Problem
Research questions and friction points this paper is trying to address.
Semantic Decision Engines
Network Control Loops
Deadline Attainment
Deterministic Computation
Coverage Verification
SoK: Semantic Decision Engines in Network Control Loops
🤖 AI Summary
This study addresses the vulnerability of semantic decision engines in network control loops, where the absence of deterministic computational steps precipitates deadline violations and inadmissible actions, further exacerbated by performance bottlenecks arising from concurrent queuing. By systematically reviewing 139 studies, this work integrates bibliometric analysis, event-model boundary testing, and coverage verification mechanisms to quantitatively evaluate decision interfaces and execution paths, revealing significant discrepancies between claimed capabilities and empirical measurements. The findings demonstrate that compliance under single-request conditions does not guarantee reliability in queuing scenarios, identifying non-deterministic steps as the primary source of risk. Accordingly, this paper establishes minimum reporting standards, formulates design principles, and outlines a future research agenda to enhance the dependability of semantic decision engines in time-critical networked environments.
📝 Abstract
A semantic decision engine such as Jev can return a valid answer and still miss a network deadline, select an infeasible action or leave the service unverified. We systematize 139 paper families by decision interface, execution path and check ownership. Fifty families claim that their engine fits a control loop or time budget, but only four support the claim with matched measurement. Across all 139, four report deadline attainment. The gap concentrates where the decision has no deterministic computation step. Those 72 families make 22 of the claims, none supported, and name a coverage owner in only two. Bounded tests under one event model show that each gap can reverse an admission verdict. A decision that meets a 10 s budget for every isolated request meets it for none once decisions queue ahead of replayed execution times. The same engine passes one coverage check and fails another. We derive a minimum reporting record, design rules and a research agenda for admitting decision engines to control loops.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Semantic Decision Engines
Network Control Loops
Systematization of Knowledge
Deadline Attainment
Coverage Verification
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