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New Topology Management Algorithms for Unstructured P2P

Networks Presentation for The Second International Workshop on P2P

Systems and Applications 14.5.2007

Annemari Auvinen, research studentDepartment of Mathematical Information Technology

University of Jyväskylä, Finlandhttp://www.mit.jyu.fi/cheesefactory

With co-authors Mikko Vapa, Matthieu Weber, Niko Kotilainen and Jarkko Vuori

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Contents

• Topology Management• Algorithms:

– Node Selection– Node Removal– Overload Estimation– Overtaking

• Results

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Topology Management 1/2

• Logical (i.e. overlay) topology on top of the physical network

• In an unstructured network a node's place in the network is not pre-defined like it is in a structured network

• A node may join the network by establishing a connection to another node on the P2P network

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Topology Management 2/2

• Topology management algorithms affect the topology by making network more scalable and effective for resource discovery

• Nodes are placed so that they stay connected and find resources efficiently without using too much of their capacity for being in the network

• Network can be kept connected

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Topology Management Algorithms

• Use local information the nodes are collecting about their neighbors

• Active neighbors and history– IP address and port number– Request time and success– The amount of the resource replies the node has

got from the neighbor and (Hit value) – The amount of the resource replies the neighbor’s

neighbor has relayed to the node (Relayed hit value)

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Goodness

• Algorithms are based on the goodness of the node

• A good neighbor node provides resources to the node

• Goodness = hit value + relayed hit values

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Node Selection

• Node tries to establish connections to the neighbors which it had before leaving the network

• Node searches a node to which to establish a new connection from the history based on hit values and request information

1. Nodes with hit values and ”old” request time

2. Nodes with ”old” request time or unrequested nodes

3. Nodes without hit values and request time

4. Nodes with hit values

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Node Removal

• Selects the ”worst” neighbor • Worst neighbor is a neighbor which has the

smallest goodness value

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Overload Estimation

• Connections are established and dropped based on the amount of traffic going through the node

• Algorithm compares the calculated traffic amount to predefined traffic limit values (upper and lower limits)

• If the traffic amount is more than the upper traffic limit one neighbor is dropped by using Node Removal

• If the traffic amount is less than the lower traffic limit, node tries to add a new neighbor by using Node Selection

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Overtaking

• A node moves closer to the ”good” nodes by overtaking the current neighbor

• If neighbor has a neighbor whose proportion of neighbor’s goodness is more than the defined overtaking percent, a new connection to that node is established and current neighbor is dropped

1 23

4Hits:2

Relayed hits:19 (68%)

Relayed hits:7 (25%)

1 23

4

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Results

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Testing

• Peer-to-Peer Realm (P2PRealm) simulator• 500 nodes, normally distributed network• Three set of queries• BFS-algorithm• Upper traffic limits 100, 125, 150, .., 600

(messages/50 sent resource queries)• Lower traffic limits 20%, 40% and 60%• Overtaking 80% and without it

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Neighbor Distribution

Lower traffic limit

20% 40% 60%

Overtaking No 80% No 80% No 80%

Distribution Normally

Power law

Normally

Power law

Normally

Normally

•

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Hops 1/2

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Hops 2/2

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Balance 1/3

• The amount of changes with overtaking

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Balance 2/3

• The amount of changes without overtaking

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Balance 3/3

• without overtaking: lower traffic limits 20%, 40% and 60% the networks attained the balance

• With overtaking:– 20% balanced – 40% upper traffic limit >350– 60% upper traffic limit >325

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Conclusion

• Best combination of parameters: lower traffic limit 40%, 80% overtaking, upper traffic limit over 350 messages/50 sent messages

• Amount of changes in the network was small, topology got balance, neighbor distribution was power law and number of hops small

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References

• Auvinen A., Vapa M., Weber M., Kotilainen N., Vuori J., "Chedar: Peer-to-Peer Middleware", Proceedings of the 19th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2006), Rhodes Island, Greece, 2006.

• Kotilainen N., Vapa M., Keltanen T., Auvinen A., Vuori J., "P2PRealm - Peer-to-Peer Network Simulator", 11th International Workshop on Computer-Aided Modeling, Analysis and Design of Communication Links and Networks (CAMAD'06), IEEE Communications Society, pp. 93-99, Trento, Italy, 2006.