1. © Manasa Quantifying Metrics for Resilient and Survivable Networks EECS 801 Graduate Reading © 2008–Manasa K 6 June 2008 Manasa K Department of Electrical Engineering & Computer Science EECS 801 mkeshava@eecs.ku.edu

2. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Quantifying Metrics for Resilient and Survivable Networks Abstract Network state can be characterized by operational metrics and service parameters. Metrics include degree of connectivity, bandwidth, BER etc. Service parameters include delay, jitter, good put etc. This project involves understanding the transformation of network State as it moves from the acceptable to unacceptable under the influence of adverse conditions. Henceforth,metric BER under constant BW was taken to analyze the network state.

3. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Outline Introduction and Motivation Simulation Phase I Simulation Phase II Simulation Phase III Conclusion Reference

4. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks 4 Metrics for Resilient and Survivable Networks Introduction and Motivation Introduction and Motivation Simulation Phase I Simulation Phase II Simulation Phase III Conclusion Reference

5. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Introduction and Motivation The Y-axis represents the service of the network The X-axis represents the condition of the network under adverse conditions Understanding the performance of the various network states helps build a more resilient network.

6. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Phase I Introduction and Motivation Simulation Phase I Simulation Phase II Simulation Phase III Conclusion Reference

7. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Phase I ns-2 Simulations started from fundamentals –Ensuring the sufficient BW is obtained with UDP-CBR for Wireless Nodes (max 15 Mb) –Usage of Error model for wireless node –Multi-hop routing/forwarding in between wireless nodes –Increased the number of nodes to 10 –Effect of RTS/CTS functionality, its effect on throughput. –Ensured the scripts were correct Throughtput End to End Delay Packetloss

8. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Phase II Introduction and Motivation Simulation Phase I Simulation Phase II Simulation Phase III Conclusion Reference

9. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Phase II Classified into 3 Scenarios –No ERROR No Mobility –With ERROR No Mobility –With ERROR With Mobility Simulations Setup –PER =.001 –3 Mobility Pattern –2 Traffic Scenarios –Total 6 simulations for each scenario Plots Included –Good put, Packet loss per sec, end to end packet delay

10. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Phase III Introduction and Motivation Simulation Phase I Simulation Phase II Simulation Phase III Conclusion Reference

11. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Phase III Classified into 2 Scenarios –No_Error_With_Mobility_Dim_820 –With_Error_With_Mobility_Dim_820 Simulations Setup –PER =.001 –3 Mobility Pattern –2 Traffic Scenarios –Total 6 simulations for each scenario Plots Included –Good put, Packet loss per sec, average delay per sec

12. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Phase III No_Error_With_Mobility_Dim_820

13. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Phase III No_Error_With_Mobility_Dim_820

14. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Phase III With_Error_With_Mobility_Dim_820

15. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Phase III With_Error_With_Mobility_Dim_820

16. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Conclusion Introduction and Motivation Simulation Phase I Simulation Phase II Simulation Phase III Conclusion Reference

17. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Conclusion The idea is to generate a Graph as shown, and then to classify the network state This would then be for one independent BER metric Delay Good put Channel Condition BW-Fixed BER – Varying ----> Good put + Delay

18. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks Metrics for Resilient and Survivable Networks Reference Introduction and Motivation Simulation Phase I Simulation Phase II Simulation Phase III Conclusion Reference

19. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks 19 Metrics for Resilient and Survivable Networks Reference [1] Poster: Towards Quantifying Metrics For Resilient and Survivable Networks ihttps://wiki.ittc.ku.edu/resilinets_wiki/index.php/Metrics_and_Modelling

20. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks 20 Metrics for Resilient and Survivable Networks Acknowledgements James Sterbenz K.U. Professor –Comments and suggestions Abdul Jabber

21. © Manasa 6 June 2008Quantifying Metrics for Resilient and Survivable Networks 21 Questions ?