peer-to-peer and agent-based computing

1. peer-to-peer and agent-based computing Freenet

2. Plan of lecture • Freenet Architecture • Goals and Properties • Searching a network • Searching/Routing algorithm • Adaptive behaviour • Differences from other algorithms • Keys • KSK keys • SSK keys • CHK keys • Network Evolution and Clustering • Clustering keys peer-to-peer and agent-based computing

3. Freenet • A decentralised system for storing/retrieving files within a massively distributed network • Each participant provides some network storage space • Peers are servents, providing/requesting storage • Different philosophy from Gnutella (no write permission in Gnutella) • A storage and retrieval facility • Clients add a file to the network but do not know the actual storage location • Information is kept private by employing various levels of encryption as the data traverses through the network • Adapts itself according to usage patterns peer-to-peer and agent-based computing

4. Freenet: Origins Architect/inventor: Ian Clark • Founded companies to commercialise Freenet technology • Raised US$4M venture capital • Top 100 innovators under the age of 35 by the MIT Technology Review magazine (Oct 2003) • Holds a degree in Artificial Intelligence and Computer Science from Edinburgh University, Scotland http://en.wikipedia.org/wiki/Ian_Clarke_(computer_scientist) peer-to-peer and agent-based computing

5. Why Freenet? • Designed to provide extensive protection from hostile attack • Both from inside and outside by addressing information privacy and survivability issues • Based around the P2P environment, which is inherently unreliable and untrustworthy • Assumes that all participants in the network could potentially be malicious or their peer could fail without warning • Implements a self-organising routing mechanism over a decentralised structure • This algorithm dynamically creates a centralised/decentralised network peer-to-peer and agent-based computing

6. Why Freenet? (Cont’d) • The network learns • It route queries in a better fashion from local (not global!) knowledge • Achieves this by using file keys and sub-dividing the key space to partition the location of the stored files across the network Good example of how various technologies can be used in an innovative system. • It supports: • P2P • Security (and privacy) • Scalability • Decentralised networks peer-to-peer and agent-based computing

7. Populating the Freenet Network • File Keys • Used to route storage or retrieval requests onto the Freenet network • Constructed from the user or the file itself (more on this later) • Routing Tables • Each peer has a routing table • Stores file keys and location of key (i.e. on connected peers) – see next slide peer-to-peer and agent-based computing

8. Routing Tables 1. Create key e.g. from SSK + descriptive string P1 2. Ask next Node 3. (a) Check Local Store (b) Check routing Table and find peer with closest key P2 4. Ask next node Routing Table File Key – Peer ID (p4) File Key – Peer ID (p5) File Key – Peer ID(p3) … P3 P4 P5 peer-to-peer and agent-based computing

9. Searching & requesting • Searching: • Peers try to intelligently route requests • Peers ask neighbours (like Gnutella) BUT… • Peers do not forward request to all peers • Peers find the closest key to the one supplied in their local routing table and pass the request only to this peer • Intelligent routing (subdividing keyspace) • At each hop keys are compared and request is passed to the closest matching peer • And so on… peer-to-peer and agent-based computing

10. Example key mapping X/2-X 0-X/2 X-Y 0-X Y-N peer-to-peer and agent-based computing

11. F A 1. A initiates request and asks B if it has file 2. B doesn’t so it asks best-bet peer = F 12. B sends file back to A 3. F doesn’t either and no more nodes to ask so returns “request failed” message B 7. B now detects that it has seen this request before so returns a “request failed” message 4. B tries its second choice D E File is Here! 11. File sent to B 9. D now tries its second choice E 6. Nor C so forwards request to B 10. Success!! E then returns file back to D who propagates it back to A 5. D doesn’t have it so forwards request to C C D 8. C forwards “request failed back to D peer-to-peer and agent-based computing – wamberto vasconcelos

12. Updating routing tables • If a peer forwards the request to a peer that can retrieve the data • Then address of upstream peer (which contains or is closer to the data) is included in reply • This peer uses this information to update its local routing table to include the peer that has a more direct route to the data • Then, when a similar request is issued again the peer can more effectively send the request to a node that is closer to the data peer-to-peer and agent-based computing

13. Adaptive behaviour • Dynamic algorithm to update information is analogous to the way humans reinforce decisions based on past experiences • The Milgram experiment: • Milgram noted that 25% of all requests went through the same person (the local shopkeeper) • People in this experiment used their experience of the local inhabitants to attempt to forward the letter to the best person who could help it reach its destination. peer-to-peer and agent-based computing

14. Adaptive behaviour (Cont’d) • Local shopkeeper was a good choice: • He knew a number of out-of-town people • Therefore could help the letter get closer to its destination • If experiment repeated using the same people • Surely the word would spread quickly in Omaha: shopkeeper is a good place to forward letters to • Success rate and efficiency would improve • People in Omaha would learn to route better! • This is what Freenet does: • Adapts routing tables based on prior experiences peer-to-peer and agent-based computing

