MTS-1: A Lightweight Delta-Encoded Telemetry Format optimised for Low-Resource Environments and Offline-First System Health Monitoring

TL;DR

MTS-1 is a new lightweight, delta-encoded telemetry format optimized for low-resource environments, offering significant payload size reductions and efficiency improvements over existing formats for offline and bandwidth-constrained system monitoring.

Contribution

The paper introduces MTS-1, a novel delta-encoded binary telemetry format tailored for offline-first, low-resource, and energy-efficient system health monitoring environments.

Findings

Up to 74.7% payload size reduction compared to JSON

Up to 5.4% reduction compared to MessagePack

Linear scaling in compression efficiency across dataset sizes

Abstract

System-level telemetry is fundamental to modern remote monitoring, predictive maintenance, and AI-driven infrastructure optimisation. Existing telemetry encodings such as JSON, JSON Lines, CBOR, and Protocol Buffers were designed for high-bandwidth, always-online environments. They impose significant overhead when deployed in bandwidth-constrained networks common across Sub-Saharan Africa, rural enterprise deployments, and unstable LAN environments. This paper introduces MTS-1 (Magenta Telemetry Standard v1), a novel delta-encoded binary telemetry format designed for offline-first system monitoring, LAN-assisted proxy delivery, and energy-efficient IoT-to-server transmission. We compare MTS-1 against JSON, JSON Lines, CBOR, MessagePack, and Protocol Buffers across payload size, encoding cost, network efficiency, and cost-latency performance. Synthetic benchmarking demonstrates preliminary compression improvements of up to 74.7% versus JSON and 5.4% versus MessagePack, with linear scaling characteristics across dataset sizes.