Ce diaporama a bien été signalé.
Nous utilisons votre profil LinkedIn et vos données d’activité pour vous proposer des publicités personnalisées et pertinentes. Vous pouvez changer vos préférences de publicités à tout moment.

Large-scale Experimentation with Network Abstraction for Network Configuration Management

268 vues

Publié le

Large-scale Experimentation with Network Abstraction for Network Configuration Management

Publié dans : Internet
  • Soyez le premier à commenter

  • Soyez le premier à aimer ceci

Large-scale Experimentation with Network Abstraction for Network Configuration Management

  1. 1. Large scale RINA Experimentation on FIRE + Large-scale Experimentation with Network Abstraction for Network Configuration Management Dr. Sven van der Meer, NM-Lab, Ericsson
  2. 2. ntroduction opic: Management of multi-layer converged service provider networks bjectives, demonstrate that RINA leads to simplification of management definitions, implementations Coordinated management can evolve –  Complex workflows to a strategy-oriented management task Single manager can simultaneously perform –  Adequate number of strategies Manager can be scaled out/up and scaled in/down –  In case a single manager is insufficient Large-scale RINA Experimentation on FIRE+
  3. 3. xperiment Design 1 experiment –  Create network, create and validate nodes, validate network, generate configuration script, generate network report Run for 24 networks –  From tiny (rumba-2-nodes) to extra large (metro2110) Run on 6 machines on 3 hardware platforms –  Raspberry PI, Windows/Cygwin, different UNIX machines including large server Using 1 management strategy –  Consisting of 2 core policies: network and node management –  Some secondary policies: context policy parameters, and templates –  Using identical software installation and network scenarios Large-scale RINA Experimentation on FIRE+
  4. 4. ACHIEVEMENT AND EXPLORED ABSTRACTIONS Large-scale RINA Experimentation on FIRE+
  5. 5. Main Statement his experiment provides substantial experimental evidence that Consequent application of RINA abstractions Leads to significant improvements In configuration management Especially for –  performance, –  management software complexity –  automation Large-scale RINA Experimentation on FIRE+
  6. 6. Explored Abstractions Large-scale RINA Experimentation on FIRE+ NA Separate mechanism from policy Mechanism/Policy are relative 1 application protocol (CDAP) Management is monitoring and repair (PtP) DIF and DAF ARCFIRE Initial •  Management requires initial configuration •  Management is relative (term and activities) •  Network: set of nodes, DIFs, IPCPs in DIFs ARCFIRE Execution •  Nodes can be isolate (for create / validate •  Network configuratio requires only node specifications •  4 graphs seem to be important to show a network
  7. 7. DMS Large-scale RINA Experimentation on FIRE+
