Smarter job scheduling cuts waste on today's quantum cloud hardware

Current cloud quantum platforms rely on simple priority queues that ignore fidelity, latency, and inter-device communication costs when scheduling jobs. This work models distributed quantum workflows as graphs and applies modified graph algorithms to match program components to the best available devices across a hybrid classical-quantum network. Tested empirically, the approach yields roughly 5% faster execution, 30% lower communication overhead, 40% shorter wait times, and a 2% fidelity gain over existing schedulers. The framework is aimed squarely at the constraints of present-day NISQ hardware, where no single device is large enough to run ambitious applications alone.