1. EE 122: Lecture 22 (Overlay Networks)
Ion Stoica
November 27, 2001

2. Motivations Changes in the network happen very slowly Why?
Internet network is a shared infrastructure; need to achieve consensus (IETF)
Many of proposals require to change a large number of routers (e.g., IP Multicast, QoS); otherwise end-users won’t benefit
Proposed changes that haven’t happened yet on large scale:
Congestion (RED ‘93); More Addresses (IPv6 ‘91)
Security (IPSEC ‘93); Multi-point (IP multicast ‘90)

3. Motivations (cont’d) One size does not fit all
Applications need different levels of
Reliability
Performance (latency)
Security
Access control (e.g., who is allowed to join a multicast group) …

4. Goals
Make it easy to deploy new functionalities in the network  accelerate the pace of innovation
Allow users to customize their service

5. Solution Deploy processing in the network
Have packets processed as they traverse the network
AS-1 IP
Overlay Network
(over IP)
AS-1

6. Examples Overlay multicast Increase robustness and performance
Content Distribution Networks (CDNs)

7. Motivations: IP Multicast Problems
Scalability with number of groups
Routers need to maintain per-group state
Aggregation of multicast addresses is complicated
Supporting higher level functionality is difficult
IP Multicast: best-effort multi-point delivery service
Reliability and congestion control for IP Multicast complicated
Need to deal with heterogeneous receiver  negotiation hard

8. Approach
Provide IP multicast functionality above the IP layer  application level multicast
Challenge: do this efficiently
Projects:
Narada
Overcast
Scattercast
Yoid …

9. Narada [Yang-hua et al, 2000]
Multi-source multicast
Involves only end hosts
Small group sizes <= hundreds of nodes
Typical application: chat

10. Narada (cont’d) Overlay Tree Gatech Stanford Stan1 Stan2 Berk1
CMU
Berk1
Berkeley
Berk2
Overlay Tree
Stan1
Gatech
Stan2
CMU
Berk1
Berk2

11. Discussion Scalability (# of groups) Easier to deploy
Routers do not maintain per-group state
End systems do, but they participate in very few groups
Easier to deploy
Potentially simplifies support for higher level functionality
Leverage computation and storage of end systems
For example, for buffering packets, transcoding, ACK aggregation
Leverage solutions for unicast congestion control and reliability
Scalability (# of receivers) still an open issue
Other solutions (e.g., Overcast) are scalable but not as flexible: typically assume single-source multicast trees

12. Examples Overlay multicast Increase robustness and performance
Content Distribution Networks (CDNs)

13. Motivation Routing in the Internet is not optimal with respect to Why?
Performance: packets do not necessary propagate along the shortest path
Robustness: two nodes may not be able to communicate although there is a path between them
Why?

14. Solution Control routing at the application level Projects
Resilient Overlay Networks
Detour

15. Resilient Overlay Networks [Anderson et al, 2001]
Make the end to end communication more robust
Each node monitor the network conditions to every other node by periodically probing the network
If node n1 cannot reach n2 directly, try to reach it through an intermediate node n3
Intended application: robust communication in a small group (<= 50, 60 nodes)

16. Resilient Overlay Networks (cont’d)
N1 can no longer communicate directly to N2 N2 N1

17. Resilient Overlay Networks (cont’d)
Find a node N3 such that N1 can communicate with N3 and N3 with N2 N2 N1

18. Discussion
Find an alternate path in most cases when two nodes cannot communicate directly’
Can be used to provide better delay and bandwidth than the direct IP route between two nodes
Scalability still an open issue

19. Examples Overlay multicast Increase robustness and performance
Content Distribution Networks (CDNs)

20. Motivations Today’s Internet is not optimized for Web traffic
Many clients transfer the same information (e.g., CNN front page, software downloads)
Identical files are transferred over and over again
IP multicast not a solution:
Users don’t access the same info at the same time
Users have widely different capabilities:
Communication: cable modem vs. dial up modem
Display: high-resolution workstation monitor vs. Palm Pilot …

21. Solution
Have nodes inside the network that store and process the documents
Examples: web caching, transcoding

22. “Base-line” Solution Many clients transfer same information 
Generate unnecessary server and network load
Clients experience unnecessary latency
Server
Backbone ISP
ISP-1
ISP-2
Clients

23. Reverse Caches Cache documents close to server  decrease server load
Typically done by content providers
Server
Reverse caches
Backbone ISP
ISP-1
ISP-2
Clients

24. Forward Proxies
Cache documents close to clients  reduce network traffic and decrease latency
Typically done by ISPs or corporate LANs
Server
Reverse caches
Backbone ISP
ISP-1
ISP-2
Forward caches
Clients

25. Content Distribution Networks (CDNs)
Integrate forward and reverse caching functionalities into one overlay network (usually) administrated by one entity
Example: Akamai
Documents are cached both
As a result of clients’ requests (pull)
Pushed in the expectation of a high access rate
Beside caching do processing, e.g.,
Handle dynamic web pages
Transcoding

26. CDNs (cont’d) Server CDN Backbone ISP ISP-1 ISP-2 Forward caches
Clients

27. Discussion
CDNs were developed to efficiently handle today’s web traffic
Relive server and network load
Perform load balancing, caching
Increase client performance
Process data according to clients needs
A basic technique that makes CDNs possible is redirection (see HTTP). How?

28. Conclusions
Overlay networks allow to deploy new services in the network today, e.g.,
Multicast, CDNs
Can increase network robustness and client perceived performance, e.g.,
RON, CDNs
Challenges
Efficiency
A packet may need to be processed above transport layer before reaching the destination
Path followed by the packet might be worse than the direct IP route
Scalability