MDM Zero-Touch Enrollment — Retrial Queue CTMC (2D)
Interactive 2D simulation of MDM zero-touch enrollment as a constant/linear retrial queue: an exact continuous-time Markov chain (Gillespie stochastic simulation algorithm) with Poisson arrivals, exponential CA signing, and per-device exponential-backoff retrial timers — live Little's-Law and utilization checks against queueing theory.
This 2D companion models the same MDM zero-touch enrollment bottleneck as the 3D scene, but computes it as a true continuous-time Markov chain rather than a per-frame tick loop. Devices arrive as a genuine Poisson process, the certificate authority signs with an exponential service clock, and every device that fails does not queue up FIFO-style — it joins an "orbit" and keeps retrying on its own independent exponential clock, exactly the classic queueing-theory retrial-queue model used for contention-based re-registration systems. Each simulation step is drawn with the Gillespie stochastic simulation algorithm, so the on-screen dynamics are an exact realization of the chain, not an approximation. The panel tracks two identities that must hold for any lossless single-server queue — utilization ρ = λ/μ and Little's Law L = λ·W — live against the running simulation, turning the sliders into a real capacity-planning and queueing-theory verification tool.
A 2D exact continuous-time Markov chain (Gillespie stochastic simulation algorithm) model of MDM zero-touch enrollment as a retrial queue: devices arrive as a genuine Poisson process, a CA server signs with an exponential clock, and failed devices join an orbit where each retries independently on its own exponential backoff clock rather than a FIFO line. Live stats verify utilization rho = lambda/(mu*(1-failRate)) and Little's Law L = lambda_eff*W against the running simulation.
2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install