Towards a Transparent and Proactively-Managed Internet

1. Towards a Transparent and Proactively-Managed Internet Ehab Al-Shaer School of Computer Science DePaul University Yan Chen EECS Department Northwestern University

2. Motivations • The Internet has evolved to become a un-cooperative ossificated network of networks • Network has to be treated as a blackbox • Performance of even neighboring networks are opaque • Inter-domain routing based on policies but not performance • Have to resort to overlay networks which are suboptimal • Diagnosis and fault location extremely hard • Network config management reactive and expensive • Reactive configurations: tune after deployment • Vulnerable: manually handled and subject to conflicts • Imperative & fragmented: need to access several specific devices in order to implement a service goal

3. Proposed Solution I: Transparent Internet • Every network shares its measurement and management information with other networks when necessary (glass box) • Link-level performance: delay, loss rate, available bandwidth, etc. • Management info • Configuration: QoS setting, traffic policing • Middle box settings: firewalls, etc. • The information sharing • As part of the inter-domain protocols: Transparent Gateway Protocols (TGP) • Other applications: leverage DHT

4. Analogy to the Airline Alliance • When airlines compose multi-lag flights, they need more than just route info. • Type of aircraft, # of vacancies, probability of punctuation, etc. • Such open model is mutual beneficial • Provide the best flight composition for clients • Similarly, open network model can provide best communications for applications

5. Proposed Solution II: Proactive Configuration Management • Proactive verification: configuration verified and translated to different vendor specific devices • Proactive validation: Test the configuration changes on the real archived network traffic without interrupting the main operation network • Autonomic configuration: configurations are auto-tuned dynamically to achieve the “objectives Dynamic Validation: auto-tuning Deploying Optimizing Evaluating defining Verifying Validation

6. Objectives Provides a completely transparent view of the Internet to networks and applications • Diagnosis & trouble shooting becomes extremely easy • No more Internet tomography needed • Flexible inter-domain routing • Not just based on policy or # of AS/hops • Flexible metrics based on bandwidth, latency, etc. • Global traffic engineering • Each AS performs its own local traffic engineering • Provide AS path-level routing guide • Unified framework that applications query (push/pull) info as needed • Streaming media, content distribution • Anomaly/security applications

7. Flexible Inter-domain Routing • Multiple routing paths with TGP • Incorporate measurement info into AS paths • Bandwidth-intensive and latency-intensive applications can take different AS paths. • Challenge: inter-domain routing based on bandwidth without making reservation • Solution: Discretize the bandwidth for better stability • Though stability is a classical problem, not unique to TGP

8. Global Traffic Engineering • For the current Internet, only local optimum is achieved in each AS • Allowing the network to handle all traffic patterns possible, within the networks ingress-egress capacity constraints (e.g. two phase routing) • With global information, we can potentially achieve global optimum (or Nash equilibrium) • Each AS is a selfish individual • A center (or each AS) infers the Nash equilibrium • Each AS can try the Nash equilibrium, or attempt to benefit itself based on the inferred Nash equilibrium

9. 2G 2G 1G 2G Example of Benefit of Global TE 1G traffic to AS 1 AS 4 AS 2 1G AS 5 AS 1 1G traffic to AS 1 AS 3

10. 0.5G 0.5G 0.5G 1G 1.5G 2G 1G 2G 2G Example of Benefit of Global TE • Without Global TE 1G traffic to AS 1 AS 4 AS 2 1G AS 5 AS 1 1G traffic to AS 1 AS 3

11. 1G 1G 1G 1G 2G 1G 2G 2G Example of Benefit of Global TE • With Global TE 1G traffic to AS 1 AS 4 AS 2 1G AS 5 AS 1 1G traffic to AS 1 AS 3

12. Unified Transparency Framework for Various Functionality • Sharing of anomaly/security-related measurement • Various characteristics of traffic: heavy hitter, heavy changes, histogram, etc. • Self-diagnosis to survivability • Adaptations • Routing adaptations at router level or application level

13. Practical Issues and Solutions • Incentives for information sharing • Mandatory for next-generation Internet ? • Alliance model for incremental growth • Security/cheating: Trust but verify • Trust most of the info shared but periodically verify • Much easier than the current Internet tomography unless many ASes collude • Verification part of the protocol • Some fields in the packet headers designed for that purpose

14. Backup Materials

15. Measurement Info to Share • Basic metrics • Delay, loss rate, capacity, available bandwidth • Demand (or traffic volume) and application types • Intra-AS Measurement Info • Link-level info • Queried only when necessary • Aggregated Info • OD flow level info • Path segment b/t entry and exit points in each AS • Inter-AS Measurement Info • General AS relationship • AS-level topology • Inter-AS link metrics

16. Transparent Internet Architecture Combined w/ routing info and export to neighboring ASes through TGP protocol Provide global retrievable Management Information Base (MIB) with DHT Network link-level monitoring

17. iterate Algorithm design Realistic simulation Methodology • Network topology • Web workload • Network end-to-end latency measurement Analytical evaluation PlanetLab tests

18. replica cache always update adaptive coherence client DHT mesh TGP MIB Dissemination Architecture • Leverage Distributed Hash Table - Tapestry for • Distributed, scalable location with guaranteed success • Search with locality data source data plane Dynamic Replication/Update and Replica Management Replica Location Web server SCAN server Overlay Network Monitoring network plane

19. Adaptive Overlay Streaming Media Stanford UC San Diego UC Berkeley X HP Labs • Implemented with Winamp client and SHOUTcast server • Congestion introduced with a Packet Shaper • Skip-free playback: server buffering and rewinding • Total adaptation time < 4 seconds

20. Summary • A tomography-based overlay network monitoring system • Selectively monitor a basis set of O(n logn) paths to infer the loss rates of O(n2) paths • Works in real-time, adaptive to topology changes, has good load balancing and tolerates topology errors • Both simulation and real Internet experiments promising • Built adaptive overlay streaming media system on top of TOM • Bypass congestion/failures for smooth playback within seconds

21. Tie Back to SCAN Provision: Dynamic Replication + Update Multicast Tree Building Replica Management: (Incremental) Content Clustering Network DoS Resilient Replica Location: Tapestry Network End-to-End Distance Monitoring Internet Iso-bar: latency TOM: loss rate

22. Contribution of My Thesis • Replica location • Proposed the first simulation-based network DoS resilience benchmark and quantify three types of directory services • Dynamically place close to optimal # of replicas • Self-organize replicas into a scalable app-level multicast tree for disseminating updates • Cluster objects to significantly reduce the management overhead with little performance sacrifice • Online incremental clustering and replication to adapt to users’ access pattern changes • Scalable overlay network monitoring

23. Existing CDNs Fail to Address these Challenges No coherence for dynamic content X Unscalable network monitoring - O(M ×N) M: # of client groups, N: # of server farms Non-cooperative replication inefficient

24. Problem Formulation • Subject to certain total replication cost (e.g., # of URL replicas) • Find a scalable, adaptive replication strategy to reduce avg access cost

25. SCAN: Scalable Content Access Network CDN Applications (e.g. streaming media) Provision: Cooperative Clustering-based Replication Coherence: Update Multicast Tree Construction Network Distance/ Congestion/ Failure Estimation User Behavior/ Workload Monitoring Network Performance Monitoring red: my work, black: out of scope

26. Comparison of Content Delivery Systems (cont’d)