We show that it is possible to apply the divide-and-conquer principle in constructing a Markov model for sensor data from available sensor logs. The state space can be partitioned into clusters, for which the required transition counts or probabilities can be acquired locally. The combination of these local parameters into a global model takes the form of a system of linear equations with a confined solution space. Expected advantages of this approach lie for example in reduced (wireless) communication costs.
|Place of Publication||Enschede|
|Number of pages||18|
|Publication status||Published - 21 Dec 2007|
|Name||CTIT Technical Report Series|
|Publisher||Centre for Telematics and Information Technology, University of Twente|