Sensor networks are used for applications in monitoring
harsh environments including reconnaissance and surveillance
of areas that may be inaccessible to humans. Such applications
depend on reliable collection, distribution and delivery of
information to processing centres which may involve multi-hop
wireless networks which experience disruptions in communication
and exhibit packet drops, connectivity loss and congestion.
Some of these faults are periodic, attributed to external, recurring
factors. In this paper, we study an effective way to forecast
such repetitive conditions using time-series analysis. We, further,
present an application-level, autonomic routing service that
adapts sensor readings routes to avoid areas in which failures or
congestion are expected. A prototype system of the approach is
developed based on an existing middleware solution for sensor
network management. Simulation results on the performance of
this approach are also presented