Low-Load Distributed Data Networks: Concept, Classification and Comparative Analysis

This article introduces the concept of a low-load distributed data network: a network in which the load on each node (traffic, storage, service state) is bounded by that node's own circle of participants and does not grow as the network grows. We show that the load classifications used in communications theory (utilization, erlangs, the "knee" and "cliff" points on the throughput-versus-load curve, quality-of-service classes) describe the state of a network at a given moment rather than a property of its architecture, and therefore cannot distinguish networks by this trait. We propose six traits of a low-load network and a classification LL-0…LL-3 by the asymptotic load on a node. We compare fifteen networks, from FidoNet (1984) to Nevod (2026), and name their predecessors in the literature: friend-to-friend (F2F) networks, delay-tolerant networks (DTN), distributed hash tables, local-first software and community networks. Keywords: distributed networks, decentralization, per-node load, scalability, F2F, DTN, peer-to-peer networks, messengers, Zero Knowledge Infrastructure.