  8. 8. DMS – Components APEX – (adaptive) policy engine –  https://ericsson.github.io/apex-docs/ and in ONAP –  With D-MIM – distributed object (shared memory) management Apex Policy Builder (APB) – develop and test strategy, create artifacts –  Plus set of clients DMS – deploy and run strategy Management Strategy –  Set of policies specified in form of a policy model –  Core: policy to handle networks, policy to handle nodes –  Secondary: policies handling context information, policy parameters, templates –  Binaries: scripts to create artifacts, measurement client Large-scale RINA Experimentation on FIRE+
  9. 9. ARCFIRE DMS Large-scale RINA Experimentation on FIRE+
  10. 10. NETWORKS AND MACHINES Large-scale RINA Experimentation on FIRE+
  11. 11. ModelledNetworks(24)
  12. 12. Large-scale RINA Experimentation on FIRE+ HardwarePlatforms(3) &Machines(6)
  13. 13. Large-scale RINA Experimentation on FIRE+
  14. 14. KPI AND MAIN RESULTS Large-scale RINA Experimentation on FIRE+
  15. 15. DMS – KPIs Speed – of the management strategy Scale – requirements to scale out the DMS Time and cost of scaling Touches – required human interference Strategy complexity –  Runtime: number of operations –  Code: counted lines of code Degree of automation –  0: not automated at all –  100: fully automated Large-scale RINA Experimentation on FIRE+
  16. 16. KPISummary
  17. 17. KPI: Speed Large-scale RINA Experimentation on FIRE+
  18. 18. KPI: Scale and Complexity Large-scale RINA Experimentation on FIRE+
  19. 19. KPI: Automation and Touch Large-scale RINA Experimentation on FIRE+
  20. 20. AGGREGATED RESULTS Large-scale RINA Experimentation on FIRE+
  21. 21. Large-scale RINA Experimentation on FIRE+ Network #runs wait duration ov-adj overall policy APEX logic crt-net Σ crt-node Σ val-node val-net get-rumba get-report Nodes DIFs P-DIFs Trigg rumba-2-nodes 300 0:07:30 1:02:58 0:44:34 0:47:44 0:02:28 0:01:26 0:01:02 0:00:07 0:00:17 0:00:16 0:00:08 0:00:08 0:00:05 600 300 300 2,4 rumba-2-layers 300 0:07:30 1:05:40 0:45:47 0:50:17 0:04:09 0:02:19 0:01:50 0:00:07 0:00:39 0:00:39 0:00:09 0:00:10 0:00:06 1,200 1,200 900 3,6 rumba-mouse 300 0:04:10 1:11:27 0:52:51 0:56:11 0:09:42 0:05:01 0:04:41 0:00:07 0:01:59 0:02:00 0:00:12 0:00:16 0:00:06 4,200 300 5,100 9,6 rumba-cnop 300 0:09:10 1:23:36 1:02:04 1:08:34 0:15:24 0:07:36 0:07:48 0:00:08 0:03:23 0:03:23 0:00:19 0:00:28 0:00:07 8,400 2,100 10,200 18,0 rina-standard 300 0:07:30 1:06:21 0:46:22 0:51:12 0:04:19 0:02:22 0:01:57 0:00:07 0:00:43 0:00:45 0:00:08 0:00:09 0:00:05 1,500 600 1,200 4,2 renum-geant 300 0:17:30 1:45:51 1:18:37 1:30:37 0:25:22 0:11:22 0:13:59 0:00:11 0:06:04 0:05:47 0:00:39 0:01:10 0:00:08 12,000 300 18,600 25,2 renum-atnt 300 0:31:40 2:41:21 2:10:34 2:25:24 0:58:55 0:22:43 0:36:12 0:00:12 0:15:04 0:15:51 0:01:34 0:03:20 0:00:11 30,300 300 35,100 61,8 d22-copper 300 0:07:30 1:01:55 0:46:24 0:50:34 0:04:19 0:02:24 