Metaheuristic approaches for optimal broadcasting design in metropolitan MANETs

11th International Conference on Computer Aided Systems Theory. Las Palmas de Gran Canaria, Spain, February 12-16, 2007Mobile Ad-hoc Networks (MANETs) are composed of a set of communicating devices which are able to spontaneously interconnect without any pre-existing infrastructure. In such scenario, broadcasting becomes an operation of tremendous importance for the own existence and operation of the network. Optimizing a broadcasting strategy in MANETs is a multiobjective problem accounting for three goals: reaching as many stations as possible, minimizing the network utilization, and reducing the duration of the operation itself. This research, which has been developed within the OPLINK project (http://oplink.lcc.uma.es), faces a wide study about this problem in metropolitan MANETs with up to seven different advanced multiobjective metaheuristics. They all compute Pareto fronts of solutions which empower a human designer with the ability of choosing the preferred configuration for the network. The quality of these fronts is evaluated by using the hypervolume metric. The obtained results show that the SPEA2 algorithm is the most accurate metaheuristic for solving the broadcasting problem.Publicad

Front-end process modeling in silicon

Front-end processing mostly deals with technologies associated to junction formation in semiconductor devices. Ion implantation and thermal anneal models are key to predict active dopant placement and activation. We review the main models involved in process simulation, including ion implantation, evolution of point and extended defects, amorphization and regrowth mechanisms, and dopant-defect interactions. Hierarchical simulation schemes, going from fundamental calculations to simplified models, are emphasized in this Colloquium. Although continuum modeling is the mainstream in the semiconductor industry, atomistic techniques are starting to play an important role in process simulation for devices with nanometer size features. We illustrate in some examples the use of atomistic modeling techniques to gain insight and provide clues for process optimization