Sweep: scale

Varies: scale factor f — terrain ×f, nodes ×f² (50 → 200 nodes).

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Provenance — measured at v1.3.0. Every number on this page was produced by the campaign runs named below, all of which predate the v1.3.0 tag (19009be). No commit between v1.2.0 and that tag changes routing behaviour, so checking out v1.3.0 reproduces these cells. The default branch will not: it has since changed the pheromone weighting (#327, betaAnts/ betaData 2.0 → 20) and the per-seed RNG stream assignment (#352), either of which moves measured values. See Provenance and #365.

What it varies

Reproduces Fig. 3 of the AntHocNet paper (Di Caro/Ducatelle/Gambardella, PPSN VIII 2004, §4): terrain is scaled by f and node count by f², holding node density roughly constant while the network grows. Unlike the paper (AODV only), every baseline is run on identical realisations.

Defined as SWEEPS["scale"] in ns3/tools/run-scenarios.py — the points are f = 1.0 (50 nodes, 1500×500 m), 1.4 (98, 2100×700), 1.8 (162, 2700×900) and 2.0 (200, 3000×1000).

How it is produced

Sweeps are too heavy for the per-merge benchmarks workflow, which runs only the discrete scenarios. They come from the manual Scenario matrix + charts workflow (scenario-matrix.yml), which renders sweep-scale.png into docs/benchmarks/ and uploads the classified CSV; the table below is filled in by pointing update-benchmarks.py at that CSV.

Raw sweep data rescued from expired artifacts lives in ../campaign/ and is summarizable with the benchmark-results skill's sweep_summary.py. This sweep is the one that had to be seed-split to run at all — see the provenance note below.

Results

Post-#88/#169, 20 seeds, 95% CIs. These numbers include the T_hop = 3 ms fix (#88, PR

167) and the reactive-hop-cap removal

(#169, PR #170), and meet the methodology runs floor. AntHocNet leads delivery at every point (+11.0 to +17.8 pp, intervals disjoint except at f = 2.0) while carrying 16–29 % lower normalized routing load. The delay99 column is worse throughout — the confirmed #21 tail, whose remediation is tracked in #308 against a like-for-like p99Common target. Do not quote path_div_*/entropy from these cells (#230).

Provenance — and why this sweep needed seed-splitting

Dispatched 2026-08-03/04 on main, scenario-matrix.yml, 3.42-opt image, 900 s, range/disk PHY, 20 seeds per point. The f = 1.0 point ran as a single 20-seed job; the other three exceed the 340-minute step ceiling at 20 seeds and were run as multiple dispatches over disjoint seed ranges using the runFirst input (#126, PR #322), then recombined with pool_runs.py, which recomputes each mean and standard deviation from the pooled per-run rows (#319) rather than combining split aggregates. Seed coverage was verified as exactly 1–20 per protocol per point, with no gaps and no duplicates.

point	nodes	dispatches	run IDs
f = 1.0	50	1 × 20 seeds	30854990473
f = 1.4	98	2 × 10 seeds	30876649282, 30876656386
f = 1.8	162	6 × 3 + 1 × 2 seeds	30898626094, 30898635717, 30898646523, 30898656990, 30898670257, 30898680790, 30898694649
f = 2.0	200	18 × 1 + 1 × 2 seeds	30898711742, 30898724984, 30898736284, 30898751349, 30898769563, 30898781607, 30898794804, 30898809114, 30898820499, 30898833922, 30898846247, 30898858035, 30898870503, 30898882109, 30898892224, 30898902277, 30898913177, 30898925485, 30876743751

The pooled inputs are committed as ../campaign/pooled-scale-{1.4,1.8,2.0}-20260804.csv (plus their per-run siblings); f = 1.0 predates #319 and has no sibling, so it is published from its aggregate CSV unchanged.

Measured simulation cost per seed, by field size (900 s sim, -opt image, queue-delayed jobs excluded so these are compute time, not wall-clock):

point	nodes	min/seed	growth exponent vs previous point
f = 1.0	50	5.0	—
f = 1.4	98	20.7	2.12
f = 1.8	162	98.2	3.09
f = 2.0	200	186.4	3.04

Cost grows faster than quadratically in node count, and the exponent itself rises with field size — which is why the first seed-split attempt (sized by extrapolating the 50 → 98-node curve) still lost its f = 1.8 and f = 2.0 chunks to the ceiling, and why the successful sizing came from measuring per-seed cost at each field size. The whole sweep is ≈ 116 CPU-hours. Anyone re-running it should size chunks from the table above rather than from a two-point extrapolation.

Sweep scale — mean of 20 run(s) per point, every baseline on identical realisations; ± is the 95% CI half-width (#293). Generated by run-scenarios.py; chart by make-charts.py.

scale factor	protocol	PDR % ±95	mean delay (ms) ±95	99th delay (ms) ±95	throughput (kbps)	NRL ±95	jitter (ms)	dOff90 (ms)
1.0	anthocnet	95.2 ± 0.3	54.9 ± 2.3	816.6 ± 25.7	6.25	38.963 ± 0.46	88.32	283.6
1.0	aodv	84.2 ± 0.6	29.8 ± 1.5	429.1 ± 25.5	5.55	52.419 ± 0.89	43.91	inf
1.0	dsdv	69.1 ± 1.1	14.3 ± 0.8	270.6 ± 82.1	4.59	27.127 ± 0.49	22.65	inf
1.0	olsr	74.8 ± 0.9	7.9 ± 0.4	26.5 ± 0.9	4.82	5.572 ± 0.09	10.68	inf
1.4	anthocnet	89.8100 ± 0.6	110.3200 ± 4.8	1205.3000 ± 42.5	5.9485	100.4570 ± 2.40	164.9015	inf
1.4	aodv	73.3150 ± 1.0	59.2650 ± 3.2	965.3000 ± 37.6	4.8160	141.1965 ± 3.47	84.7745	inf
1.4	dsdv	56.1500 ± 0.9	45.9450 ± 2.8	1033.7500 ± 3.9	3.7230	125.0810 ± 2.19	79.5920	inf
1.4	olsr	61.2550 ± 1.2	26.8300 ± 1.9	1011.2000 ± 1.3	4.0215	15.8410 ± 0.32	42.3560	inf
1.8	anthocnet	79.3600 ± 1.5	199.2450 ± 10.6	2001.2000 ± 58.3	5.2315	262.8115 ± 15.74	275.6305	inf
1.8	aodv	61.6100 ± 0.8	113.6750 ± 5.4	1434.7500 ± 89.1	4.0890	351.4885 ± 10.59	158.7285	inf
1.8	dsdv	46.4200 ± 1.3	111.3800 ± 3.2	2019.4500 ± 3.3	3.0610	405.1405 ± 10.59	188.1960	inf
1.8	olsr	51.1600 ± 1.3	62.9050 ± 4.7	1035.3500 ± 3.3	3.3620	36.8080 ± 0.96	102.3335	inf
2.0	anthocnet	66.7850 ± 3.2	263.9800 ± 18.9	2458.6500 ± 102.2	4.4380	496.3050 ± 66.88	346.9210	inf
2.0	aodv	53.0000 ± 1.3	153.5750 ± 9.4	1834.5500 ± 100.3	3.5090	591.2330 ± 29.58	205.7745	inf
2.0	dsdv	39.4200 ± 1.1	134.8800 ± 6.6	2138.9000 ± 74.2	2.6145	706.8070 ± 19.55	222.6235	inf
2.0	olsr	47.6050 ± 1.3	81.9950 ± 3.9	1133.2500 ± 99.5	3.1260	52.7170 ± 1.53	134.3915	inf