0:01:55 0:00:07 0:00:43 0:00:42 0:00:09 0:00:09 0:00:06 1,500 1,200 1,200 4,2 d22-coredifs2 300 0:07:30 1:08:21 0:47:32 0:53:12 0:05:24 0:02:58 0:02:26 0:00:07 0:00:57 0:00:57 0:00:09 0:00:11 0:00:05 2,100 900 4,800 5,4 d22-dc 300 0:09:10 1:10:51 0:50:21 0:55:41 0:06:18 0:03:22 0:02:56 0:00:07 0:01:13 0:01:12 0:00:09 0:00:11 0:00:05 2,700 600 2,400 6,6 d22-interxdifs 300 0:07:30 1:05:19 0:46:18 0:50:08 0:04:36 0:02:33 0:02:03 0:00:07 0:00:44 0:00:49 0:00:09 0:00:10 0:00:05 1,500 900 1,200 4,2 d22-lte 300 0:07:30 1:06:18 0:45:42 0:50:42 0:03:50 0:02:11 0:01:39 0:00:07 0:00:35 0:00:34 0:00:09 0:00:09 0:00:05 1,200 1,200 900 3,6 d22-metro 300 0:07:30 1:06:00 0:46:24 0:50:04 0:04:27 0:02:28 0:01:59 0:00:07 0:00:44 0:00:45 0:00:08 0:00:09 0:00:05 1,500 900 1,200 4,2 d22-pbb 300 0:07:30 1:10:39 0:50:30 0:55:30 0:08:03 0:04:18 0:03:46 0:00:07 0:01:39 0:01:31 0:00:10 0:00:13 0:00:06 3,600 1,200 3,300 8,4 d22-servicedifs 300 0:07:30 1:07:02 0:46:58 0:51:48 0:05:13 0:02:47 0:02:26 0:00:07 0:00:56 0:00:58 0:00:10 0:00:11 0:00:05 1,800 1,800 1,800 4,8 d22-together1 300 0:07:30 1:10:19 0:49:56 0:54:46 0:07:45 0:04:04 0:03:41 0:00:07 0:01:32 0:01:31 0:00:10 0:00:14 0:00:07 3,300 2,100 3,300 7,8 d22-together3 300 0:07:30 1:10:56 0:50:00 0:56:00 0:08:03 0:04:11 0:03:52 0:00:07 0:01:36 0:01:35 0:00:11 0:00:15 0:00:07 3,300 2,100 3,300 7,8 d22-wifi 300 0:07:30 1:05:26 0:46:21 0:50:11 0:04:30 0:02:31 0:01:58 0:00:07 0:00:43 0:00:45 0:00:08 0:00:10 0:00:05 1,500 1,200 1,500 4,2 d22-wifi2 300 0:07:30 1:04:22 0:45:52 0:48:52 0:03:58 0:02:16 0:01:42 0:00:07 0:00:34 0:00:37 0:00:10 0:00:09 0:00:05 1,200 1,200 900 3,6 apex-pcvs1 300 0:04:10 1:10:08 0:49:18 0:54:48 0:07:08 0:03:54 0:03:15 0:00:07 0:01:22 0:01:20 0:00:09 0:00:11 0:00:06 3,000 900 3,000 7,2 metro0248 250 1:56:40 2:53:24 2:29:08 2:33:58 2:51:32 0:43:42 2:07:49 0:00:13 0:43:23 1:04:47 0:06:04 0:13:09 0:00:13 62,000 2,500 66,000 125,0 metro0500 250 3:04:10 4:22:15 4:00:16 4:09:56 7:38:04 1:12:36 6:25:28 0:00:16 2:09:32 3:14:00 0:21:14 0:39:31 0:00:56 125,000 3,000 131,250 251,0 metro1000 250 9:48:20 11:47:46 10:02:48 10:21:18 23:30:45 2:11:53 21:18:53 0:00:16 6:28:02 11:51:00 0:57:30 2:01:07 0:00:59 250,000 3,000 256,250 501,0 metro2110 200 8:53:20 11:43:50 10:52:57 11:05:27 24:20:13 1:11:45 23:08:29 0:00:09 7:03:51 15:21:50 0:19:02 0:23:19 0:00:17 422,000 2,400 427,000 844,8 Σ 20 6,000 3:00:50 24:54:49 18:02:24 19:52:14 3:13:54 1:32:45 1:41:09 0:02:31 0:41:26 0:41:57 0:05:11 0:08:03 0:02:01 86,400 21,300 100,200 196,8 Σ 6,950 26:43:20 55:42:05 45:27:33 48:02:53 61:34:28 6:52:41 54:41:47 0:03:24 17:06:14 32:13:34 1:49:01 3:25:08 0:04:27 945,400 32,200 980,700 1,918,6 Network #runs wait, s duration, s ov-adj, s overall, s policy, ms APEX, ms logic, ms crt-net, ms Σ crt-node, ms Σ val-node, ms val-net ms, ms get-rumba, ms get-report, ms Nodes DIFs P-DIFs Trig rumba-2-nodes 300 450 3,778 2,674 2,864 147,796 85,785 62,011.00 7,286.00 