Graph-based mobility model for urban areas fueled with real world datasets

Mobile ad-hoc networks (MANETs) and especially mobile Wireless Sensor Networks (mWSNs) are embedded in the environment and therefore stand under strong influence of its specific characteristics. Beside e.g. sensor input, nodes motion patterns are supposed to be a very basic factor regarding performance. Hence simulations may need to account scenario specific mobility patterns while keeping the tradeoff related to simulation complexity in mind. This contribution proposes a graph based mobility model, designed to resemble probabilistic node movements according to real world node paths like they may be induced by road grids. The model is presented along with a real world mWSN sample deployment from which the paths are extracted and against which the simulation fine-tuned.

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