We present the wireless manifold, a 2-dimensional surface in 3-dimensional space with the property that geodesic
distances accurately capture wireless signal strengths.
A compact representation of the manifold can be reconstructed from a sparse set of signal measurements.
The manifold distance suggests a simple routing algorithm that avoids obstacles, naturally handles mobile
nodes without explicitly maintaining the connectivity
graph and is more efficient compared to using Euclidean
distance as measured by success rate, routing load and
failure tolerance. Placing sensors to cover the manifold
is more effective than covering the underlying physical
space.