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Internet-of-Things (IoT) devices are low size, weight and power (SWaP), lowcomplexity and include sensors, meters, wearables and trackers. Transmittinginformation with high signal power is exacting on device battery life,therefore an efficient link and network configuration is absolutely crucial toavoid signal power enhancement in interference-rich environment and resortingto battery-life extending strategies. Efficient network configuration can alsoensure fulfilment of network performance metrics like throughput, coding rateand spectral efficiency. We formulate a novel approach of first localizing theIoT nodes and then extracting the network topology for information exchangebetween the nodes (devices, gateway and sinks), such that overall networkthroughput is maximized. The nodes are localized using noisy measurements of asubset of Euclidean distances between two nodes. Realizable subsets ofneighboring devices agree with their own position within the entire networkgraph through eigenvector synchronization. Using communication globalgraph-model-based technique, network topology is constructed in terms oftransmit power allocation with the aim of maximizing spatial usage and overallnetwork throughput. This topology extraction problem is solved using theconcept of linear programming.

IoT Localization and Optimized Topology Extraction Using Eigenvector Synchronization