15. Similarities with other techniques • Gnutella: • User searches the network by broadcasting her request to every node within a given TTL • Not efficient • Napster: • Uses central database that contains locations of all files in network • Not scalable • Subject to attack due to centralisation of its file indexing • However, both matured into using multiple caching servers in order to be able to scale the network • Resulting in a centralised/decentralised topology peer-to-peer and agent-based computing

16. But the Freenet approach… • Caching services (super peers or Napster indexes) are building blocks of Freenet • Each peer contains a routing table • Key difference • Freenet peers do not store locations of files • Instead, they contain file keys that indicate the direction in key space where file is likely to be • File keys used to route the query to the stored file • But there are many different types of keys… peer-to-peer and agent-based computing

17. Keys Three types of keys: • Keyword-Signed Keys (KSK) • The simplest of Freenet keys • Derived directly from a descriptive string that the user chooses for the file • Signed-Subspace Keys (SSK) • Used to create a subspace • To define ownership OR • To make pointers to a file or a collection of files • Content-Hash Keys (CHK) • Used for low-level data storage • Obtained by hashing the contents of the data to be stored peer-to-peer and agent-based computing

18. i.e. string always creates the same key Keyword-Signed Keys (KSKs) Descriptive String Deterministically Generate Public Key Private Key Digitally Sign Hash Keyword Signed Keys (KSK) Derived from short file description File KSK peer-to-peer and agent-based computing

19. KSKs (Cont’d) • Key Generation: • Derived from a descriptive string in a deterministic manner • Therefore same key pair gets created for the same key • If we change the string then a new key gets generated and therefore a new file gets created • If we create the same key, then the old file gets overwritten • Ownership: • None – file owned only by descriptive string peer-to-peer and agent-based computing

20. Signed Subspace Keys (SSKs) Signed Subspace Private Key Public Key Description Sign Hash Hash XOR File Hash Signed Subspace Keys (SSK) peer-to-peer and agent-based computing

21. SSKs (Cont’d) • Key Generation: • Derived from subspace key pair + description • Unique within this sub-domain (i.e. the key subspace) • Ownership: • Creates a read-only file system for all users • Only owners of the subspace can overwrite the files within the subspace • i.e. they need private subspace key to generate the correct signature peer-to-peer and agent-based computing

22. Content Hash Keys (CHKs) File to Store SHA-1 Secure Hashing Content Hash Key (CHK) File GUID (Direct reference to file contents; used for comparisons) peer-to-peer and agent-based computing – wamberto vasconcelos 22

23. CHKs (Cont’d) • Key Generation: • derived directly from the contents of the file • Ownership: • None – normally associated with a subspace to define ownership peer-to-peer and agent-based computing

24. Analogies for keys Three types of keys: • Keyword-Signed Keys (KSK): • Like filenames on a file system • Analogous to having all files in one directory • Signed-Subspace Keys (SSK): • May contain collections of filenames • Analogous to using (multiple level) directories • Content-Hash Keys (CHK): • Like inodes on a file system, i.e. a pointer to the file on disk peer-to-peer and agent-based computing

25. The use of keys • Keyword-Signed Keys (KSK) and Signed-Subspace Keys (SSK): • Used to create a user view of the file • E.g. a description or a subspace • Content-Hash Keys (CHK): • Used to verify file – for file version control, integrity, etc peer-to-peer and agent-based computing

26. Distribution of keys within key space • All keys use hash functions to create final key value • Hash functions have a good avalanche effect • Therefore input has no correlation with output • So, two very similar files will create two completely different hash keys (CHKs) • Therefore, similar files will be put in completely different parts of the network peer-to-peer and agent-based computing

27. Properties of key distribution Does this random behaviour matter? • Helps file distribution across network • Imagine experiment in which all data is quite similar (e.g. people faces, star features, etc.) • Freenet keys will create quasi-random keys from these files • This ensures even (random) distribution across all peers within the network peer-to-peer and agent-based computing

28. Summary • Example technology • Demonstrates how some of the technologies can be used in a system • E.g., security and privacy policies/techniques • Shows how centralised-decentralised models can be dynamically created • In a self-organising fashion peer-to-peer and agent-based computing

29. Further reading • Freenet web site (including downloads): http://freenetproject.org • In particular, the “philosophy” page http://freenetproject.org/philosophy.html • Freenet Wikipedia page: http://en.wikipedia.org/wiki/Freenet • Video http://video.google.com/videoplay?docid=-2894489251637986433 • MiniHowTo http://www.minihowto.org/freenet_minihowto/freenet%20a%20very%20short%20minihowto.html • Textbook chapter on Freenet http://homepages.abdn.ac.uk/w.w.vasconcelos/pages/teaching/CS4027/abdn.only/freenet.pdf peer-to-peer and agent-based computing