Topology maps and distance-free localization from partial virtual coordinates for IoT networks

While physical coordinates are useful for IoT and sensor network operations, physical localization is not a viable option for large-scale networks of simple devices in complex or harsh environments. Topology Preserving Maps (TPM) extracted from anchor-based Virtual Coordinates (VCs) are an attractive localization free alternative for physical maps. We present an approach, based on the theory of low-rank matrix completion, to extract TPMs with only partial information about VCs. Evaluation using 2D and 3D networks with random anchors shows that accurate TPMs can be obtained even when up to 40% to 60% of random coordinates are missing. Coordinate generation and communication cost thus may be reduced significantly. TPM generation can now also be based on a different VC system as long as it characterizes each node with distances to a small set of random nodes instead of a global set of anchors.