Composite Fleet Health Assessment

Mechanism

The mechanism begins at the per-device tier, where each device produces a health attestation drawn from three classes of evidence. First, hardware identity evidence is anchored by a PUF whose challenge-response pairs are bound at provisioning to a manufacturer-issued credential; the attestation includes a freshly evaluated PUF response over a challenge nonce that is itself part of the chain trust substrate. Second, software integrity evidence is anchored by an SBOM whose component hashes are verified against a curated allow-list and whose runtime measurement record (boot measurements, kernel attestation, container image attestation) is signed by the device's measured-boot subsystem. Third, tamper-evident telemetry evidence is drawn from sealed sensors, intrusion detectors, environmental monitors, and anomaly detectors whose outputs are signed at the source and aggregated under a per-device monitoring authority.

Per-device attestations are admitted as primitive events by the fleet-level composition. The composition enumerates the population of devices in scope, requests current attestations from each, and produces a fleet-level credentialed observation whose structure includes the count and identity of admitted devices, the count and identity of refused or unreachable devices, the per-device evidence summary, and a fleet-level fitness vector derived from the per-device data. The fleet-level observation is signed by a fleet monitoring authority whose credentials authorize it to emit composite events on behalf of the population.

Aggregate decline is realized by the composition rule. As individual devices degrade, fail attestation, suffer credential revocation, or exit the trust envelope, their contributions are removed or downgraded in the composite. The composite is monotone in the sense that loss of admissible devices cannot improve the aggregate; recovery requires that devices re-attest successfully and re-enter the population. The composite admits four categories of operational decision: engagement of an admissible subset (when partial fleet capacity suffices), deferral of fleet-wide engagement (when the composite falls below an engagement threshold), retirement by class (when correlated evidence implicates an entire device class, for example a firmware version or a manufacturing batch), and graduation (when newly attested devices are admitted into the population).

Operating Parameters

The PUF tier is parameterized by challenge-response pair length, evaluation cadence, error-correction tolerance, and freshness window. Typical deployments use silicon PUFs with 128-bit responses, evaluated on each attestation cycle, with bounded fuzzy-extractor error correction and freshness windows of seconds to minutes depending on operational tempo. The SBOM tier is parameterized by component-list completeness, hash algorithm, allow-list version, and revocation-list horizon. Measured-boot evidence is parameterized by the depth of the measurement chain, the reference-value source, and the attestation key's binding to the hardware root of trust.

Tamper-evident telemetry is parameterized by sensor coverage (which physical and logical channels are observed), sampling cadence, anomaly-detection thresholds, and signing latency. The composition rule is parameterized by population definition, engagement threshold, deferral threshold, retirement-by-class trigger conditions, and graduation policy. Population definition may be static (a fixed set of identifiers), dynamic (a query against a fleet registry), or scoped (devices within a declared geographic, mission, or class boundary).

Fitness vectors carry per-dimension scores including hardware integrity, software integrity, tamper status, mission-readiness, and class-specific operational metrics. Engagement and deferral thresholds are expressed as constraints over the fitness vector, supporting decisions that depend on multi-dimensional sufficiency rather than a single scalar. Retirement-by-class triggers fire when correlated evidence (shared firmware version, shared component lot, shared environmental exposure) crosses a population-fraction threshold, indicating that the issue is class-level rather than device-level.

Alternative Embodiments

One embodiment confines composition to a single homogeneous device class, producing a class-specific composite. A second embodiment composes across heterogeneous classes (mixing, for example, drones, ground sensors, and edge compute nodes) using a class-weighted fitness vector whose weights reflect operational importance. A third embodiment supports nested composition, in which sub-fleets emit intermediate composites that are then composed into a higher-level composite, supporting hierarchical operations such as squadron-of-squadrons or region-of-substations.

A further embodiment runs continuous composition with streaming attestations, producing a rolling composite that updates as devices report. Another embodiment runs episodic composition, producing composites only at decision points (mission engagement, scheduled maintenance windows, regulatory reporting cadences). An embodiment for adversarial environments employs byzantine-robust aggregation to resist devices reporting false attestations, requiring corroborating peer attestations before admitting individual contributions.