16,714.00 16,302 8,249 8,283 5,177 2 1 1 rumba-2-layers 300 450 3,940 2,747 3,017 249,091 139,030 110,061.00 7,135.00 39,311.00 38,925 8,965 10,116 5,609 4 4 3 rumba-mouse 300 250 4,287 3,171 3,371 581,956 301,192 280,764.00 7,358.00 119,023.00 119,764 11,956 16,484 6,179 14 1 17 rumba-cnop 300 550 5,016 3,724 4,114 923,957 455,582 468,375.00 7,881.00 203,070.00 202,860 18,743 28,399 7,422 28 7 34 rina-standard 300 450 3,981 2,782 3,072 258,742 142,168 116,574.00 6,765.00 42,560.00 44,919 8,212 9,066 5,052 5 2 4 renum-geant 300 1,050 6,351 4,717 5,437 1,521,501 682,032 839,469.00 10,542.00 364,498.00 347,270 39,190 69,648 8,321 40 1 62 renum-atnt 300 1,900 9,681 7,834 8,724 3,535,363 1,362,888 2,172,475.00 12,013.00 903,681.00 951,424 94,363 200,445 10,549 101 1 117 d22-copper 300 450 3,715 2,784 3,034 259,056 144,014 115,042.00 7,263.00 42,821.00 41,879 8,692 8,836 5,551 5 4 4 d22-coredifs2 300 450 4,101 2,852 3,192 323,819 177,688 146,131.00 6,861.00 57,132.00 56,912 9,379 10,516 5,331 7 3 16 d22-dc 300 550 4,251 3,021 3,341 378,416 202,426 175,990.00 6,598.00 73,074.00 71,556 8,931 10,824 5,007 9 2 8 d22-interxdifs 300 450 3,919 2,778 3,008 276,100 152,784 123,316.00 7,195.00 43,512.00 48,520 9,044 9,558 5,487 5 3 4 d22-lte 300 450 3,978 2,742 3,042 230,090 131,067 99,023.00 7,182.00 34,580.00 34,394 8,773 9,135 4,959 4 4 3 d22-metro 300 450 3,960 2,784 3,004 266,891 147,874 119,017.00 6,921.00 43,713.00 45,373 8,219 9,384 5,407 5 3 4 d22-pbb 300 450 4,239 3,030 3,330 483,436 257,704 225,732.00 7,001.00 99,278.00 90,800 9,834 12,694 6,125 12 4 11 d22-servicedifs 300 450 4,022 2,818 3,108 312,673 166,566 146,107.00 7,021.00 55,520.00 57,978 9,580 10,710 5,298 6 6 6 d22-together1 300 450 4,219 2,996 3,286 465,258 243,978 221,280.00 7,027.00 91,998.00 91,400 10,248 13,719 6,888 11 7 11 d22-together3 300 450 4,256 3,000 3,360 483,159 251,149 232,010.00 7,393.00 96,275.00 95,191 11,287 14,691 7,173 11 7 11 d22-wifi 300 450 3,926 2,781 3,011 269,821 151,468 118,353.00 7,155.00 42,991.00 44,967 8,498 9,685 5,057 5 4 5 d22-wifi2 300 450 3,862 2,752 2,932 238,344 136,028 102,316.00 7,164.00 34,413.00 36,786 9,972 8,958 5,023 4 4 3 apex-pcvs1 300 250 4,208 2,958 3,288 428,116 233,517 194,599.00 6,848.00 81,923.00 79,715 9,104 11,463 5,546 10 3 10 metro0248 250 7,000 10,404 8,948 9,238 10,291,666 2,622,302 7,669,364.00 12,632.00 2,602,563.00 3,887,245 364,054 789,380 13,490 248 10 264 metro0500 250 11,050 15,735 14,416 14,996 27,483,990 4,356,038 23,127,952.00 15,833.00 7,772,120.00 11,639,551 1,273,910 2,371,017 55,521 500 12 525 1 metro1000 250 35,300 42,466 36,168 37,278 84,645,373 7,912,864 76,732,509.00 15,911.00 23,281,608.00 42,659,696 3,449,745 7,266,552 58,997 1,000 12 1,025 2 metro2110 200 32,000 42,230 39,177 39,927 87,613,498 4,304,906 83,308,592.00 9,411.00 25,431,222.00 55,310,085 1,141,723 1,398,764 17,387 2,110 12 2,135 4 Σ 20 6,000 10,850 89,689 64,944 71,534 11,633,585 5,564,940 6,068,645.00 150,609.00 2,486,087.00 2,516,935 311,239 482,614 121,161 288 71 334 Σ 6,950 96,200 200,525 163,653 172,973 221,668,112 24,761,050 196,907,062.00 204,396.00 61,573,600.00 116,013,512 6,540,671 12,308,327 266,556 4,146 117 4,283 8 Allmachines,allnetworks
