Non-additive collaborative information coverage for cellular-model deployment in sensor networks

The information acquisition capabilities of networked sensors are affected by environmental factors in real deployment, such as the shadowing effects, and it is imperative to have practical considerations at the design stage in order to anticipate this information acquisition behavior. Due to the imperfection of information acquisition in sensor networks, this paper generalizes the information coverage from probability space to Sugeno measure space, and proposes a new notion of non-additive collaborative information coverage based on Sugeno measure to evaluate the coverage capabilities. The experiment results show that non-additive collaborative information coverage approach not only can reduce to the probability coverage approach for the perfect information acquisition scenario, but also can adjust the parameters adaptively to handle different information acquisition behavior in a practical sensor network, which is a more ubiquitous information coverage approach.