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better routing solution

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kdee committed 2026-07-12 22:50:14 -07:00
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commit 37598479cc
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test/test_miSim.m
+198 -2
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@@ -105,6 +105,13 @@ classdef test_miSim < matlab.unittest.TestCase
methods (Test)
% Test methods
function miSim_initialization(tc)
% Test flag: set true to exercise the min-max-workload LP routing
% overlay on this random scenario. Routing requires SINR comms, so
% the flag switches the whole SINR stack on (agents keep their
% default 0.1 W txPower); the permissive -30 dB threshold keeps
% random geometries fully connected.
useRoutingTopology = true;
% randomly create obstacles
nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
tc.obstacles = cell(nGeom, 1);
@@ -240,7 +247,11 @@ classdef test_miSim < matlab.unittest.TestCase
end
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
if useRoutingTopology
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing, true, -30.0, 2.0, 290, 2.4e9, 20e6, true, 0.02);
else
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
end
end
function miSim_run_rf_sensor(tc)
% randomly create obstacles
@@ -391,6 +402,13 @@ classdef test_miSim < matlab.unittest.TestCase
tc.testClass = tc.testClass.run();
end
function miSim_run(tc)
% Test flag: set true to exercise the min-max-workload LP routing
% overlay on this random scenario. Routing requires SINR comms, so
% the flag switches the whole SINR stack on (agents keep their
% default 0.1 W txPower); the permissive -30 dB threshold keeps
% random geometries fully connected.
useRoutingTopology = true;
% randomly create obstacles
nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
tc.obstacles = cell(nGeom, 1);
@@ -527,7 +545,11 @@ classdef test_miSim < matlab.unittest.TestCase
end
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
if useRoutingTopology
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing, true, -30.0, 2.0, 290, 2.4e9, 20e6, true, 0.02);
else
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
end
% Write out initialization state
tc.testClass.writeInits();
@@ -959,6 +981,180 @@ classdef test_miSim < matlab.unittest.TestCase
% Run the simulation
tc.testClass = tc.testClass.run();
end
function test_routing_topology_3_agents(tc)
% Three near-collinear agents with the routing-LP topology
% selector. Endpoints are agents 1 and 3 (largest odd index);
% agent 2 is the only relay, so only its unit of data transits
% the network. Agent 2 sits slightly closer to agent 1, giving
% the 2->1 link strictly higher capacity than 2->3. The min-max
% optimum is then unique: node 2's transmit workload
% f21/c21 + f23/c23 is always the system max (endpoint receive
% time is a subset of it), so ALL flow goes over the better
% link. No split occurs because the receive side never binds
% with a single relay.
tc.minDimension = 10; % domain size
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([2, 8; 8, 8]), tc.domain, tc.discretizationStep, tc.protectedRange);
% Initialize agent collision geometry. Asymmetric spacing: agent 2
% is 1.8 m from agent 1 and 2.2 m from agent 3 (both above the 1 m
% path-loss floor). The 1-3 link (4 m, with agent 2 interfering
% close-in) stays below the threshold in both directions.
tc.agents = {agent; agent; agent;};
tc.collisionRanges = .25 * ones(size(tc.agents));
dLeft = [1.8, 0, 0];
dRight = [2.2, 0, 0];
geometry1 = spherical;
geometry2 = geometry1;
geometry3 = geometry1;
geometry1 = geometry1.initialize(tc.domain.center - dLeft, tc.collisionRanges(1), REGION_TYPE.COLLISION);
geometry2 = geometry2.initialize(tc.domain.center, tc.collisionRanges(2), REGION_TYPE.COLLISION);
geometry3 = geometry3.initialize(tc.domain.center + dRight, tc.collisionRanges(3), REGION_TYPE.COLLISION);
% Initialize agent sensor model
tc.sensor = sigmoidSensor;
tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 15, 3);
% Initialize obstacles
tc.obstacles = {};
% Initialize agents
tc.maxIter = 50;
tc.commsRanges = 4 * ones(size(tc.agents)); % unused in SINR mode
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - dLeft, geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + dRight, geometry3, tc.sensor, tc.commsRanges(3), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
% SINR communications model parameters (same threshold logic as
% the lesser-neighbor 3-agent test: a couple dB above the
% rejected end-to-end link, below the chain-link binding)
useSinrComms = true;
txPower = [0.1, 0.1, 0.1]; % homogeneous transmit power (W)
pathLossExponent = 2.0;
ambientTemp = 290; % K
centerFreq = 2.4e9; % Hz
bandwidth = 20e6; % Hz
endBindingDb = 10 * log10(0.5^pathLossExponent); % ~ -6.02 dB
sinrThreshold = endBindingDb + 2.0; % ~ -4.02 dB
useRoutingTopology = true;
routingFlowThreshold = 0.02;
tc.agents{1}.txPower = txPower(1);
tc.agents{2}.txPower = txPower(2);
tc.agents{3}.txPower = txPower(3);
% Initialize the simulation with the routing-LP topology selector
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing, useSinrComms, sinrThreshold, pathLossExponent, ambientTemp, centerFreq, bandwidth, useRoutingTopology, routingFlowThreshold);
% Feasible (threshold) links form the 1-2-3 line; the routing LP
% then puts all of relay 2's data on the higher-capacity 2->1
% link and drops 2->3 entirely
tc.assertEqual(tc.testClass.routingAdjacencyMatrix, logical( ...
