1. Scott Shenker and Ion Stoica Computer Science Division Department of Electrical Engineering and Computer Sciences University of California, Berkeley Berkeley, CA 94720-1776 Internet Architectures: Internet Indirection Infrastructure (i3), …

2. 2 Motivations Today’s Internet is built around a unicast point-to-point communication abstraction: –Send packet “p” from host “A” to host “B” This abstraction allows Internet to be highly scalable and efficient, but… … not appropriate for applications that require other communications primitives: –Multicast –Anycast –Mobility –Service composition (Middleboxes) –…–…

3. 3 Why? Point-to-point communication  implicitly assumes there is one sender and one receiver, and that they are placed at fixed and well-known locations –E.g., a host identified by the IP address 128.32.xxx.xxx is located in Berkeley

4. 4 IP Solutions Extend IP to support new communication primitives, e.g., –Mobile IP –IP multicast –IP anycast Disadvantages: –Difficult to implement while maintaining Internet’s scalability (e.g., multicast) –Require community wide consensus -- hard to achieve in practice

5. 5 Application Level Solutions Implement the required functionality at the application level, e.g., –Application level multicast (e.g., Fastforward, Narada, Overcast, Scattercast…) –Application level mobility Disadvantages: –Efficiency hard to achieve –Redundancy: each application implements the same functionality over and over again –No synergy: each application implements usually only one service; services hard to combine

6. 6 Key Observation Virtually all previous proposals use indirection! “Any problem in computer science can be solved by adding a layer of indirection”

7. 7 Indirection is Everywhere! “foo.org” IP foo DNS Server foo.org IP foo IP foo DNS (IP home,data) Home Agent IP home IP mobile (IP mobile,data) IP mofile Mobile IP NAT Box IP nat :P nat IP dst :P dst (IP dst :P dst,data) IP dst NAT Internet (IP M  IP R1 ) (IP M  IP R2 ) (IP M,data) (IP R1,data) (IP R2,data) IP R1 IP R2 IP Multicast (IP foot,data) (IP nat :P nat,data)

8. 8 Internet Indirection Infrastructure (i3) Use an overlay network to implement this layer –Incrementally deployable; don’t need to change IP Build an efficient indirection layer on top of IP IP TCP/UDP Application Indir. layer

9. 9 Internet Indirection Infrastructure (i3) Each packet is associated an identifier id To receive a packet with identifier id, receiver R maintains a trigger ( id, R) into the overlay network Sender idR trigger iddata Receiver (R) iddata R

10. 10 Service Model API –sendPacket( p ); –insertTrigger( t ); –removeTrigger( t ) // optional Best-effort service model (like IP) Triggers periodically refreshed by end-hosts ID length: 256 bits

11. 11 Mobility Host just needs to update its trigger as it moves from one subnet to another Sender Receiver (R1) Receiver (R2) idR1 idR2

12. 12 iddata Multicast Receivers insert triggers with same identifier Can dynamically switch between multicast and unicast Receiver (R1) idR1 Receiver (R2) idR2 Sender R1data R2data iddata

13. 13 Anycast Use longest prefix matching instead of exact matching –Prefix p: anycast group identifier –Suffix s i : encode application semantics, e.g., location Sender Receiver (R1) p|s 1 R1 Receiver (R2) p|s 2 R2 p|s 3 R3 Receiver (R3) R1 data p|a data p|a data

14. 14 Service Composition: Sender Initiated Use a stack of IDs to encode sequence of operations to be performed on data path Advantages –Don’t need to configure path –Load balancing and robustness easy to achieve Sender Receiver (R) id T T id R Transcoder (T) T,id data iddata R id T,id data id T,id data

15. 15 Service Composition: Receiver Initiated Receiver can also specify the operations to be performed on data Receiver (R) id id F,R Firewall (F) Sender id F F id F,R data R F,R data id data id data

16. 16 Outline  Implementation Examples Security Architecture Optimizations Applications

17. 17 Quick Implementation Overview i3 is implemented on top of Chord Each trigger t = ( id, R ) is stored on the node responsible for id Use Chord recursive routing to find best matching trigger for packet p = ( id, data )

18. 18 Routing Example R inserts trigger t = (37, R) ; S sends packet p = (37, data) An end-host needs to know only one i3 node to use i3 –E.g., S knows node 3, R knows node 35 3 7 20 35 41 37R 3 7 20 35 41 37R S R trigger(37,R) send(37, data) send(R, data) Chord circle S R 0 2 m-1

19. 19 Sender (S) Optimization #1: Path Length Sender/receiver caches i3 node mapping a specific ID Subsequent packets are sent via one i3 node [42..3] [4..7] [8..20] [21..35] [36..41] 37R data R cache node Receiver (R)

20. 20 Optimization #2: Triangular Routing Use well-known trigger for initial rendezvous Exchange a pair of (private) triggers well-located Use private triggers to send data traffic [42..3] [4..7] [8..20] [21..35] [36..41] 37R R [2] 2S 37 [2] 2 [30] 30R S [30] 30 data R Receiver (R) Sender (S)

