Merge pull request 'direct-fixes' (#6) from direct-fixes into develop
Reviewed-on: #6
This commit is contained in:
commit
ccff05c8d2
335
evaluation.ipynb
335
evaluation.ipynb
@ -91,15 +91,14 @@
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" (directionInbound[test.name()], directionOutbound[test.name()]) = env.test(test)\n",
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"\n",
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"def attempt_n_times(foo, n=3):\n",
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" i = 0\n",
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" while True:\n",
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" for i in range(n):\n",
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" try:\n",
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" return foo()\n",
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" except KeyboardInterrupt as e:\n",
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" raise e\n",
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" except Exception as e:\n",
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" if i == n:\n",
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" if i == n - 1:\n",
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" raise e\n",
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" finally:\n",
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" i += 1\n",
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"\n",
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"\n",
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"fast_tests = True"
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@ -114,7 +113,7 @@
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}
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},
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"source": [
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"### Direct Server to Server Testing"
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"### Direct Server to Server"
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]
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},
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{
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@ -132,7 +131,9 @@
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" run_and_save_test(env, DirectTest(1, variation_target=0.4 if fast_tests else 0.2))\n",
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" run_and_save_test(env, DirectTest(2, variation_target=0.4 if fast_tests else 0.2))\n",
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" run_and_save_test(env, DirectTest(3, variation_target=0.4 if fast_tests else 0.2))\n",
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" run_and_save_test(env, DirectTest(4, variation_target=0.4 if fast_tests else 0.2))"
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" run_and_save_test(env, DirectTest(4, variation_target=0.4 if fast_tests else 0.2))\n",
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"\n",
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"attempt_n_times(direct_tests)"
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]
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},
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{
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@ -228,7 +229,11 @@
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {
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"pycharm": {
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"name": "#%% md\n"
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}
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},
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"source": [
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"## Graphs\n",
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"This section produces graphs from the collected data."
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@ -391,6 +396,316 @@
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"### More than 2 connections evaluation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '4x1MB Connections (proxied)': StandardTest([1,1,1,1]),\n",
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" '3x1MB Connections (proxied)': StandardTest([1,1,1]),\n",
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" '2x1MB Connections (proxied)': StandardTest([1,1]),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '4x2MB Connections (proxied)': StandardTest([2,2,2,2]),\n",
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" '3x2MB Connections (proxied)': StandardTest([2,2,2]),\n",
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" '2x2MB Connections (proxied)': StandardTest([2,2]),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"### Mixed Performance Evaluation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '2x2MB Connections (proxied)': StandardTest([2,2]),\n",
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" '1x1MB + 1x2MB Connections (proxied)': StandardTest([1,2]),\n",
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" '2x1MB Connections (proxied)': StandardTest([1,1]),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"### Eventful Evaluation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" 'Varied Connection': StandardTest([2,2], events={10: (0,1), 15: (0,2)}, duration=30),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"### Comparisons to a Direct Connection"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '1x2MB Connection (not proxied)': DirectTest(2),\n",
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" '2x1MB Connections (proxied)': StandardTest([1,1]),\n",
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" '1x1MB Connection (not proxied)': DirectTest(1),\n",
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"\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '1x4MB Connection (not proxied)': DirectTest(4),\n",
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" '2x2MB Connections (proxied)': StandardTest([2,2]),\n",
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" '1x2MB Connection (not proxied)': DirectTest(2),\n",
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"\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '4x1MB Connections (proxied)': StandardTest([1,1,1,1]),\n",
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" '3x1MB Connections (proxied)': StandardTest([1,1,1]),\n",
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" '2x1MB Connections (proxied)': StandardTest([1,1]),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '4x2MB Connections (proxied)': StandardTest([2,2,2,2]),\n",
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" '3x2MB Connections (proxied)': StandardTest([2,2,2]),\n",
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" '2x2MB Connections (proxied)': StandardTest([2,2]),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"### Mixed Performance Evaluation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '2x2MB Connections (proxied)': StandardTest([2,2]),\n",
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" '1x1MB + 1x2MB Connections (proxied)': StandardTest([1,2]),\n",
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" '2x1MB Connections (proxied)': StandardTest([1,1]),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"### Eventful Evaluation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" 'Varied Connection': StandardTest([2,2], events={10: (0,1), 15: (0,2)}, duration=30),\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"### Comparisons to a Direct Connection"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '1x2MB Connection (not proxied)': DirectTest(2),\n",
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" '2x1MB Connections (proxied)': StandardTest([1,1]),\n",
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" '1x1MB Connection (not proxied)': DirectTest(1),\n",
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"\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"plot_iperf_results(\n",
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" {\n",
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" '1x4MB Connection (not proxied)': DirectTest(4),\n",
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" '2x2MB Connections (proxied)': StandardTest([2,2]),\n",
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" '1x2MB Connection (not proxied)': DirectTest(2),\n",