[ 0, 0, 0; ...
1, 0, 0; ...
0, 0, 0;]));
tc.assertEqual(tc.testClass.routingFlows(2, 1), 1.0, "AbsTol", 1e-6);
% Endpoints never transmit; total flow equals the relay's unit
tc.assertEqual(sum(tc.testClass.routingFlows, "all"), 1.0, "AbsTol", 1e-6);
% The CBF maintains the low-level (lesser-neighbor) connectivity
% line PLUS the routed bulk link (2->1, already part of the line):
% the network must stay connected for basic traffic even though
% bulk data only flows over 2->1
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
[ 1, 1, 0; ...
1, 1, 1; ...
0, 1, 1;]));
% Run the simulation
tc.testClass = tc.testClass.run();
end
function test_routing_topology_4_agents(tc)
% Four collinear agents, 2 m spacing. Endpoints are agents 1 and
% 3; relays are agents 2 and 4. Threshold-feasible links form the
% chain 1-2-3-4 (longer links are interference-limited below the
% threshold). Relay 4's only outlet is endpoint 3; relay 2 can
% reach both endpoints but 2->1 has strictly higher capacity than
% 2->3 (endpoint 3 is also loaded by relay 4's traffic), so the
% unique optimum is 2->1 and 4->3.
tc.minDimension = 10; % domain size
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([2, 8; 8, 8]), tc.domain, tc.discretizationStep, tc.protectedRange);
% Initialize agent collision geometry: collinear at x = 2, 4, 6, 8
tc.agents = {agent; agent; agent; agent;};
tc.collisionRanges = .25 * ones(size(tc.agents));
d = [2.0, 0, 0];
positions = [tc.domain.center - 1.5 * d; ...
tc.domain.center - 0.5 * d; ...
tc.domain.center + 0.5 * d; ...
tc.domain.center + 1.5 * d;];
% Initialize agent sensor model
tc.sensor = sigmoidSensor;
tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 15, 3);
% Initialize obstacles
tc.obstacles = {};
% Initialize agents
tc.maxIter = 50;
tc.commsRanges = 4 * ones(size(tc.agents)); % unused in SINR mode
for aa = 1:4
geometry = spherical;
geometry = geometry.initialize(positions(aa, :), tc.collisionRanges(aa), REGION_TYPE.COLLISION);
tc.agents{aa} = tc.agents{aa}.initialize(positions(aa, :), geometry, tc.sensor, tc.commsRanges(aa), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
tc.agents{aa}.txPower = 0.1;
end
% SINR communications model parameters
useSinrComms = true;
pathLossExponent = 2.0;
ambientTemp = 290; % K
centerFreq = 2.4e9; % Hz
bandwidth = 20e6; % Hz
endBindingDb = 10 * log10(0.5^pathLossExponent); % ~ -6.02 dB
sinrThreshold = endBindingDb + 2.0; % ~ -4.02 dB
useRoutingTopology = true;
routingFlowThreshold = 0.02;
% Initialize the simulation with the routing-LP topology selector
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing, useSinrComms, sinrThreshold, pathLossExponent, ambientTemp, centerFreq, bandwidth, useRoutingTopology, routingFlowThreshold);
% Unique optimum: 2->1 and 4->3
expectedDirected = false(4);
expectedDirected(2, 1) = true;
expectedDirected(4, 3) = true;
tc.assertEqual(tc.testClass.routingAdjacencyMatrix, expectedDirected);
% The CBF maintains the full lesser-neighbor chain (low-level
% connectivity) with the bulk links overlaid on it
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
[ 1, 1, 0, 0; ...
1, 1, 1, 0; ...
0, 1, 1, 1; ...
0, 0, 1, 1;]));
% Flow conservation at every relay: out - in = 1 unit produced
F = tc.testClass.routingFlows;
endpoints = [1, 3];
for aa = 1:4
if any(aa == endpoints)
continue;
end
tc.assertEqual(sum(F(aa, :)) - sum(F(:, aa)), 1.0, "AbsTol", 1e-6);
end
% Every surviving link carries at least the pruning threshold,
% and total delivered data equals the number of relays
tc.assertTrue(all(F(F > 0) >= tc.testClass.routingFlowThreshold));
tc.assertEqual(sum(F(:, endpoints), "all") - sum(F(endpoints, :), "all"), 2.0, "AbsTol", 1e-6);
end
function test_communications_constraint_fixed_radius(tc)
% No obstacles
% Fixed two agents initial conditions