  Inter-domain Traffic Engineering for multi-homed networks faces a scalability
challenge, as the size of BGP routing table continue to grow. In this context,
the choice of the best path must be made potentially for each destination
prefix, requiring all available paths to be characterised (e.g., through
measurements) and compared with each other. Fortunately, it is well-known that
a few number of prefixes carry the larger part of the traffic. As a natural
consequence, to engineer large volume of traffic only few prefixes need to be
managed. Yet, traffic characteristics of a given prefix can greatly vary over
time, and little is known on the dynamism of traffic at this aggregation level,
including predicting the set of the most significant prefixes in the near
future. %based on past observations. Sophisticated prediction methods won't
scale in such context. In this paper, we study the relationship between prefix
volume, stability, and predictability, based on recent traffic traces from nine
different networks. Three simple and resource-efficient methods to select the
prefixes associated with the most important foreseeable traffic volume are then
proposed. Such proposed methods allow to select sets of prefixes with both
excellent representativeness (volume coverage) and stability in time, for which
the best routes are identified. The analysis carried out confirm the potential
benefits of a route decision engine.
