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This article investigates the functional properties of complex
networks used as grid computing systems. Complex networks following
the Erdös-Rényi model and other models with a preferential
attachment rule (with and without growth) or priority to the
connection of isolated nodes are studied. Regular networks are also
considered for comparison. The processing load of the parallel
program executed on the grid is assigned to the nodes on demand, and
the efficiency of the overall computation is quantified in terms of
the parallel speedup. It is found that networks with preferential
attachment allow lower computing efficiency than networks with
uniform link attachment. At the same time, considering only node
clusters of the same size, preferential attachment networks display
better efficiencies. The regular networks, on the other hand,
display a poor efficiency, due to their implied larger internode
distances. A correlation is observed between the topological
properties of the network, specially average cluster size, and their
respective computing efficiency
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