1. P-Grid Presentation by Thierry Lopez P-Grid: A Self-organizing Structured P2P System Karl Aberer, Philippe Cudré-Mauroux, Anwitaman Datta, Zoran Despotovic, Manfred Hauswirth, Magdalena Punceva, Roman Schmidt, SIGMOND Record, 32(2), September 2003. Updates in Highly Unreliable, Replicated Peer-to-Peer Systems Updates in Highly Unreliable, Replicated Peer-to-Peer Systems Anwitaman Datta, Manfred Hauswirth, Karl Aberer, Proceedings of the 23rd International Conference on Distributed Computing Systems (ICDCS 2003), May 19-22, 2003, Providence, Rhode Island, USA.23rd International Conference on Distributed Computing Systems (ICDCS 2003) Scalable Data Access in P2P Systems Using Unbalanced Search Trees Scalable Data Access in P2P Systems Using Unbalanced Search Trees Karl Aberer, Workshop on Distributed Data and Structures (WDAS-2002), Paris, France, 2002. Managing Trust in a Peer-2-Peer Information System Managing Trust in a Peer-2-Peer Information System Karl Aberer, Zoran Despotovic, 10th International Conference on Information and Knowledge Management, (2001 ACM CIKM), ACM Press, New York, 2001. Advanced Peer-to-Peer Networking: The P-Grid System and its Applications Advanced Peer-to-Peer Networking: The P-Grid System and its Applications Karl Aberer, Philippe Cudré-Mauroux, Anwitaman Datta, Zoran Despotovic, Manfred Hauswirth, Magdalena Punceva, Roman Schmidt, Jie Wu, PIK 26(3), 2003.

2. Presentation Overview ● What is P-Grid? ● Grid Structure ● Search Tree ● Load Balancing ● Updating ● Security ● Trust

3. What is P-Grid ● Self-organizing structured P2P system ● Multi-use. One use file distribution ● Heavy use of probabilities and redundancy ● Each peer has a unique ID ● Look up table based on virtual distributed search tree. ● Each peer is responsible for a section of the tree. ● Goal to have each node with equal load

4. Example of the Network ● Each peer has a prefix of the network ● Files hashed to a key. Low probability of conflicts. ● Redundancy

5. Example Tree

6. Routing Algorithm ● Each peer has a routing table. – Show how routing works ● Each peer knows about its duplicates ● Each peer knows a few other peers. Less know are held. – Small world Model – Different than Chord in who is known. ● Should be O(Log(n)) routing

7. Adding a new node ● Gets a global ID from bootstrapping node – Computer holds onto this ID even offline ● Sharing of files and routing table. – Shares to many files, split index again ● Similar to CAN ● “show example” ● Updating files/routing talked about later – Method of pushing and pulling. ● Storage of routing table, O(log(n))

8. The Unbalanced Search Tree ● Goal is to be load balanced. Think CAN. – Importance is on number of messages for a search and not the depth of the tree ● A message is routed to a closer reference. ● When the correct node is found, reply sent straight back to source.

9. Load Balance ● 1024 peers, with average path length of 5.

10. Updating ● Does not need to be strongly consistent. ● Use of local knowledge. ● Uses rumor spreading by a push and pull method. ● Push when new files added or updates. – Controlled flooding. Select x random prefix peers, send the update, those peers might re- flood. ● Pulling: When logging back on: – Query a few prefix peers for routing tables and file handles. Ask multiple peers for protection.

11. Updating Cont. ● Basic Idea: Each prefix group is a mini P2P group with no internal structure. ● Each member knows a “minimal fraction of the complete set of replicas.” ● P-Grid to have a higher replication factor than normally assumed. – Replicate between 100 and 1000 times. – Based on staticitics of real information, on average 200-250 replicas exist. ● This is scalable since if to many peers join a prefix it breaks to be smaller.

12. Trust ● The use of a binary reputation system. – Meaning, good node or bad node. ● Complaints are only stored. – Stored via the distrusted method of P-Grid. ● Interactions between peers p & q. – Example of q cheating and giving bad reviews. – Look at all the reviews/witnesses and judge yourself.

13. Example of a Trust Tree

14. Details on Trust ● What if complaints stored on malicious host? – Replication of that data == voting system. ● Lying witnesses: Randomly check the trust of the witnesses or check if results are mixed. ● Stopping requests. – Use a different route by the routing table.