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Peer-to-Peer Filesystems
Tom Roeder
CS414 2005sp
Nature of P2P Systems
We discussed this a little in 415 on Friday P2P: communicating peers in the system normally an overlay in the network
In some sense, P2P is older than the name many protocols used symmetric interactions not everything is client-server
What’s the real definition? no-one has a good one, yet depends on what you want to fit in the class
Nature of P2P Systems
Standard definition symmetric interactions between peers no distinguished server
Minimally: is the Web a P2P system? We don’t want to say that it is but it is, under this definition I can always run a server if I want: no asymmtery
There must be more structure than this Let’s try again
Nature of P2P Systems
Recent definition No distinguished initial state Each server has the same code servers cooperate to handle requests clients don’t matter: servers are the P2P system
Try again: is the Web P2P? No, not under this def: servers don’t interact
Is the Google server farm P2P? Depends on how it’s set up? Probably not.
Overlays
Recall: two types of overlays Unstructured
No infrastructure set up for routing Random walks, flood search
Structured Small World Phenomenon: Kleinberg Set up enough structure to get fast routing We will see O(log n) For special tasks, can get O(1)
Overlays: Unstructured
From Gribble a common unstructured overlay look at connectivity more structure than it seems at first
Overlays: Unstructured
Gossip: state synchronization technique Instead of forced flooding, share state Do so infrequently with one neighbor at a time Original insight from epidemic theory
Convergence of state is reasonably fast with high probability for almost all nodes good probabilistic guarantees
Trivial to implement Saves bandwidth and energy consumption
Overlays: Structured
Need to build up long distance pointers think of routing within levels of a namespace eg. namespace is 10 digit numbers base 4
0112032101 then you can hop levels to find other nodes
This is the most common structure imposed
Distributed Hash Tables
One way to do this structured routing Assign each node each node an id from space eg. 128 bits: SHA-1 salted hash of IP address build up a ring: circular hashing assign nodes into this space
Value diversity of neighbors even coverage of space less chance of attack?
Distributed Hash Tables
Why “hash tables”? Stored named objects by hash code Route the object to the nearest location in space key idea: nodes and objects share id space
How do you find an object without its name? Close names don’t help because of hashing
Cost of churn? In most P2P apps, many joins and leaves
Cost of freeloaders?
Distributed Hash Tables
Dangers Sybil attacks: one node becomes many id attacks: can place your node wherever Solutions hard to come by
crytpo puzzles / money for IDs? Certification of routing and storage?
Many routing frameworks in this spirit Very popular in late 90s early 00s Pastry, Tapestry, CAN, Chord, Kademlia
Applications of DHTs
Almost anything that involves routing illegal file sharing: obvious application backup/storage filesystems P2P DNS
Good properties O(log N) hops to find an id Non-fate-sharing id neighbors Random distribution of objects to nodes
Pastry: Node state
Pastry: Node Joins
Find another geographically nearby node Hash IP address to get Pastry id Try to route a join message to this id get routing tables from each hop and dest select neighborhood set from nearby node get the leaf set from the destination Give info back to nodes so they can add you
Assuming the Pastry ring is well set up, this procedure will give good parameters
Pastry: Node Joins
Consider what happens from node 0 bootstraps itself next node to come adds itself and adds this node Neighborhood information will be bad for a while
need a good way to discover network proximity This is a current research problem
On node leaves, do the reverse If a node leaves suddenly, must be detected removal from tables by detecting node
Pastry: Routing
The key idea: grow common prefix given an object id, try to send to a node with at
least one more digit in common if not possible, send to a node that is closer
numerically if not possible, then you are the destination
Gives O(log N) hops Each step gets closer to destination Guaranteed to converge
Pastry: Routing
PAST: Pastry Filesystem
Now a simple filesystem follows: to get a file, hash its name and look up in Pastry to store a file, store it Pastry
Punt on metadata/discovery Can implement directories as files Then just need to know the name of root
Shown to give reasonable utilization of storage space
PAST: File Replication
Since any one node might fail, replicate Uses the neighbor set for k-way storage Keeps the same file at each neighbor Diversity of neighbors helps fate-sharing
Certification Each node signs a certificate
Says that it stored the file Client will retry storage if not enough certificates
OK guarantees
PAST: Tradeoffs
No explicit FS structure: Could build any sort of system by storing files Basically variable-sized block storage mechanism This buys simplicity at the cost of optimization
Speed vs. storage See Beehive for this tradeoff Makes it an explicit formula; can be tuned
Ease of use vs. security Hashes make file discovery non-transparent
Rationale and Validation
Backing up on other systems no fate sharing automatic backup by storing the file
But Cost much higher than regular filesystem Incentives: why should I store your files? How is this better than tape backup? How is this affected by churn/freeloaders Will anyone ever use it?
PAST: comparsion to CFS
CFS: a filesystem built on Chord/DHash Pastry is MSR, Chord/DHash is MIT Very similar routing and storage
PAST: comparison to CFS
PAST stores files, CFS blocks Thus CFS can use more fine-grained space lookup could be much longer
get each block: must go through routing for each CFS claims: ftp-like speed
Could imagine much faster: get blocks in parallel thus routing is slowing them down Remember: hops here are overlay, not internet, hops
Load balancing in CFS predictable storage requirements per file per node
References
A. Rowstron and P. Druschel, "Pastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems". IFIP/ACM International Conference on Distributed Systems Platforms (Middleware), Heidelberg, Germany, pages 329-350, November, 2001.
A. Rowstron and P. Druschel, "Storage management and caching in PAST, a large-scale, persistent peer-to-peer storage utility", ACM Symposium on Operating Systems Principles (SOSP'01), Banff, Canada, October 2001.
Ion Stoica, Robert Morris, David Karger, M. Frans Kaashoek, and Hari Balakrishnan, Chord: A Scalable Peer-to-peer Lookup Service for Internet Applications, ACM SIGCOMM 2001, San Deigo, CA, August 2001, pp. 149-160.
References
Frank Dabek, M. Frans Kaashoek, David Karger, Robert Morris, and Ion Stoica, Wide-area cooperative storage with CFS, ACM SOSP 2001, Banff, October 2001.
Stefan Saroiu, P. Krishna Gummadi, and Steven D. Gribble. A Measurement Study of Peer-to-Peer File Sharing Systems, Proceedings of Multimedia Computing and Networking 2002 (MMCN'02), San Jose, CA, January 2002.Kleinberg
C. G. Plaxton, R. Rajaraman, and A. W. Richa. Accessing nearby copies of replicated objects in a distributed environment. In Proceedings of the 9th Annual ACM Symposium on Parallel Algorithms and Architectures, Newport, Rhode Island, pages 311-320, June 1997.
Conclusions
Tradeoffs are critical Why are you using it? What sort of security/anonymity guarantees?
DHT applications Think of a good one and become famous
PAST caches whole files Save some routing overhead Harder to implement true filesystem