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"\n",
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" },\n",
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" filename='png',\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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@ -399,9 +714,7 @@
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"name": "#%% md\n"
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}
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},
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"source": [
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"### More than 2 connections evaluation"
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]
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"source": []
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},
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{
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"cell_type": "code",
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@ -167,11 +167,15 @@ class SpeedTestServer(Node):
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def server(self):
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self.ssh('iperf3 -s -1 -D', error_stdout=True, error_stderr=True)
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def client(self, target, time=30):
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def client(self, target, time=30, interval_size=2.0):
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if isinstance(target, SpeedTestServer):
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target = target.get_interfaces()[0].get_address()
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command = 'iperf3 -c {target} -t {time} -O 5 -J'.format(target=target, time=time)
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command = 'iperf3 -c {target} -t {time} -O 6 -i {interval_size} -J'.format(
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target=target,
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time=time,
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interval_size=interval_size,
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)
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return self.ssh(command, error_stdout=True, error_stderr=True, return_stdout=True)
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@ -231,6 +235,7 @@ class RemotePortal(Node):
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sudo ip route add table 10 to {local_host} via 172.19.152.3 dev nc0
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sudo ip rule add to {local_host} table 10 priority 10
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ping -W 0.1 -c 1 172.19.152.3
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ps $(cat mpbl3p.pid) || cat mpbl3p.log
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''').format(
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local_host=self.get_interfaces()[0].get_address(),
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@ -329,6 +334,7 @@ class LocalPortal(Node):
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sudo ip route add to {remote_host} dev {local_interface} table 19
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sudo ip rule add to {remote_host} table 19 priority 19
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ping -W 0.1 -c 1 172.19.152.2
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ps $(cat mpbl3p.pid) || cat mpbl3p.log
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''').format(
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**self.setup_params,
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@ -373,7 +379,7 @@ class DirectTest(StandardTest):
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class StandardIperfResult:
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def __init__(self, test: StandardTest, iperf: str, interval_size=1.0):
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def __init__(self, test: StandardTest, iperf: str, interval_size=2.0):
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self.test = test
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self.interval_size = interval_size
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@ -381,6 +387,7 @@ class StandardIperfResult:
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# list containing an exact time and a value
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self.data: List[Tuple[float, float]] = []
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self.num_tests = 0
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self.add_results(iperf)
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def add_results(self, iperf: str):
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@ -397,6 +404,8 @@ class StandardIperfResult:
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):
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self.data.append((time, result))
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self.num_tests += 1
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def bins(self) -> List[List[Tuple[float, float]]]:
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bins: List[List[Tuple[float, float]]] = [[] for _ in np.arange(0, self.test.duration, self.interval_size)]
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@ -432,12 +441,13 @@ class StandardIperfResult:
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def repeat_until_satisfied(reducer, satisfied, initial=None, max_attempts=100, max_failures=3):
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val = initial()
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i = 0
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val = initial
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for i in range(max_attempts):
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for j in range(max_failures):
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try:
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val = reducer(val)
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break
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except Exception as e:
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print('failed with {}'.format(e))
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if j == max_failures - 1:
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@ -485,8 +495,8 @@ class BaseEnvironment:
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for t, (iface, rate) in test.events.items():
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threading.Timer(
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5 + t,
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(lambda s: lambda: s.lp.get_interfaces()[iface].set_rate(rate))(self),
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6 + t,
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(lambda n: lambda: n.get_interfaces()[iface].set_rate(rate))(rated_node),
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)
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iperf = client.client(server, time=test.duration)
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@ -496,9 +506,14 @@ class BaseEnvironment:
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old.add_results(iperf)
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return old
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def test_satisfier(val: StandardIperfResult) -> bool:
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if val.num_tests < 3:
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return False
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return False not in [x < test.variation_target for x in val.coefficient_variance().values()]
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result = repeat_until_satisfied(
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test_reducer,
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lambda x: max(x.coefficient_variance().values()) < test.variation_target,
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test_satisfier,
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max_failures=test.max_failures,
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max_attempts=test.max_attempts,
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)
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