Estimation of Distances to Integrate the National Fiber Optic Backbone Network into the Peruvian Army

Abstract

Data transport networks are vital strategic infrastructures that enable interconnection between countries, governments, and populations. In Australia, the National Broadband Network (NBN) has expanded digital service access to remote areas by combining fiber optics, satellite, and wireless technologies. Similarly, Peru developed the National Fiber Optic Backbone Network (RDNFO) to bridge the digital divide and provide internet access to rural and vulnerable communities. However, the Peruvian Army has limited connectivity to this network, relying in part on the private operator NEXTNET, which involves high installation and maintenance costs. To address this challenge, this study presents a tool that estimates distances between Army units and RDNFO nodes, aiming to optimize fiber optic network design and deployment. Developed using Google Apps Script—a JavaScript-based environment that automates tasks and integrates geospatial data through Google Maps API—the tool improves planning efficiency. Applied to the Army’s III Division (III-DE), it estimated distances with an average error of 12.41%, adding 23.446 kilometers and an extra cost of USD 18,756.80. Despite this added cost, the tool offers enhanced accuracy and reliability, reducing potential deployment risks and supporting more strategic decisions in extending military connectivity through the national fiber optic infrastructure.