1. EE 122: Peer-to-Peer (P2P) Networks
Ion Stoica
November 27, 2002

2. How Did it Start? A killer application: Naptser
Free music over the Internet
Key idea: share the storage and bandwidth of individual (home) users
Internet

3. Model Each user stores a subset of files
Each user has access (can download) files from all users in the system

4. Main Challenge Find where a particular file is stored E? E F D C A B

5. Other Challenges
Scale: up to hundred of thousands or millions of machines
Dynamicity: machines can come and go any time

6. Napster
Assume a centralized index system that maps files (songs) to machines that are alive
How to find a file (song)
Query the index system  return a machine that stores the required file
Ideally this is the closest/least-loaded machine
ftp the file
Advantages:
Simplicity, easy to implement sophisticated search engines on top of the index system
Disadvantages:
Robustness, scalability (?)

7. Napster: Example E m5 E m6 E? F D m1 A m2 B m3 C m4 D m5 E m6 F m4 E?

8. Gnutella Distribute file location Idea: multicast the request
Hot to find a file:
Send request to all neighbors
Neighbors recursively multicast the request
Eventually a machine that has the file receives the request, and it sends back the answer
Advantages:
Totally decentralized, highly robust
Disadvantages:
Not scalable; the entire network can be swamped with request (to alleviate this problem, each request has a TTL)

9. Gnutella: Example
Assume: m1’s neighbors are m2 and m3; m3’s neighbors are m4 and m5;… m5 E m6 E E? F D m4 E? C A B m3 m1 m2

10. FastTrack Use the concept of supernode
A combination between Napster and Gnutella
When a user joins the network it joins a supernode
A supernode acts like Napster server for all users connected to it
Queries are brodcasted amongst supernodes (like Gnutella)

11. Other Solutions to the Location Problem
Goal: make sure that an item (file) identified is always found
Abstraction: a distributed hash-table data structure
insert(id, item);
item = query(id);
Note: item can be anything: a data object, document, file, pointer to a file…
Proposals (also called structured p2p networks)
CAN (ACIRI/Berkeley)
Chord (MIT/Berkeley)
Pastry (Rice)
Tapestry (Berkeley)

12. Content Addressable Network (CAN)
Associate to each node and item a unique id in an d-dimensional space
Properties
Routing table size O(d)
Guarantee that a file is found in at most d*n1/d steps, where n is the total number of nodes

13. CAN Example: Two Dimensional Space
Space divided between nodes
All nodes cover the entire space
Each node covers either a square or a rectangular area of ratios 1:2 or 2:1
Example:
Assume space size (8 x 8)
Node n1:(1, 2) first node that joins  cover the entire space 7 6 5 4 3 n1 2 1 1 2 3 4 5 6 7

14. CAN Example: Two Dimensional Space
Node n2:(4, 2) joins  space is divided between n1 and n2 7 6 5 4 3 n1 n2 2 1 1 2 3 4 5 6 7

15. CAN Example: Two Dimensional Space
Node n2:(4, 2) joins  space is divided between n1 and n2 7 6 n3 5 4 3 n1 n2 2 1 1 2 3 4 5 6 7

16. CAN Example: Two Dimensional Space
Nodes n4:(5, 5) and n5:(6,6) join 7 6 n5 n4 n3 5 4 3 n1 n2 2 1 1 2 3 4 5 6 7

17. CAN Example: Two Dimensional Space
Nodes: n1:(1, 2); n2:(4,2); n3:(3, 5); n4:(5,5);n5:(6,6)
Items: f1:(2,3); f2:(5,1); f3:(2,1); f4:(7,5); 7 6 n5 n4 n3 5 f4 4 f1 3 n1 n2 2 f3 1 f2 1 2 3 4 5 6 7

18. CAN Example: Two Dimensional Space
Each item is stored by the node who owns its mapping in the space 7 6 n5 n4 n3 5 f4 4 f1 3 n1 n2 2 f3 1 f2 1 2 3 4 5 6 7

19. CAN: Query Example Each node knows its neighbors in the d-space
Forward query to the neighbor that is closest to the query id
Example: assume n1 queries f4 7 6 n5 n4 n3 5 f4 4 f1 3 n1 n2 2 f3 1 f2 1 2 3 4 5 6 7

20. Chord
Associate to each node and item a unique id in an uni-dimensional space
Properties
Routing table size O(log(N)) , where N is the total number of nodes
Guarantees that a file is found in O(log(N)) steps

21. Data Structure Assume identifier space is 0..2m Each node maintains
Finger table
Entry i in the finger table of n is the first node that succeeds or equals n + 2i
Predecessor node
An item identified by id is stored on the succesor node of id

22. Chord Example Assume an identifier space 0..8
Node n1:(1) joinsall entries in its finger table are initialized to itself
Succ. Table
i id+2i succ 1 7 6 2 5 3 4

23. Chord Example Node n2:(3) joins 1 7 6 2 5 3 4 Succ. Table i id+2i succ
i id+2i succ 1 7 6 2
Succ. Table
i id+2i succ 5 3 4

24. Chord Example Nodes n3:(0), n4:(6) join 1 7 6 2 5 3 4 Succ. Table
i id+2i succ
Succ. Table
i id+2i succ 1 7
Succ. Table
i id+2i succ 6 2
Succ. Table
i id+2i succ 5 3 4

25. Chord Examples Nodes: n1:(1), n2(3), n3(0), n4(6)
Succ. Table
Items
Nodes: n1:(1), n2(3), n3(0), n4(6)
Items: f1:(7), f2:(2)
i id+2i succ 7
Succ. Table
Items 1 7
i id+2i succ 1
Succ. Table 6 2
i id+2i succ
Succ. Table
i id+2i succ 5 3 4

26. Query Upon receiving a query for item id, node n
Check whether the item is stored at the successor node s, i.e.,
id belongs to (n, s)
If not, forwards the query to the largest node in its successor table that does not exceed id
Succ. Table
Items
i id+2i succ 7
Succ. Table
Items 1 7
i id+2i succ 1
query(7)
Succ. Table 6 2
i id+2i succ
Succ. Table
i id+2i succ 5 3 4

27. Discussion Query can be implemented
Iteratively
Recursively
Performance: routing in the overlay network can be more expensive than in the underlying network
Because usually there is no correlation between node ids and their locality; a query can repeatedly jump from Europe to North America, though both the initiator and the node that store the item are in Europe!
Solutions: Tapestry takes care of this implicitly; CAN and Chord maintain multiple copies for each entry in their routing tables and choose the closest one in terms of network distance

28. Discussion (cont’d)
Gnutella, Napster, Fastrack can resolve powerful queries, e.g.,
Keyword searching, approximate matching
Natively, CAN, Chord, Pastry and Tapestry support only exact matching
On-going work to support more powerful queries

29. Discussion Robustness Security
Maintain multiple copies associated to each entry in the routing tables
Replicate an item on nodes with close ids in the identifier space
Security
Can be build on top of CAN, Chord, Tapestry, and Pastry

30. Conclusions
The key challenge of building wide area P2P systems is a scalable and robust location service
Solutions covered in this lecture
Naptser: centralized location service
Gnutella: broadcast-based decentralized location service
Freenet: intelligent-routing decentralized solution (but correctness not guaranteed; queries for existing items may fail)
CAN, Chord, Tapestry, Pastry: intelligent-routing decentralized solution
Guarantee correctness
Tapestry (Pastry ?) provide efficient routing, but more complex