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Throughout the years, biological processing demands have been addressed by relying on the design of algorithmic approaches for parallel architectures. By taking advantage of multicore processor systems, we can deal with the main sources of complexity which explain the NP-hard nature of multiple problems in computational biology. In this work, we address the inference of phylogenetic topologies by...
Currently, wavelength division multiplexing technology is widely used for exploiting the huge bandwidth of optical networks. It allows simultaneous transmission of traffic on many nonoverlapping channels (wavelengths). These channels support traffic demands in the gigabits per second (Gb/s) range; however, since the majority of devices or applications only require a bandwidth of megabits per second...
This work presents a novel parallel multiobjective approach based on the Artificial Bee Colony algorithm for grooming low-speed traffic requests onto high-capacity optical channels. The traffic grooming problem in mesh optical networks is an NP-hard problem, so the usage of metaheuristics and parallelism jointly for increasing the network performance is a great option in order to reduce execution...
This paper presents a multi-objective swarm optimization algorithm for scheduling experiments across the Grid. In a sense, MOABC (Multi-Objective Artificial Bee Colony) is implemented to optimize the scheduling of an experiment with dependent jobs respect to the minimization of its execution time and cost. The main advantage in this approach is that it provides decision support for the final user...
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