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We present a study on the intricate problem of the simulation of large scale complex networks. The complexity of the simulation is due to the need to represent networks with a high number of nodes and links, but even more to the need to model interactions among network nodes. We focus on discrete-event simulation, a simulation methodology that enables both sequential (i.e. monolithic) and parallel/distributed simulation (i.e. PADS) approaches. We discuss performance and scalability requirements that the simulator should have. We also discuss the need to have practical methods to easily build simulation models. In this sense, an agent-based simulation approach facilitates the model definition. To demonstrate the viability of this simulation technique, we focus on a tool we built to simulate complex networks. The tool exploits adaptive partitioning mechanisms, which are essential to reduce the communication overhead in the PADS. An experimental evaluation has been conducted using different network topologies and simulator setups. Results demonstrate the feasibility of the approach to simulate complex networks.