21. 21 Outline Implementation  Examples –Heterogeneous multicast –Scalable Multicast –Load balancing –Proximity

22. 22 Example 1: Heterogeneous Multicast Sender not aware of transformations ( sends MPEG) Receiver R1 specifies that wants to receive JPEG data, while R2 specifies that wants to receive MPEG data Receiver R1 (JPEG) id_ MPEG/JPEG S_ MPEG/JPEG id (id_ MPEG/JPEG, R1) send(id, data) S_MPEG/JPEG Sender (MPEG) send((id _MPEG/JPEG, R1), data) send(R1, data) id R2 Receiver R2 (MPEG) send(R2, data)

23. 23 Example 2: Scalable Multicast i3 doesn’t provide direct support for scalable multicast Solution: have end-hosts build an hierarchy of trigger of bounded degree –multicast tree, using chains of triggers R2R2 R1R1 R4R4 R3R3 g R 2 g R 1 gxgx x R 4 x R 3 (g, data) (x, data)

24. 24 Example 2: Scalable Multicast (Discussion) Unlike IP multicast, i3 1.Implement only small scale replication  allow infrastructure to remain simple, robust, and scalable 2.Gives end-hosts control on routing  enable end-hosts to –Achieve scalability, and –Optimize tree construction to match their needs, e.g., delay, bandwidth

25. 25 Example 3: Load Balancing Servers insert triggers with IDs that have random suffixes Clients send packets with IDs that have random suffixes S1 1010 0101 S2 1010 S3 1010 1101 S4 S1 S2 S3 S4 A B send(1010 0110,data) send(1010 1110,data) 1010 0010

26. 26 Example 4: Proximity Suffixes of trigger and packet IDs encode the server and client locations 1000 0010 S1 1000 1010 S2 1000 1101 S3 S1 S2 S3 send(1000 0011,data)

27. 27 Example 5: Protection against DOS Attacks Problem scenario: attacker floods the incoming link of the victim Solution: stop attacking traffic before it arrives at the incoming link –Today: call the ISP to stop the traffic, and hope for the best! Approach: give end-host control on what packets they receive –Enable end-hosts to stop the attacks in the network

28. 28 Example 5: Why End-Hosts (and not Network)? End-hosts can better react to an attack –Aware of semantics of traffic they receive –Know what traffic they want to protect End-hosts may be in a better position to detect an attack –Flash-crowd vs. DoS

29. 29 Example 5: Some Useful Defenses 1.White-listing: avoid receiving packets on arbitrary ports 2.Traffic isolation: –Contain the traffic of an application under attack –Protect the traffic of established connections 3.Throttling new connections: control the rate at which new connections are opened (per sender)

30. 30 Example 5: (1) White-listing Packets not addressed to open ports are dropped in the network –Create a public trigger for each port in the white list –Allocate a private trigger for each new connection ID S S Sender (S) Receiver (R) S [ID R ] ID S [ID R ] ID R R R data ID P R R [ID S ] ID P [ID S ] ID R data ID P – public trigger ID S, ID R – private triggers

31. 31 Example 5: (2) Traffic Isolation Drop triggers being flooded without affecting other triggers –Protect ongoing connections from new connection requests –Protect a service from an attack on another services Victim (V) Attacker (A) Legitimate client (C) ID 2 V ID 1 V Transaction server Web server

32. 32 Example 5: (2) Traffic Isolation Drop triggers being flooded without affecting other triggers –Protect ongoing connections from new connection requests –Protect a service from an attack on another services Victim (V) Attacker (A) Legitimate client (C) ID 1 V Transaction server Web server Traffic of transaction server protected from attack on web server Traffic of transaction server protected from attack on web server

33. 33 Server (S) Client (C) Example 5: (3) Throttling New Connections Redirect new connection requests to a gatekeeper –Gatekeeper has more resources than victim –Can be provided as a 3 rd party service ID C C XS puzzle puzzle’s solution Gatekeeper (A) ID P A

34. 34 Another View of Indirection/Delegation Indirection point  point where control is transferred from sender to receiver –Translation/forwarding entry usually controlled by receiver

35. 35 End-host Empowerment Both the sender and receiver are able to explicitly control the service-path –Note: multiple indirection points possible Internet Receiver Indirection point (tussle boundary) Sender Middlebox 1 (M1) M2 M3M4 sender control receiver control

36. 36 Realization: i3 vs DOA Internet i3 M1 M2 R ([id S1,id R ], data) id R [id M2,R] id M1 M1 id M2 S2 i3 Internet M1 R ([id S1,id S2 ], data) id M2 id R id M1 M1 id M2 M2 id S1 S1 M2 id S2 S2 id R R id R R Name resolution infrastructure (e.g., OpenDHT) DOA