  22. 22. Large-scale RINA Experimentation on FIRE+ 20networks svu + svud + ls + lsd #runs wait duration ov-adj overall policy APEX logic crt-net Σ crt-node Σ val-node val-net get-rumba get-report Nodes DIFs P-DIFs Trigg rumba-2-nodes 200 0:00:00 0:29:54 0:21:45 0:24:55 0:00:50 0:00:29 0:00:21 0:00:02 0:00:06 0:00:05 0:00:03 0:00:03 0:00:02 400 200 200 1,6 rumba-2-layers 200 0:00:00 0:30:04 0:21:43 0:24:53 0:01:15 0:00:42 0:00:33 0:00:02 0:00:12 0:00:11 0:00:03 0:00:03 0:00:02 800 800 600 2,4 rumba-mouse 200 0:00:00 0:29:47 0:21:57 0:24:47 0:03:02 0:01:36 0:01:26 0:00:02 0:00:37 0:00:35 0:00:04 0:00:05 0:00:02 2,800 200 3,400 6,4 rumba-cnop 200 0:00:00 0:30:32 0:22:31 0:25:41 0:05:26 0:02:40 0:02:45 0:00:03 0:01:11 0:01:13 0:00:06 0:00:10 0:00:02 5,600 1,400 6,800 12,0 rina-standard 200 0:00:00 0:30:15 0:21:46 0:25:16 0:01:30 0:00:49 0:00:41 0:00:02 0:00:16 0:00:15 0:00:03 0:00:03 0:00:02 1,000 400 800 2,8 renum-geant 200 0:00:00 0:31:40 0:23:00 0:26:40 0:07:55 0:03:37 0:04:18 0:00:03 0:01:53 0:01:47 0:00:11 0:00:22 0:00:02 8,000 200 12,400 16,8 renum-atnt 200 0:00:00 0:35:01 0:25:19 0:29:19 0:19:37 0:07:46 0:11:51 0:00:04 0:05:08 0:05:05 0:00:28 0:01:02 0:00:03 20,200 200 23,400 41,2 d22-copper 200 0:00:00 0:30:24 0:21:43 0:25:13 0:01:30 0:00:49 0:00:41 0:00:02 0:00:15 0:00:15 0:00:03 0:00:03 0:00:02 1,000 800 800 2,8 d22-coredifs2 200 0:00:00 0:30:17 0:21:48 0:25:18 0:01:50 0:01:00 0:00:50 0:00:02 0:00:20 0:00:19 0:00:03 0:00:04 0:00:02 1,400 600 3,200 3,6 d22-dc 200 0:00:00 0:30:11 0:21:51 0:25:21 0:02:13 0:01:11 0:01:02 0:00:02 0:00:26 0:00:25 0:00:03 0:00:04 0:00:02 1,800 400 1,600 4,4 d22-interxdifs 200 0:00:00 0:29:23 0:21:43 0:24:23 0:01:30 0:00:50 0:00:41 0:00:02 0:00:15 0:00:15 0:00:03 0:00:03 0:00:02 1,000 600 800 2,8 d22-lte 200 0:00:00 0:30:24 0:21:43 0:25:13 0:01:17 0:00:43 0:00:35 0:00:02 0:00:12 0:00:12 0:00:03 0:00:03 0:00:02 800 800 600 2,4 d22-metro 200 0:00:00 0:30:17 0:21:45 0:24:55 0:01:33 0:00:51 0:00:42 0:00:02 0:00:16 0:00:16 0:00:03 0:00:03 0:00:02 1,000 600 800 2,8 d22-pbb 200 0:00:00 0:29:52 0:21:51 0:24:51 0:02:39 0:01:24 0:01:15 0:00:02 0:00:31 0:00:32 0:00:03 0:00:04 0:00:02 2,400 800 2,200 5,6 d22-servicedifs 200 0:00:00 0:29:54 0:21:43 0:24:53 0:01:42 0:00:55 0:00:46 0:00:02 0:00:18 0:00:17 0:00:03 0:00:04 0:00:02 1,200 1,200 1,200 3,2 d22-together1 200 0:00:00 0:29:41 0:21:51 0:24:21 0:02:33 0:01:19 0:01:13 0:00:02 0:00:31 0:00:30 0:00:03 0:00:04 0:00:02 2,200 1,400 2,200 5,2 d22-together3 200 0:00:00 0:30:09 0:21:48 0:25:38 0:02:33 0:01:20 0:01:13 0:00:02 0:00:31 0:00:30 0:00:03 0:00:04 0:00:02 2,200 1,400 2,200 5,2 d22-wifi 200 0:00:00 