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More than 40% of the world's population is not connected to the internet,majorly due to the lack of adequate infrastructure. Our work aims to bridgethis digital divide by proposing solutions for network deployment in remoteareas. Specifically, a number of access points (APs) are deployed as aninterface between the users and backhaul nodes (BNs). The main challengesinclude designing the number and location of the APs, and connecting them tothe BNs. In order to address these challenges, we first propose a metric calledconnectivity ratio to assess the quality of the deployment. Next, we propose anagile search algorithm to determine the number of APs that maximizes thismetric and perform clustering to find the optimal locations of the APs.Furthermore, we propose a novel algorithm inspired by infection dynamics toconnect all the deployed APs to the existing BNs economically. To support theexisting terrestrial BNs, we investigate the deployment of non-terrestrial BNs,which further improves the network performance in terms of average hop count,traffic distribution, and backhaul length. Finally, we use real datasets from aremote village to test our solution.

Network Graph Generation through Adaptive Clustering and Infection Dynamics: A Step Towards Global Connectivity