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Peer-to-peer and agent-based computing Freenet. peer-to-peer and agent-based computing 2 Plan of lecture Freenet Architecture –Goals and Properties Searching.

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Presentation on theme: "Peer-to-peer and agent-based computing Freenet. peer-to-peer and agent-based computing 2 Plan of lecture Freenet Architecture –Goals and Properties Searching."— Presentation transcript:

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

2 peer-to-peer and agent-based computing 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

3 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

4 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

5 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

6 peer-to-peer and agent-based computing 6 Why Freenet? (Contd) 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

7 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

8 peer-to-peer and agent-based computing 8 P1 P2 P4 1. Create key e.g. from SSK + descriptive string 4. Ask next node 3. (a) Check Local Store (b) Check routing Table and find peer with closest key Routing Table File Key – Peer ID (p4) File Key – Peer ID (p5) File Key – Peer ID(p3) … P3P5 2. Ask next Node Routing Tables

9 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…

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

11 peer-to-peer and agent-based computing – wamberto vasconcelos A initiates request and asks B if it has file 2. B doesnt so it asks best-bet peer = F 3. F doesnt either and no more nodes to ask so returns request failed message 4. B tries its second choice D B C F A D E File is Here! 5. D doesnt have it so forwards request to C 6. Nor C so forwards request to B 7. B now detects that it has seen this request before so returns a request failed message 8. C forwards request failed back to D 9. D now tries its second choice E 10. Success!! E then returns file back to D who propagates it back to A 11. File sent to B 12. B sends file back to A

12 peer-to-peer and agent-based computing 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

13 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.

14 peer-to-peer and agent-based computing 14 Adaptive behaviour (Contd) 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

15 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

16 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…

17 peer-to-peer and agent-based computing 17 Keys Three types of keys: 1.Keyword-Signed Keys (KSK) –The simplest of Freenet keys –Derived directly from a descriptive string that the user chooses for the file 2.Signed-Subspace Keys (SSK) –Used to create a subspace –To define ownership OR –To make pointers to a file or a collection of files 3.Content-Hash Keys (CHK) –Used for low-level data storage –Obtained by hashing the contents of the data to be stored

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

19 peer-to-peer and agent-based computing 19 KSKs (Contd) 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

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

21 peer-to-peer and agent-based computing 21 SSKs (Contd) 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

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

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

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 24

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 25

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 26

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 27

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 28

29 Further reading Freenet web site (including downloads): –In particular, the philosophy page Freenet Wikipedia page: Video MiniHowTo very%20short%20minihowto.html Textbook chapter on Freenet aching/CS4027/abdn.only/freenet.pdf peer-to-peer and agent-based computing 29

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