0:29:34 0:21:42 0:24:32 0:01:29 0:00:49 0:00:40 0:00:02 0:00:15 0:00:15 0:00:03 0:00:03 0:00:02 1,000 800 1,000 2,8 d22-wifi2 200 0:00:00 0:29:26 0:21:48 0:24:08 0:01:19 0:00:44 0:00:35 0:00:02 0:00:12 0:00:12 0:00:03 0:00:03 0:00:02 800 800 600 2,4 apex-pcvs1 200 0:00:00 0:30:38 0:21:49 0:25:29 0:02:24 0:01:18 0:01:06 0:00:02 0:00:27 0:00:27 0:00:03 0:00:04 0:00:02 2,000 600 2,000 4,8 Σ 20 4,000 0:00:00 10:07:23 7:21:04 8:25:44 1:04:06 0:30:52 0:33:14 0:00:50 0:13:50 0:13:39 0:01:37 0:02:38 0:00:39 57,600 14,200 66,800 131,2 svu + svud + ls + lsd #runs wait, s duration, s ov-adj, s overall, s policy, ms APEX, ms logic, ms crt-net, ms Σ crt-node, ms Σ val-node, ms val-net ms, ms get-rumba, ms get-report, ms Nodes DIFs P-DIFs Trig rumba-2-nodes 200 0 1,794 1,305 1,495 49,789 28,722 21,067.00 2,467.00 5,559.00 5,338 2,826 3,008 1,869 2 1 1 rumba-2-layers 200 0 1,804 1,303 1,493 75,178 42,026 33,152.00 2,333.00 11,659.00 11,495 2,681 3,207 1,777 4 4 3 rumba-mouse 200 0 1,787 1,317 1,487 181,785 96,130 85,655.00 2,396.00 37,285.00 35,106 3,706 5,286 1,876 14 1 17 rumba-cnop 200 0 1,832 1,351 1,541 325,820 160,387 165,433.00 2,510.00 71,296.00 73,229 6,034 10,177 2,187 28 7 34 rina-standard 200 0 1,815 1,306 1,516 90,304 49,443 40,861.00 2,333.00 15,624.00 14,835 2,823 3,379 1,867 5 2 4 renum-geant 200 0 1,900 1,380 1,600 474,764 217,182 257,582.00 2,989.00 112,725.00 106,733 10,979 21,961 2,195 40 1 62 renum-atnt 200 0 2,101 1,519 1,759 1,177,064 465,769 711,295.00 4,491.00 308,142.00 304,787 28,418 61,982 3,475 101 1 117 d22-copper 200 0 1,824 1,303 1,513 89,608 48,675 40,933.00 2,403.00 14,923.00 15,409 2,951 3,383 1,864 5 4 4 d22-coredifs2 200 0 1,817 1,308 1,518 109,995 60,151 49,844.00 2,308.00 19,814.00 19,164 3,028 3,677 1,853 7 3 16 d22-dc 200 0 1,811 1,311 1,521 133,026 71,251 61,775.00 2,296.00 26,173.00 24,726 2,958 3,858 1,764 9 2 8 d22-interxdifs 200 0 1,763 1,303 1,463 90,346 49,786 40,560.00 2,237.00 15,048.00 15,081 2,946 3,427 1,821 5 3 4 d22-lte 200 0 1,824 1,303 1,513 77,378 42,787 34,591.00 2,341.00 12,115.00 12,048 2,852 3,381 1,854 4 4 3 d22-metro 200 0 1,817 1,305 1,495 93,466 51,161 42,305.00 2,489.00 15,990.00 15,651 2,861 3,452 1,862 5 3 4 d22-pbb 200 0 1,792 1,311 1,491 158,519 83,652 74,867.00 2,353.00 30,686.00 32,325 3,286 4,363 1,854 12 4 11 d22-servicedifs 200 0 1,794 1,303 1,493 101,589 55,140 46,449.00 2,449.00 17,650.00 17,432 3,165 3,872 1,881 6 6 6 d22-together1 200 0 1,781 1,311 1,461 152,515 79,123 73,392.00 2,302.00 30,831.00 30,446 3,398 4,419 1,996 11 7 11 d22-together3 200 0 1,809 1,308 1,538 152,893 80,079 72,814.00 2,241.00 30,625.00 30,375 3,260 4,428 1,885 11 7 11 d22-wifi 200 0 1,774 1,302 1,472 88,777 48,554 40,223.00 2,217.00 14,567.00 15,286 2,884 3,453 1,816 5 4 5 d22-wifi2 200 0 1,766 1,308 1,448 78,952 44,189 34,763.00 2,409.00 11,865.00 12,356 2,891 3,445 1,797 4 4 3 apex-pcvs1 200 0 1,838 1,309 1,529 144,266 78,250 66,016.00 2,421.00 27,416.00 26,860 3,147 4,189 1,983 10 3 10 Σ 20 4,000 0 36,443 26,464 30,344 3,846,034 1,852,457 1,993,577.00 49,985.00 829,993.00 818,682 97,094 158,347 39,476 288 71 334