Composition with Other Primitives

Composite fleet health composes with cascade-propagation: a fleet-level refusal observation propagates to downstream consumers as a primitive event admissible under the same rules that govern any other observation. A scheduling system, an allocation engine, or a partner fleet may admit the refusal and adjust its operations accordingly without consulting the underlying device-level evidence directly.

Composition with the governed marketplace supplies fleet capacity attestations as inputs to commodity-class allocation. A fleet of charging stations may attest its aggregate available capacity into a grid-services class allocation; a fleet of compute nodes may attest its aggregate available throughput into a compute-capacity class allocation; a fleet of vessels may attest its aggregate berth utilization into a port-services class. The same composite event serves as both an operational status and a market-facing capacity declaration.

Composition with runtime-signed artifacts ensures that the analysis primitives, fitness-vector weights, threshold definitions, and retirement-by-class trigger logic are themselves signed and admitted under capability-scope discipline, so that fleet-level composition cannot be silently subverted by altered analytics. Composition with the bilateral primitive supports cross-fleet attestation exchange between operationally independent fleets that need to admit one another's capacity claims.

Distinction from Prior Art

Conventional fleet management systems aggregate device telemetry into dashboards and alerts, but they do not produce credentialed observations, do not bind aggregation to a chain trust substrate, and do not admit composite events as inputs to other primitives in a structurally disciplined manner. Conventional remote attestation frameworks attest individual devices but provide no native composition into population-level credentials, leaving aggregation to ad-hoc tooling.

Conventional fleet-level analytics in domains such as wind turbines, vehicle fleets, and data-center hardware employ statistical aggregation and condition monitoring, but the aggregate is consumed within the operator's own boundary; it is not a credentialed primitive that downstream consumers in other organizations or other primitives may admit. The present mechanism unifies per-device attestation, population-level composition, monotone aggregate decline, structured operational decision categories, and composability with cascade-propagation, governed-marketplace, and runtime-signing primitives into a single disclosed composition.

Worked Examples

Consider a fleet of one thousand distributed energy resource controllers participating in a grid-services market. Each controller produces a per-device attestation every fifteen seconds, drawing PUF responses from a hardware security element, SBOM verification from the most recent firmware update, and tamper-evident telemetry from sealed enclosure sensors. The fleet monitoring authority composes these into a rolling fleet attestation that declares, at each composition interval, the count of admitted controllers, the aggregate kilowatt response capability, and the fitness-vector summary. When ten percent of the controllers report a shared firmware-version anomaly within a single composition window, the retirement-by-class trigger fires; the composite declares the affected version retired pending remediation, and the aggregate capacity declines accordingly. The grid-services market admits the new aggregate as the controlling capacity declaration for the next allocation cycle.

Consider a fleet of fifty unmanned ground vehicles supporting a critical-infrastructure inspection mission. Per-device attestations include PUF identity, signed firmware measurements, intrusion-detector status, and mission-payload calibration. The fleet composite is consumed by a mission-engagement decision: at engagement time, only the admissible subset proceeds; vehicles that fail attestation are deferred. If the composite falls below the engagement threshold, the entire mission is deferred and the deferral observation propagates to the operations cell, which admits it as a cascade-propagation event and triggers spare-fleet engagement under a separate composite. Throughout, the lineage record retains every attestation, every refusal, and every composition decision, enabling post-mission audit without recourse to off-system reconciliation.

Disclosure Scope

This disclosure covers the per-device attestation structure spanning PUF, SBOM, and tamper-evident telemetry; the fleet-level composition rule and the resulting credentialed observation; the parameters governing population scope, engagement threshold, deferral threshold, retirement-by-class triggers, and graduation policy; the fitness-vector representation; and the composition interfaces with cascade-propagation, governed-marketplace, runtime-signed artifacts, and bilateral exchange. Application domains include defense fleets, civilian critical-infrastructure fleets, distributed energy resource aggregations, autonomous vehicle fleets, robotics deployments, sensor networks, and any other population whose operation requires structurally credentialed aggregate fitness.

The composite fleet health primitive is disclosed in Provisional Application No. 64/049,409 as a secondary embodiment of the health-monitoring chain primitive, and the structural features described herein — monotone aggregate decline, credentialed population observation, retirement-by-class trigger logic, and composition with cascade-propagation and governed-marketplace primitives — are presented as the disclosed reduction-to-practice rather than as bounds on the underlying primitive's scope across alternative population classes and credentialing roots.