The incremental view maintenance problem deals with the efficient
  updating of materialized views in response to updates to base relations.
  This paper considers the problem in a distributed database environment,
  with communication cost minimization as the primary objective.  The views
  considered are defined based on the relational join operation.  The
  approach is to use ``yes''/``no'' tags as auxiliary data on tuples in the
  base relations to indicate whether the tuples participate in joins. These
  tags will help avoid sending irrelevant data over the network and thus
  reduce the communication cost. Two basic view maintenance algorithms are
  proposed using the tags. In addition to reducing communication costs, an
  important feature of these two basic algorithms is that they derive the
  ``exact change'' to views without looking at the old views. This feature
  allows us to maintain certain aggregates on views without actually
  materializing the views themselves; this feature is useful in 
  applications such as active databases where many conditions or constraints
  must be tested whenever updates occur, since a condition is true
  exactly when some corresponding view has nonzero number of tuples. 
  The paper
  then combines the use of tags with the counting algorithm \cite{GMS93}
  to derive a tagged counting algorithm that further reduces the
  communication cost.  The paper illustrates the algorithms by examples and
  studies their performance via a statistical analysis.  The illustrating
  examples and the performance analysis show that, under uniform
  distribution with reasonable join participation rates, the use of tags
  significantly improves the efficiency of view maintenance over similar
  algorithms without tags. The performance analysis also identifies the
  situations where a particular algorithm is superior to others. The use of
  tags for memoing values of subexpressions in a view definition is also
  explored in the paper.