  23. 23. OTHER RESULTS – VISUALISATION Large-scale RINA Experimentation on FIRE+
  24. 24. Other Experiment 1 Results Network visualization –  4 graphs, generated by the management strategy •  Network (nodes) graph: isolated nodes with their DIF structure •  Point-to-Point (PtP) graph: node connectivity (commonly named “topology”) •  DIF graph: all DIFs in a network, and their connections •  Network (IPCP) graph: all IPCPs in their DIFs per node –  Node finger print using onion diagrams –  Network 2-D view with onion diagrams –  Network 3-D view using onion diagrams RINA DAF Model (Application Model) –  Detailed model of a distributed application, as executables –  With infrastructure –  With RINA distributed infrastructure –  Facilitiy and DMS model Large-scale RINA Experimentation on FIRE+
  25. 25. Large-scale RINA Experimentation on FIRE+ D22–Together3
  26. 26. Large-scale RINA Experimentation on FIRE+ GÉANT
  27. 27. Large-scale RINA Experimentation on FIRE+ RumbaConvergedOperator
  28. 28. Standard RINA Example Large-scale RINA Experimentation on FIRE+
  29. 29. Connecting the Dots Large-scale RINA Experimentation on FIRE+
  30. 30. Remove DIFs Large-scale RINA Experimentation on FIRE+
  31. 31. Remember DIFs Large-scale RINA Experimentation on FIRE+
  32. 32. Change Names Large-scale RINA Experimentation on FIRE+
  33. 33. Define in YAML --- node: host1 registrations: - application: - {difid: border1, diftype: eth, diftype_number: 1} --- node: border1 registrations: - application: - {difid: routing, diftype: normal, diftype_number: 1} - {difid: host1, diftype: eth, diftype_number: 1} - routing: - {difid: interior, diftype: eth, diftype_number: 1} --- node: interior registrations: - routing: - {difid: border1, diftype: eth, diftype_number: 1} - {difid: border2, diftype: eth, diftype_number: 1} --- node: border2 registrations: - application: - {difid: routing, diftype: normal, diftype_number: 1} - {difid: host2, diftype: eth, diftype_number: 1} - routing: - {difid: interior, diftype: eth, diftype_number: 1} --- node: host2 registrations: - application: - {difid: border2, diftype: eth, diftype_number: 1} ... Large-scale RINA Experimentation on FIRE+
  34. 34. Generated Nodes Large-scale RINA Experimentation on FIRE+
  35. 35. Large-scale RINA Experimentation on FIRE+ StandardRINA
  36. 36. How to Look at Nodes Large-scale RINA Experimentation on FIRE+
  37. 37. How to See DIFs – Examples Large-scale RINA Experimentation on FIRE+
  38. 38. How to See DIFs – RINA Standard Large-scale RINA Experimentation on FIRE+
  39. 39. How to See DIFs – RINA Standard Large-scale RINA Experimentation on FIRE+
  40. 40. Large scale RINA Experimentation on FIRE + Thank you!

×