Mobile Ad-hoc Networks are used in many scenarios (e.g., emergency management) for supporting collaborative work of operators. But this requires either (i) continuous connections, or at least (ii) the possibility to foresee that a device is going out and disconnecting (e.g., in order to locally cache important data needed for the following activities, etc.). Therefore a basic problem is how to predict the possible disconnections of devices, in order to let the upper layers appropriately address connection anomalies (e.g., either taking global remedial actions to maintain the network connected, or local ones to let the disconnecting device to go on for some time with its own work). In
this paper we present a bayesian approach to predict disconnections in MANETs, and validating experimental results that show the viability of the approach.