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.