Random Trip Models
Milan Vojnovic
Random mobility models have been used extensively by a wide community of
researchers for the purpose of analysis and simulation-based studies of
mobile ad-hoc networks. It is thus surprising that some of the mobility
models were ill-defined (non-existence of steady-state). Existence of a
unique steady-state is important to evaluate long-run behaviour of a
protocol under consideration. For well-defined mobility models, in
general, starting from an initial distribution of the mobility state,
there is initial transient phase during which the distribution of the
state converges to a steady-state distribution. A common practice is to
truncate the initial simulation run with the aim to eliminate the effect
of the transient. The problem is that for some mobility models the
initial transient lasts a long time -- for some models, as long as
typical duration of a simulation run!
The talk presents Random Trip Models, a broad class of mobility models
that accommodates many existing mobility models in one; e.g. widely-used
random waypoint. Random trip models are featured with having a unique
steady-state distribution. We give a ready-to-use perfect sampling
algorithm to sample the initial mobility state, so that mobility is in
steady-state throughout a simulation, i.e. simulation is perfect. The
algorithm alleviates knowing geometric normalization constants in the
cases where they are difficult to compute -- a bound on diameter of the
mobility domain suffices. Our perfect sampling is implemented in a tool
to use with ns-2 network simulator.
Joint work with Jean-Yves Le Boudec (EPFL), Santashil PalChaudhuri (Rice
University)
Reference:
IEEE INFOCOM 2005 (to appear);
http://icwww.epfl.ch/publications/abstract.php?ID=200459
|
