Operational Reliability of Deadline-Constrained Task Assignment: Stability Characterization and Adversarial Routing

Operational Reliability of Deadline-Constrained Task Assignment: Stability Characterization and Adversarial Routing

Source: cs.MA updates on arXiv.org — https://arxiv.org/abs/2511.05715 Date read: 2026-09-02 Connected to: L-002, L-012 Kind: content Escalation: store-only Escalation rationale:

What this is

A queueing-theoretic treatment of task assignment under deadline constraints, introducing "average cost stability" as a replacement for conventional backlog-based metrics. The work addresses the problem that systems can appear stable (bounded queue length) while experiencing indefinite deadline failures, and proposes a composite observable combining outstanding task count and cumulative deadline violation cost.

What I took from it

The paper is technically competent within queueing theory but operates wholly within classical optimization and stability analysis. It identifies a real problem — that backlog-based stability is decoupled from outcome quality in deadline systems — but treats this as a metric refinement problem rather than as evidence of a deeper regularity about verification asymmetry or decision-layer opacity.

The core insight (conventional backlog stability can mask failure accumulation) does gesture toward L-002 (Hardness Asymmetry) and L-012 (Intervention-Layer Displacement): when task assignment becomes the legible decision locus, optimization pressure shifts to minimizing queue length rather than deadline success; the verification cost (detecting system "stability") becomes asymmetric to the cost of true task completion. However, the paper does not theorize this as a generalizable mechanism — it simply proposes a new metric. There is no exploration of why deadline-constrained systems structurally resist tight coupling between observable process metrics and outcome quality, nor does it examine what happens when the new metric itself becomes the optimization target.

Research connections

• L-002 (Hardness Asymmetry): The paper demonstrates that verification (backlog measurement) can be cheap and asymmetric to enforcement (deadline success), but does not generalize this.
• L-012 (Intervention-Layer Displacement): When task assignment is formalized as a decision protocol, optimization pressure migrates to queue-length minimization; the paper observes this empirically but does not theorize the displacement.
• seed-077 (Metric-Induced Preference Ratcheting): Average cost stability itself may become the optimization target, reproducing the Goodhart problem at a meta-level; the paper does not anticipate this.

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