Relay Placement Algorithms for Communication in a Heterogeneous Propagation Environment

A vast majority of the IoT devices will be connected in a topology where edge-devices push data to a local gateway which in turn forward the data to the cloud for analytics and archiving. In large networks, many edge-nodes will be located far away from their nearest gateways. Due to their locations and limited transmission power, these edge-nodes might experience poor network coverage. To provide reliable connectivity to these edge-nodes, relays/repeaters may have to be placed at a few locations until a gateway is reached. Network deployment engineers often do this based on field visits, surveys, measurements, initial deployments, followed by fine-tuning. For the scalability of such deployments, automated network planning tools are essential. Such tools should be able to predict coverage based on the edge-node locations using perhaps GIS data, identify the need for relays/repeater and, if needed, suggest the number and locations of relays, in order to provide reliable connectivity. This entire process should be as fast and automated as possible for rapid network deployment. In this paper, using a black box RSSI estimator between any candidate pair of transceiver locations, we propose a network deployment framework that uses either Ant Colony Optimisation (ACO) or Differential Evolution (DE) to identify the number and location of relays for meeting specified quality of service constraints. We also show how to handle multiple gateways.