can be made and show how it can be used in a programming contest environment. We then conclude by revisiting some past IOI problems, suggesting ways to enhance them with graphical components.

Abstract
This paper describes a fully complete autonomous hybrid robot system, named YAM (Yet Another Mouse), that is able to navigate through an unknown maze environment. YAM effectively tackles the problem of how to represent the environment using its sensor data to produce probability maps of the walls and beacons. Besides that, it is capable of computing long-term path plans using an adapted breadth-first search algorithm. It also shows how it is possible to model the actual motors behavior as a reactive task, using artificially created virtual short-term goals. We give real contest results, showing how YAM behaved on the "CiberRato" robotics competition.