  Internet-of-Things (IoT) devices are low size, weight and power (SWaP), low
complexity and include sensors, meters, wearables and trackers. Transmitting
information with high signal power is exacting on device battery life,
therefore an efficient link and network configuration is absolutely crucial to
avoid signal power enhancement in interference-rich environment and resorting
to battery-life extending strategies. Efficient network configuration can also
ensure fulfilment of network performance metrics like throughput, coding rate
and spectral efficiency. We formulate a novel approach of first localizing the
IoT nodes and then extracting the network topology for information exchange
between the nodes (devices, gateway and sinks), such that overall network
throughput is maximized. The nodes are localized using noisy measurements of a
subset of Euclidean distances between two nodes. Realizable subsets of
neighboring devices agree with their own position within the entire network
graph through eigenvector synchronization. Using communication global
graph-model-based technique, network topology is constructed in terms of
transmit power allocation with the aim of maximizing spatial usage and overall
network throughput. This topology extraction problem is solved using the
concept of linear programming.
