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Edge Data Aggregation: Sensor Bandwidth Reduction

Interactive edge-computing simulator: watch a field of remote geological sensors stream raw readings to a local edge node, which aggregates and delta-filters them before forwarding over a bandwidth-limited backhaul link to the cloud — tune sampling rate, aggregation window, change threshold and link capacity and watch bandwidth, utilization and latency respond live.

Geology & Earth Science2DModerate60 FPS📱 Mobile-adapted🌍 Earth

This simulation explores the core resource-allocation trade-off in edge computing: a field of remote sensors — such as instruments at a geological survey site — generates far more raw data than a slow backhaul link to the cloud can carry. Processing that data closer to the source, at a local edge node, lets you filter out redundant readings before they ever leave the site. Here a ring of sensor nodes streams samples at a chosen rate to a central edge node, which buffers them over an aggregation window and forwards only the readings that have changed by more than a threshold. Tune the sensor count, sampling rate, aggregation window, change-detection threshold and link capacity, and watch the raw versus edge-forwarded data rates, bandwidth reduction, backhaul utilization and estimated queueing latency respond live as packets animate from sensors to the edge node and on to the cloud.

⚙ Under the hood

This simulation allows you to explore the core principles of advanced edge computing, where data processing is performed closer to the source – often in remote locations like a geological survey site – to reduce latency and improve real-time decision-making. By manipulating network parameters and sensor data, you can observe how these factors impact system performance and resource allocation.

Edge Computing

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install