We present an algorithm to migrate multidimensional
data in a non-replicated distributed environment.  
Our proposed algorithm is intented to improve
query performance for mobile objects.
Our algorithm automatically 
detects access pattern changes and 
migrates portions of the data from current sites of residence to
sites recently accessing the data most frequently, thus 
reducing remote communication costs.  
We assume the data is indexed by an R-tree 
multidimensional index and that a global R-tree is used to 
locate and retrieve portions of the data set.  
We present a distributed R-tree structure
% suggest a few alternatives for detecting when migration is necessary, 
and experimentally
explore a specific access detection and migration mechanism.  
Our experimental results show that 
when compared to the no-migration case, and depending on network speed,
our migration scheme may result in a query time reduction of 
a few percent to an order of magnitude.