CHORD – peer to peer lookup protocol

1. CHORD – peer to peer lookup protocol Shankar Karthik Vaithianathan & Aravind Sivaraman University of Central Florida

2. Outline • History • General definition of a DHT system • Chord • Applications • Implementation • Demo/Open questions

3. History: client-server model server index table data client a client b client c client d query data transferring

4. History: peer-to-peer model (Napster) index table server data data data data query data transferring client a client b client c client d

5. History: peer-to-peer model (Gnutella) index table index table index table index table data data data data client a client b client c client d query data transferring

6. History: peer-to-peer model (DHT systems) index table index table index table index table data data data data client a client b client c client d query data transferring

7. Distributed Hash Table What is normal hashing ? Putting items into say n buckets, often solved by a static solution(e.g H(key)mod N) Problems N changes ? We must move every thing (simple solution) or could we move just (#items) / (#buckets) on an average (optimal solution) what if we do not know the number of buckets ?

8. Distributed Hash Table Consistent Hashing • Let A & B be Hashing. They send an object k to two • different buckets, say y and z, respectively. Then either • A cannot see bucket z or B cannot see bucket y. • Each bucket is a assigned a number in (0,1), and each item gets a value (0,1). You could then be in according to least distance or always round down(or up) and wrap at the edges.

9. Distributed Hash Table Consistent Hashing c’td If a new bucket is added, we therefore need to move the Contents of bucket immediately before it. If we let each bucket have m elements and (M = log n) then each bucket gets a fair share of load and on an average we move only the average contents of the bucket around. If we let each bucket have m elements and (M = log n) then each bucket gets a fair share of load and on an average we move only the average contents of the bucket around.

10. Distributed Hash Table • a new class of peer-to-peer routing infrastructures. • support a hash table-like functionality on Internet-like scale • Consider the buckets to be computers on the internet and that given a key, they should find the value(IP address) • The challenges with such a system are: • Load balancing • Scalability • dynamic nature • no critical point • deterministic.

11. Basic DHT components • an overlay space and its partition approach • a routing protocol • local routing table • next-hop decision • a base hash function • variants: proximity-aware, locality-preserving, etc.

12. Hashing Overlay space Consistent hashing data server

13. Chord [Stoica et al. Sigcomm2001] • Overlay space • - one-dimensional unidirectional key space 0 – 2m-1. • Given two m-bit identifiers x and y, d(x, y)=(y-x+2m) % 2m • - Each node is assigned a random m-bit identifier. • - Each node is responsible for all keys equal to or before its identifier until its predecessor node’s identifier in the key space.

14. Chord – routing protocol • Routing table (finger table) • - (at most) m entries. The ith entry of node n contains the pointer to the first node that succeeds n by at least 2(i-1) on the key space, 1  i  m. • Next-hop decision: • For the given target key k, find the closest finger before (to) k and forward the request to it. • Ending condition: The request terminates when k lies between the ID range of current node and its successor node. • - The routing path length is O(log n) for a n-nodes network with high probability (w.h.p.).

15. 0 Data 0 256 224 32 256 64 192 96 160 120 128 Chord – an example (m=8) Network node A Chord network with 8 nodes and 8-bit key space

16. Data 32 [2,4) [16,32) [128,256) [8,16) [64,128) [4,8) [1,2) [32,64) 64 96 160 128 224 192 Range 1 Range 2 Range 3 Range 7 Range 4 Range 8 Range 5 Range 6 Chord – routing table setup Network node Pointer 0 255 A Chord network with 8 nodes and 8-bit key space

17. Chord – a lookup for key 120

18. How to look up a key quickly ? • We need finger table

19. How to look up a key quickly ?(cont.) • finger table for node 1

20. Node 3: Am I predecessor(1) ? Node 3: Try entry 3, and find node 0 Node 3: Send lookup to node 0 Node 0: Am I predecessor(1) ? Node 0: successor(1) is node 1 return to node 3 (RPC) How to look up a key quickly ?(cont.) Predecessor(1)  successor(1) Value of key 1 ?

21. Node joins • Two challenges • Each node’s finger table is correctly filled • Each key k is stored at node successor(k) • Three operations • Initialize the predecessor and fingers of the new node n • Update the fingers and predecessors of existing nodes • Copy to n all keys for which node n has became their successor

22. Initialize the predecessor and fingers of node n • Idea: Ask an existing node for information needed Join in

23. Update the fingers and predecessors of existing nodes • Observation: when node n joins the network, n will become the ith finger of a node p when the following two conditions meet: • P proceeds n by at least 2i-1 • The ith finger of node p succeeds n • Solution: Try to find predecessor(n- 2i-1) for all 1<=i<=m; and check whether n is their ith finger, and whether n is their predecessor’s ith finger.

24. Predecessor(3) =1, no update Predecessor(6-22-1) =3, update Predecessor(6-23-1) =1, update Predecessor(1) =0, update Predecessor(3) =1, no update Predecessor(0) =3, no update Update the fingers and predecessors of existing nodes (cont.) Predecessor(6-21-1) =3, update Join in 6 6 6 6

25. Copy to n all keys for which node n has became their successor • Idea: Node n can become the successor only for keys stored by the node immediately following n Join in

26. Extended Chord protocol • Concurrent joins • Failures and replication • Beyond are project scope. [Ref. Stoica et, all sigcomm 2001]

27. Example applications: • Co-operative Mirroring • Time-shared storage • Distributed indexes • Large-Scale combinatorial search

28. Implementation Our current implementation is simulation of the Chord protocol in O(log n) steps in java. The framework can be shown as below

29. Methods Implemented

30. Conclusion Questions ? Reference : Chord: A Scalable Peer to peer Lookup Service for Internet Applications Ion Stoica , Robert Morris, David Karger, M. Frans Kaashoek, Hari Balakrishnan MIT Laboratory for Computer Science chord@lcs.mit.edu http://pdos.lcs.mit.edu/chord/

31. THANK YOU