Ecosystem Flow

This graph plots simplified analytic functions that approximate how load and security checks propagate through a Quantum‑Safe MCP deployment. Each colour corresponds to one subsystem; the overlay demonstrates the compound effect on final, policy‑filtered throughput.

Client Input Rate U(t) - Black curve

Represents external requests—model inferences, policy updates, or key‑rotation commands—arriving at the platform. We approximate a cyclic day‑night usage pattern with a shifted sine:

$$U(t)=1+\sin(t)$$

MCP Console Dispatch C(t) - Green curve

The Console accepts user traffic, attaches context metadata, and forwards the job to an available enclave. Its capacity scales the incoming wave by a factor 2 (extra batching, caching, and queueing efficiency):

$$C(t)=2\bigl(1+\sin(t)\bigr)$$

Peaks mark surge periods when the Console pipelines requests aggressively toward runtimes.

Enclave Runtime Output R(t) - Purple curve

Inside each TEE, the model executes; quantum‑secured sealing adds slight latency jitter, model complexity adds phase shift. We model that with a combined sine + cosine term:

$$R(t)=3\sin(t)+2\cos(t)$$

The higher amplitude reflects heavy compute bursts during complex inference.

Post‑Quantum Attestation Confidence A(t) - Blue curve

Every enclave response is signed and verified. A sigmoid captures the probability that an attestation passes on the first try versus requiring re‑challenge when load is high (the sigmoid uses the Console load as input):

$$A(t)=\frac{1}{1+e^{-0.5\,C(t)}}$$

When dispatch traffic spikes, the curve flattens near 1, indicating continuous but still‑valid proofs.

 Policy‑Engine Throughput P(t) - Green & Purple overlap

The Policy Engine releases only data that satisfy leakage and rate rules. We scale the compute output by the attestation confidence and add a small constant 0.2 that represents baseline system messages (health pings, key‑rotation notices):

$$P(t)=R(t)\,A(t)+0.2$$

Overlaying P(t) atop the run‑time and attestation curves shows how security gates throttle raw enclave output into a smooth, policy‑compliant stream.

Interpretation

• Oscillation alignment between U(t) and C(t) demonstrates that the Console can elastically match client demand.

• R(t) spikes above C(t)—enclaves amplify compute intensity relative to request count.

• A(t) never drops below 0.5, signalling that post‑quantum attestations remain reliable even when request volume surges.

• The final P(t) overlay confirms the platform’s goal: consistent, auditable throughput that is bounded by both compute capacity and security verification, ready for anchoring to the inter‑chain Audit Ledger.