Positioning systems in self-organizing networks generally rely on
measurements such as delay and received signal strength, which may be difficult
to obtain and often require dedicated equipment. An alternative to such
approaches is to use simple connectivity information, that is, the presence or
absence of a link between any pair of nodes, and to extend it to hop-counts, in
order to obtain an approximate coordinate system. Such an approximation is
sufficient for a large number of applications, such as routing. In this paper,
we propose Jumps, a positioning system for those self-organizing networks in
which other types of (exact) positioning systems cannot be used or are deemed
to be too costly. Jumps builds a multiple coordinate system based solely on
nodes neighborhood knowledge. Jumps is interesting in the context of wireless
sensor networks, as it neither requires additional embedded equipment nor
relies on any nodes capabilities. While other approaches use only three
hop-count measurements to infer the position of a node, Jumps uses an arbitrary
number. We observe that an increase in the number of measurements leads to an
improvement in the localization process, without requiring a high dense
environment. We show through simulations that Jumps, when compared with
existing approaches, reduces the number of nodes sharing the same coordinates,
which paves the way for functions such as position-based routing
