Configuring Multi-Objective Evolutionary Algorithms for Design-Space Exploration of Wireless Sensor Networks

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Wireless Sensor Networks (WSNs) consist of numerous sensor nodes with several possible configurations for each node. As there are a lot of nodes in a typical WSN, each with its own set of configurations, the number of configurations for the network as a whole is huge and the design space is extremely large. The configuration of a WSN has a strong effect on the quality of services of running applications and the performance of the WSN. Multi-objective Evolutionary Algorithms (EAs) are well suited to explore the trade-offs in a WSN design space. However, an EA has many configuration parameters in itself.