Abstract | Motivated by the problem of efficiently collecting data from
wireless sensor networks via a mobile sink, we present an accelerated
random walk on Random Geometric Graphs. Random
walks in wireless sensor networks can serve as fully local,
very simple strategies for sink motion that significantly
reduce energy dissipation but introduce higher latency in the
data collection process. While in most cases random walks
are studied on graphs like Gn,p and Grid, we define and experimentally
evaluate our newly proposed random walk on
the Random Geometric Graphs model, that more accurately
abstracts spatial proximity in a wireless sensor network. We
call this new random walk the ã-stretched random walk, and
compare it to two known random walks; its basic idea is
to favour visiting distant neighbours of the current node
towards reducing node overlap. We also define a new performance
metric called Proximity Cover Time which, along
with other metrics such as visit overlap statistics and proximity
variation, we use to evaluate the performance properties
and features of the various walks. |