Three research directions · one control loop

From fast decisions
to working networks.

A decision has to be correct, arrive in time, and produce the intended result. Explore where faster interpretation helps wireless control and edge services—and what it takes to verify the loop.

Explore the evidence
Start with a question
01 / Wireless networks

Wireless network control

What reaches the radio, and what changes for users? Read the service outcome alongside policy quality, control deadlines and queues.

Ideal policy effect3.96 pp

Affected-class SLA headroom relative to no update.

95% interval 2.17–7.02 pp · base point
Controlled delay effect3.93 pp

Higher violation with 5 s instead of 0.1 s enforcement.

95% interval 1.22–6.37 pp · true policy held fixed
Read both endpoints

Faster interpretation reduces the time spent waiting for a policy. The base-point affected-class SLA comparisons do not establish a hosted-model ranking under both block lengths.

Does a faster decision improve the radio outcome?

Latency-only ns-3 closed loop · event-driven mode · 2 s SLA window

Simulated radio outcomes

All models are shown together. Select a measured rate and UE speed.

Scenario map · select a cell

Find the operating conditions that change the outcome.

Select a cell to inspect all four KPIs. Arrow keys move between cells; on small screens, swipe the map horizontally.

All models and confidence intervals for the selected condition
More radio KPIs for this condition

Link failures are counts per run; run durations differ across arrival rates. These radio KPI point estimates are descriptive.

Measurement definitions and source

Radio outcomes: RQ1–2, latency-only ns-3 runs. Base-point SLA intervals use 48.8 s blocks, with 10 s sensitivity checks; grid points are descriptive. Policy quality: RQ4, 57-cell telemetry. Deadline curve: supplied empirical aggregates at 61 budgets; all seven 1 s values match the manuscript, without a fresh raw-call reanalysis. Load: RQ3, live arrivals and modeled enforcement. Control path: RQ6, real-stack component medians and separately observed KPM bounds.

Supporting study ↗
02 / Distributed services

Edge service orchestration

How many requests finish correctly before their deadline? Keep completion and latency together, then inspect what limits a real service.

Measured sweep

A / B comparison

Keep one condition. Change the other.

A stays pinned while the controls above update B.

A
B

○ A · ● B · horizontal position is correct, on-time completion (0–100%). Differences are descriptive.

Request p95 belongs to each condition's own completions. A lower p95 with fewer completions does not establish a latency advantage.

Inspect current B: completion counts and request p95

Read the two outcomes together. Request p95 is conditional on each model's own completions. A low p95 with few completions does not establish a latency advantage. The count column reports the selected correct-completion criterion.

Completion, latency and denominators

Part A uses live admission and modeled execution. Completion requires the full intent to be exactly correct and the supported service to finish on time (300 supported requests per cell). Part B uses real OCR: correct completion additionally requires the recognized text to match (180 supported OCR requests per cell). Its 60 unsupported requests and correct rejections are counted separately. Counts are recovered from manuscript-rounded rates using these fixed denominators and checked by rounding back. Request p95 is computed on each model's own completions; “—” means no completed requests. Supporting study: RQ5.

Supporting study ↗
03 / Network control methodology

Closed-loop verification

Where does the clock stop? What happens when work queues? Who checks an infeasible action? Measured cases show why these choices change the verdict.

Measured decision delay
Fixed-action intervention
Follow the evidence · four checkpoints

Move the clock's endpoint and see what changes.

The guide reads reported aggregates; it does not animate an individual execution trace. Checkpoints 1–3 describe the isolated arm. Checkpoint 4 changes the test context to the selected queue and replay arm.

01 · Measurement endpoint

Follow the result beyond the ACK.

Isolated physical executions · same action, controlled decision delay

p50 and p95 include the decision and downstream work. Decision shares are the reported mean shares across scenes.

02 · Workload

Include the queue in the deadline.

Real single-slot FIFO queue + measured execution-time replay. Rates stay fixed across delay arms. Intervals describe the finite measurement window, including overloaded queues.

03 · Check responsibility

A check must be tested in the task where it is used.

Jev-1.13 · constructed application-control tasks · different checks retain their own denominators

Missing contract candidate

Requests a new candidate when the catalogue has no valid option.

Infeasible forwarding instance

Escalates when the forwarding instance is infeasible.

The workflow intervention changes instructions, refresh actions and check ownership together. Full rule: 120/120 in both arms for these quota conditions.

What to report for a deployable loop

Named endpoints · correctness and failure counts · deadline attainment · arrivals and concurrency · queueing · check ownership · verified outcome

Explore the literature evidence 139 families · reporting coverage, execution paths and check ownership4 / 50 claims supported

What does the literature actually measure?

Of 50 families claiming a control-loop or timing fit, four provide matched measurement. Across all 139 families, nine report p95 or higher and four report deadline attainment.

Read the coding uncertainty. Load, queueing, stability, network round-trip inclusion and final-state checks have lower pre-adjudication coding agreement. The family bootstrap intervals below do not capture that coding uncertainty. Categories overlap and all 139 families remain in the denominator.

Decision interface · families may use several

S = selection · G = generation · C = deterministic computation · U = unspecified. “Unresolved” means the map does not establish check ownership. Check descriptions support inspection, not a reliable prevalence estimate or a deployment ranking.

Verification experiments and literature sources

Fixed-action endpoint measurements use 30 scenes × 10 repeats per delay and domain. Load tests use the same decision queue with execution residuals sampled from measured physical runs; the post-queue physical actions do not run concurrently. Transport and edge retain their own exploratory 10 s and 2 s budgets. Correctness checks are separate constructed tasks. Reporting coverage and the 139-family map come from the current SoK tables and supplement. Supporting study: diagnostic lenses L1–L3 and reporting coverage.

Supporting study ↗
Research sources

Supporting studies and data

Each direction links to the study that supplies its measurements, methods and evidence.

Wireless network control

Intent Interpretation at RIC Timescales: Jev Decision Models versus Large Language Models in 6G Open RAN

Delong Li, Xu Wang, Haochen Gong, Rui Lang, Guangsheng Yu

Edge service orchestration

Replacing Large Language Models with Jev Decision Models for Low-Latency Edge Service Orchestration

Delong Li, Xu Wang, Haochen Gong, Rui Lang, Guangsheng Yu

Closed-loop verification

SoK: Semantic Decision Engines in Network Control Loops

Delong Li, Chen Li, Xu Wang, Haochen Gong, Rui Lang, Guangsheng Yu

Explore recorded experimental conditions. API fees refer to those measurements. Comparable energy per decision is unavailable across hosted and self-hosted deployments.

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