🤖 AI Summary
This work addresses the challenge in hierarchical caching networks where conventional request-time-based eviction policies fail to assess the impact of removing aligned storage blocks on the connectivity of downstream critical services, often causing service disruptions. The authors model aligned eviction as a weighted vertex separation problem on a graph, precisely computing the downstream demand cut of candidate blocks to reject evictions that compromise protected paths and selecting the feasible eviction with minimal impact. They introduce a novel verifiable service-cut certificate mechanism that, for the first time, unifies capacity reclamation, path continuity, and distributed failure within a certifiable interface, and prove that strategies relying solely on historical information can incur unbounded single-step damage. Experiments across 144 scenarios processing 582.9 trillion packets (404.86 PiB) validate theoretical predictions, reveal a zero-impact extremal phase transition point, and enable full impact vectors and audit samples within supplementary material budgets.
📝 Abstract
In a tiered cache, eviction is a graph decision: removing one aligned storage block can disconnect downstream demand that never addressed that block directly, so request recency alone cannot price the action. This paper studies aligned eviction as a vertex-separation problem and gives a selection rule whose decisions carry independently checkable service-cut evidence. For every candidate block, it computes the exact weighted downstream demand cut, rejects actions that disconnect protected demand, and selects the minimum-impact admissible eviction. Reclamation is characterized as vertex separation: minimum-location reclamation reduces to node-capacitated flow, while minimum aligned block actions are NP-complete. In two-hop cache networks, one streaming pass evaluates every candidate impact; a matching adversarial construction proves that a history-only victim selector has unbounded one-step damage. The packet-scale implementation combines a seed-indexed exact-cardinality residency structure with collision-aware, 32-bank impact counters. Replay compression makes the result auditable: counter intervals reproduce the stream, exact monoid summaries retain every reported additive statistic, and a counting lower bound quantifies the state required by any exact all-candidate summary. A 144-scenario evaluation processes 582.90 trillion packets (404.86 PiB of simulated payload), validates the coordinate expectations, and exposes a zero-impact extreme-value transition near $Nζ=\log m$. Complete impact vectors, decoded audit samples, telemetry, and logs remain within the ancillary-file budget. Finally, invalidation is monotone replicated state: fair asynchronous delivery converges without coordination, with a diameter bound under synchronous full-edge rounds. The architecture therefore binds capacity reclamation, path continuity, and distributed invalidation to one certifying interface.