Before Agents Act: Assurance-Aware Semantic Scheduling for Evidence Acquisition in Distributed Systems

Abstract:Tool-using agents can initiate consequential infrastructure changes, yet evidence required for admission may expire while other checks run or depend on a shared fault domain. We formulate evidence acquisition as joint witness selection and scheduling under quorum, diversity, freshness, deadline, and resource constraints. Assurance-Aware Semantic Scheduling (AAS) combines integer-program selection, dispatch-aware temporal scheduling, bounded diagnostic expansion, and receipt-aware repair. Formal results state the assumptions needed for dispatch-time freshness and finite diagnostic expansion. In three generated infrastructure workloads, AAS produces 1,075/1,200 valid candidates versus 647/1,200 for constraint-aware forward scheduling; stale candidates fall from 440 to 12. Paired sensitivity studies reuse the same instances and operation latency draws across parameter settings. A corrected timeout intervention finds 18/20 admissions with repair or full resynthesis versus 0/20 for a static plan, with lower committed cost when receipts are reused. On 20 constructed cases requiring a certified decomposition cut, refinement recovers an oracle-matching feasible plan every time. These are controlled simulation results; the bounded oracle shares a temporal search component, and transfer to deployed systems remains untested.

30 pages, 5 figures, 3 tables. Extended manuscript with formal proofs and operation catalogue

Distributed, Parallel, and Cluster Computing (cs.DC); Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)

C.2.4; D.4.1; D.4.6; I.2.11

arXiv:2609.34376 [cs.DC]

(or arXiv:2609.34376v1 [cs.DC] for this version)

https://doi.org/10.48550/arXiv.2609.34376 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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