Decentralized Compute Grids: Orchestrating Low‑Latency Inference Across Heterogeneous Edge Devices
Introduction Edge computing has moved from a niche research topic to a production‑grade reality. From autonomous drones to smart‑city cameras, billions of devices now generate data that must be processed in‑situ to meet stringent latency, privacy, and bandwidth constraints. Yet most deployments still rely on a single‑node model—each device runs its own inference workload or forwards raw data to a distant cloud. This approach wastes valuable compute resources, creates cold‑starts, and makes it difficult to scale sophisticated models that exceed the memory or power envelope of a single device. ...