1. Towards Resilient Networks using Programmable Networking Technologies Linlin Xie, Paul Smith, Mark Banfield, Helmut Leopold, James Sterbenz and David Hutchison Computing Department Lancaster University Department of Electrical Engineering and Computer Science University of Kansas Telekom Austria AG

2. Linlin XieIWAN 20052 Presentation Outline Introduction to resilience networking –Motivation –Resilient networks –Aims –Approaches Scenario –Flash Crowd Event to Web Servers –Ill-Effect Detection –Remediation

3. Linlin XieIWAN 20053 Motivation The Internet is a utility –Consumers, businesses, governments Failures & attacks are inevitable –Hurricane Katrina, 9/11, NE blackout… –Link/device failures, DDoS… Current Internet and applications not resilient Need networking effort: network providers should take the responsibility –to protect network resources and optimize the utilization –to protect cross traffic as well as stricken customers

4. Linlin XieIWAN 20054 Resilient Networks Ability of network to maintain or recover an acceptable level of service in the face of challenges to normal operation in an acceptable period of time Example challenges to normal operation: –Unusual traffic load (e.g. flash crowds) –High-mobility of nodes and sub-networks –Weak and episodic connectivity of wireless channels –Long delay paths –Large-scale natural disasters –Attacks against the network hardware, software, protocol infrastructure –Natural faults of network components

5. Linlin XieIWAN 20055 General Resilience Aims Provide acceptable services to applications –Ensure information is accessible –Maintain end-to-end communication when possible –Operation of distributed processing and networked storage Resilient services must remain accessible –Can degrade gracefully when necessary, but ensure correctness –Recover rapidly and automatically when challenges dissipate

6. Linlin XieIWAN 20056 Role of Programmable Networks Challenges to normal operation will rapidly change over time and space Prescribed solutions cannot be deployed Therefore, resilient networks must: –Operate in real-time –Be autonomic –Be context-aware and “intelligent” –Be dynamically extensible Programmable networking technologies are key to enabling these facilities

7. Linlin XieIWAN 20057 Programmable Networking Facilities Dynamic extensibility and self-organisation –Programmability allows dynamic response to challenges by altering its behaviour –But need to be controlled in order to avoid misuse and potential harm (e.g., stealthy interfaces) –Service to determine suitable locations to deploy services is required Traffic and network environment awareness –Packet inspection at line speed –Network information collection Cross layer awareness and interaction –Avoid waste of resources and enhance coordination –How and the possible consequences need further study

8. Linlin XieIWAN 20058 Related Work Knowledge Plane (“KP”, David Clark et al. MIT) –Part of the KP purpose is to detects faults &intrusion and mitigate the ill-effects –It proposes to add a new plane into the Internet architecture –The supporting technology is cognitive AI –The purpose of KP covers a very broad range –Cognitive AI is still in its initial stage of development –No concrete mechanisms for resilience maintenance yet Autonomic Communications –Efforts largely focused on self-configuring, self-managing, and self-healing networked server systems –Initiatives now on making communications system autonomic Learn network context and automatically adapt

9. Linlin XieIWAN 20059 Related Work (Cont’d) COPS (Checking, Observing and Protecting Services) (Randy Katz, UCB) –Propose to protect network using iBoxes on the network edge –Propose an annotation layer between IP and transport layers to carry information along the traffic Other similar/related efforts –Disruption Tolerant Network (DTN) Mean to provide stable end to end paths for applications when network connectivity faces challenges –Survivability Enable the system to fulfil its mission even in the presence of attacks or failures (CMU) –Resilience covers a broader range including protection against unusual traffic load (e.g., FC)

10. Linlin XieIWAN 200510 Resilience Networking Scenario Demonstrate the applicability of programmable networks Flash Crowd Event –Although flash crowd requests are legitimate, the damage caused is equally as bad as malicious attacks Two activities investigated: –Detecting ill-effects of a flash crowd on Web servers –Remediation of a flash crowd event

11. Linlin XieIWAN 200511 Network Model We take the role of network provider, i.e. ISP, to detect and mitigate the ill-effects occurred to the web servers network (which subscribes such service), and protect resources and cross traffic in the network of its own

12. Linlin XieIWAN 200512 Ill-Effects Detection Detection basis: –An increase of request rate in an association with a decrease or level-off of response rate Detection location: –The edge router that connects the web server network to the ISP network Algorithm overview: –compare actual observed response rate with the expected one

13. Linlin XieIWAN 200513 Ill-Effect Detection (Cont’d) Mechanism based on the formulae: Where the sizes of response objects are estimated according to the size distribution calculated from sampling the “content-length” domain in HTTP header of the response traffic

14. Linlin XieIWAN 200514 Simulation Setup Based on ns-2 Topology α chosen to 0.2 Detection interval t set to be 30s

15. Linlin XieIWAN 200515 Simulation Setup (Cont’d) Parameters set up as follows

16. Linlin XieIWAN 200516 Simulation Results Flash crowd traffic simulation Flash crowd starts at 500s We use access link congestion to simulate the server-side behavior

17. Linlin XieIWAN 200517 Simulation Results (Cont’d) Detection results Ratio of the actual response volume over the expected one

18. Linlin XieIWAN 200518 Simulation Results Statistical distribution of ratio samples of background traffic: N(1.10817, 0.227477 2 ) The 95% confidence range of this distribution is [0.662315, 1.554025]

19. Linlin XieIWAN 200519 Remediation Drop excessive requests at the ingress edges of the network –Pushback-similar mechanism Opportunistic multiple-routing of large response traffic that is packet-sequence-tolerant to protect cross traffic from degrading QoS too much –Multiple routes database –Path bandwidth information collection –Split the response traffic in proportion to the available bandwidth of each path Must consider the possibility of having zero or just a few of programmable routers in the core network

20. Linlin XieIWAN 200520 Scenario Conclusions Contributions –Cross-layer coordination in detection –Cross traffic protection in the network Future work –Mitigation mechanism and experiments –Design and improve a resilient network infrastructure and architecture

21. Linlin XieIWAN 200521 Conclusions Resilient networks are crucial for the future information society Programmable networking technology is appropriate for building resilient networks Example flash crowd scenario demonstrates the need for programmability, namely: –cross-layer interaction –dynamic extensibility

22. Linlin XieIWAN 200522 Thanks! Questions?