Distributed Hash Tables

1
Distributed Hash Tables

• David Tam
• Patrick Pang

2
Presentation Outline

• What is DHT (Distributed Hash Table)?
• Why DHTs?
• Applications
• How lookup works?
• Alternatives to DHTs
• Performance Routing
• Performance Load Balancing
• Security Routing Attack
• Security Inconsistent Behaviour
• Comparison to Other Facilities
• Current Research Projects
• Conclusion

3
What is DHT?
Distributed application
data
get (key)
put(key, data)
Distributed hash table

• DHT provides the information look up service for
  P2P applications.
• Nodes uniformly distributed across key space
• Nodes form an overlay network
• Nodes maintain list of neighbours in routing
  table
• Decoupled from physical network topology

(Figure adopted from Frans Kaashoek)
4
Why DHTs?

• Why Middleware?
• Simplifies the development for large-scale
  distributed Apps
• Better security and robustness
• Simple API

• Why Do We Need DHTs?
• Simplifies the development for large-scale
  distributed Apps
• Better security and robustness
• Simple API
• Exploits P2P resources

5
Applications

• Anything that requires a hash table
• Databases, FSes, storage, archival
• Web serving, caching
• Content distribution
• Query indexing
• Naming systems
• Communication primitives
• Chat services
• Application-layer multi-casting
• Event notification services
• Publish/subscribe systems ?

6
How lookup works?
0
Example Chord Stoica et. al.
1
15
Finger Table for Node 2
2
14
3
start interval succ.
3 3,4) 5
4 4,6) 5
6 6,10) 7
10 10,2) 10
13
4
12
5
11
10
6
7
9
8
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How lookup works?
0
Example Chord
1
15
Finger Table for Node 10
2
14
3
start interval succ.
11 11,12) 12
12 12,14) 12
14 14,2) 14
2 2,10) 2
13
4
12
5
11
10
6
7
9
8
8
How lookup works?
0
Example Chord
1
15
Finger Table for Node 10
2
14
3
start interval succ.
11 11,12) 12
12 12,14) 12
14 14,2) 14
2 2,10) 2
13
4
12
5
11
10
6
7
9
8
9
How lookup works?
0
Example Chord
1
15
Finger Table for Node 14
2
14
3
start interval succ.
15 15,0) 15
0 0,2) 1
2 2,6) 2
6 6,13) 7
13
4
12
5
11
10
6
7
9
8
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How lookup works?
0
Example Chord
1
15
Finger Table for Node 14
2
14
3
start interval succ.
15 15,0) 15
0 0,2) 1
2 2,6) 2
6 6,13) 7
13
4
12
5
11
10
6
7
9
8
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How lookup works?
0
Example Chord
1
15
2
14
3
Now Node 2 can retrive information for key 0 from
Node 1.
4
12
5
11
10
6
7
9
8
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Alternatives to DHTs

• Distributed file system
• Centralized lookup
• P2P flooding queries

(Figures adopted from Frans Kaashoek)
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Performance -- Lookup

• Purpose -- to locate a target node
• Each step, try to get closer to locating target
  node
• Ask a closer neighbour
• Performance scalability tied directly to
  lookup algorithm

• 2 Aspects to Scalability
• size of routing table O(log N)
• lookup path length O(log N)

• 2 Aspects to Performance
• Path latency
• Lookup path length ( hops)

• 3 Techniques
• proximity lookup
• proximity neighbour selection
• geographic layout

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Performance -- Load Balancing

• Issues
• Hot-spots
• Content
• Lookup
• Heterogeneous nodes paths
• System flux
• Solution
• Replication is the key
• Also good for fault-tolerance
• Cache lookup answers backwards along path

15
Security Incorrect Lookup (1)

• When asked for the next hop, give a wrong
  answer

0
Finger Table for Node 2
1
15
start interval succ.
3 3,4) 5
4 4,6) 5
6 6,10) 7
10 10,2) 10
2
14
3
13
4
12
5
11
Node 2 to Node 10 Please tell me how to reach
key 0 .
10
6
7
9
8
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Security Incorrect Lookup (2)

• When asked for the next hop, give a wrong
  answer

0
Finger Table for Node 10
1
15
start interval succ.
11 11,12) 12
12 12,14) 12
14 14,2) 14
2 2,10) 2
2
14
3
13
4
12
5
11
Node 2 to Node 10 Please tell me how to reach
key 0 . Node 10 answers ask Node 14
10
6
7
9
8
17
Security Incorrect Lookup (3)

• When asked for the next hop, give a wrong
  answer

0
Finger Table for Node 14
1
15
start interval succ.
15 15,0) 15
0 0,2) 1
2 2,6) 2
6 6,13) 7
2
14
3
13
4
12
5
11
Node 2 to Node 14 Please tell me how to reach
key 0 . Node 14 answers ask Node 10
10
6
7
9
8
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Security Incorrect Lookup (4)

• Solution Sit and Morris
• Define verifiable system invariant
• Allow the querier to observe lookup progress
• Our idea how this can be implemented
• Concretely, using an integral monotonically
  decreasing quantity to implement the idea of
  progress.
• The concept of monotonically decreasing
  quantity has been used in program construction
  guaranteeing total correctness. Parnas

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Security Inconsistent Behaviour

• Inconsistent Behaviour, i.e., lie intelligibly
• Sybil attack Kaashoek

Solution 1 public key solution
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Security Inconsistent Behaviour

• Inconsistent Behaviour, i.e., lie intelligibly
• Sybil attack Kaashoek

Solution 1 public key solution Solution 2
Byzantine Protocol
Byzantine Generals Problem How to find out the
traitors among the Generals? Lamport
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Security Inconsistent Behaviour

• Inconsistent Behaviour, i.e., lie intelligibly
• Sybil attack Kaashoek

Solution 1 public key solution Solution 2
Byzantine Protocol
Byzantine Generals Problem How to find out the
traitors among the Generals? Lamport
22
Security Inconsistent Behaviour

• Inconsistent Behaviour, i.e., lie intelligibly
• Sybil attack Kaashoek

Solution 1 public key solution Solution 2
Byzantine Protocol
Byzantine Generals Problem How to find out the
traitors among the Generals? Lamport
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Comparison to Other Facilities
Facility Abstraction Easy Use/Prg Scalability Load-Balance
DHT high high high yes
Centralized Lookup medium medium low no
P2P flooding queries medium high low no
Distributed FS low medium medium no
Facility Fault-Tolerance Self-Org Admin
DHT high yes low
Centralized Lookup low no medium
P2P flooding queries depends yes low
Distributed FS medium no high
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Research Projects
Iris security fault-tolerance US
Govt Chord circular key space Pastry
circular key space Tapestry hypercube space CAN
n-dimensional key space Kelips n-dimensional
key space DDS -- middleware platform for internet
service construction -- cluster-based --
incremental scalability
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Summary

• Good middleware platform
• Exploits P2P networks
• An exciting new research area

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References

• Lamport, Leslie et. al. The Byzantine Generals
  Problem
• Sit, Emil, Morris, Robert. Security
  Considerations for Peer-to-Peer Distributed Hash
  Tables
• Kaashoek, Frans. Distributed Hash Tables
  Building large-sacle, robust distributed
  applications
• Stoica, Ion et. al. Chord A scalable
  peer-to-peer lookup service for Internet
  applications
• Parnas, D. L. Connecting Theory to Practice
  Software Engineering Programme