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PEER DISCOVERY PROTOCOL FOR JXTA

SNEHAL PATELADVISIOR: DR. HUIPING GUO

CALIFORNIA STATE UNIVERSITY LOS ANGELES1 DECEMBER 2006

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Outline

• Peer-to-Peer Architecture

• Peer-to-Peer Networks

• Related Work on Peer Discovery

• Suggested Peer Discovery Protocol

• Conclusion

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• P2P are distributed systems without any centralized control or hierarchical organization.

• Each peer is considered as a server and a client is called a servent.

• P2P networks are self-organized and self-administrative.

Peer-to-Peer Architecture

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Outline

• Peer-to-Peer Architecture

• Peer-to-Peer Networks

– Type of P2P

– Advantages and Disadvantages of P2P

– JXTA and Gnutella

• Related Work on Peer Discovery

• Suggested Peer Discovery Protocol

• Conclusion

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Types of P2P Networks

• Collaborative Computing: Combines the idle or unused CPU processing power and/or free disk space of many computer in the network

– Grid MP Platform

• Instant Messaging:

– MSN Messenger

– AOL Messenger.

• Affinity Communities: Group of P2P networks that is based around file-sharing

– Napster

– Gnutella

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Advantages of P2P

• Distributes the responsibility of providing services

• Prevents from a single point of failure

• Improves scalability

• Reduces network congestion

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Disadvantages of P2P

• Query flooding

• Scalability

• Security

• Efficient group communication

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Gnutella

• A common P2P file sharing network

• Purely a query flooding-based protocol

• Works on five different packet types:

– ping: discover hosts on network – pong: reply to ping – query: search for a file – query hit: reply to query – push: download request for firewalled servents

• Query flooding is one of the problems with Gnutella

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Gnutella

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JXTA

• Introduced by Sun Microsystems.

• JXTA is a set of open, generalized P2P protocol

specification, that allows any connected device,

from cell phone and PDAs, to desktops and

servers; to network, communicate, and collaborate

in a fully decentralized manner.

• Developed in Java and XML

• JXTA protocols are language-independent,

platform independent.

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JXTA Peer Discovery Protocol

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• Peer-to-Peer Architecture

• Peer-to-Peer Networks

• Related Work on Peer Discovery

– Decentralized and Self-Organizing

– Instant Message Relaying

• Suggested Peer Discovery Protocol

• Conclusion

Outline

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Decentralized & Self Organizing Mechanism

• Proposed by Moore and Suda.

• A discovery mechanism that structures

relationship and forwards discovery queries based

on keyword similarity, usage history, and small-

world clustering.

• The peers in the networks are considered as

agents that contain a limited number of

relationships to the other agents.

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Decentralized & Self Organizing Mechanism

• The algorithm is divided into following sections

– The definition of agents and their relationship

– How the overall network of relationship are to

be organized

– How the relationship organization is used for

discover forwarding

• This peer discovery mechanism is limited to a

small clustering.

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Instant Message Relaying Mechanism

• Proposed by Cuihong Li, Bin Yu, and Katia Sycara.

• The peer discovery mechanism is developed based on

sending messages to each other.

• The source peer sends the query to some neighbors and

promises some payment to each receiver.

• Each receiver decides the number of neighbors she

relays the message to.

• Not feasible for an anonymous message relaying process.

• Limited by the free-riding problem.

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• Peer-to-Peer Architecture

• Peer-to-Peer Networks

• Related Work on Peer Discovery

• Suggested Peer Discovery Protocol

– Semi-Centralized, Agent-based Hierarchical Model

– Caching Mechanism

– Evaluation of the Model

– Update Mechanism

– Failure Handling and Recovery

– Performance

• Conclusion

Outline

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Suggested Peer Discovery Protocol

• The thesis proposes a semi-centralized, agent-

based hierarchical tree schema for peer discovery

of JXTA.

• The main proposal of the thesis is to use edge

peers as hosts, rendezvous peers as agents, and

group the edge peers based on their network

proximity.

• This type of structure would provide better

scalability than a fully decentralized system.

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Semi-Centralized, Agent-based Model

• The components used to construct the framework

are:

– Registration Server (RS): Maintains a database

about the IP address of all the agents at

different levels of the hierarchy

– Agents: Act as a service provider to hosts.

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Determine the number of Agents and their threshold

Determine the no. of agents and their threshold

Input: N[DNS]

Output: N[A], N[G]

1. N [P] = c % * N [DNS] where c is constant; 5 < c <10

2. N [A] = p % * N [P] = p % * c% * N [DNS] where c is constant

3. N [G] = N [P] / N [A]; N [A] < N [G]

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Construction of Agent based Framework

Input: RS, Ah[i], H[j]

Output: join [H[j]; A1 [i]]

1: register [A1[i] for every i ; RS];

2: query [H[j] for any j; RS];

3: response [RS; H[j] for any j ];

4: ping [H[j] for any j; A1 [i] for every i];

minTminT

Determine the Host’s Agents and Grouping Mechanism

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Determine the Host’s Agents and Grouping Mechanism

5: ST[k] ← Record time [H[j] for any j; A1 [i] for every i ] for k = 1,2.. N

6: compute T[i] = Σ ST[k] / n for every k = 1

7: compute = min [T[i] for every i];

8: join [H[j]; A1 [i] with];

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Caching Mechanism

• A peer will ping all the agents of level 1 to

discover its closest agent and computes the

shortest time.

• A peer host will also cache the IP address and ping

times of a few agents having the shortest times.

• The main advantage is that if a host leaves the

network and tries to join again, it does not have to

go through the query and ping message process

again.

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Evaluation of the Framework

• The main contribution of this thesis is to provide a

scalable model for peer discovery, while maintaining

load balancing of the nodes and proximity feature of the

grouping mechanism.

• The model is very dynamic in nature once the

framework is constructed.

• The cost factor is involved with the maintenance of the

agents.

• The self-organization property of the P2P network is

violated; hence the model is more like a hybrid P2P

model.

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Update MechanismPeer join/leave mechanism

Input: Host, Agents at level 1Output: Join the groupfor every peer host {send_query_message (host [source] , RS [destination] )

send_response_message ( RS[source] , host [destination] )

send_ping_message ( host [source] , Agent_level_1(i) where i = 1,2,3,….[destination] )

compute sample ping times(host [source] , Agent_level_1(i) where i = 1,2,3,….[destination])

compute_average_time ( host [source] , Agent_level_1(i) where i = 1,2,3,….[destination] )

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Update Mechanism

compute min_average_time

send_join_message ( host[source] , Agent_level_1 with min_average_time [destination] )

cache the IP addresses of few agents with the minimum ping times } Input: Host, Agent, quit messageOutput: leave the group

Host sends a quit message to its agentThe agent breaks the connection with the hostThe agent updates the database

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Failure Handling and Recovery

• In a hierarchical tree structure failure handling can

be established by back up links.

• Back up links are created with agents that have

the second shortest ping time response.

• The failure detection can be done using

“KeepAlive messages”.

• The host and agents, or two agents exchange

“KeepAlive messages” to test network

connectivity.

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Performance of the Hierarchical Model

• The performance of discovery process is mainly based on

the number of routing connections.

• Fewer connections have a quick discovery process and

higher system performance.

• The average service discovery speed v can be defined as

v= r/d where r is the total number of requests

d is the total number of connections

• The complexity of the model is O(m) + O(log n) where m is

the no. of agents at level 1 and n is total no. of nodes.

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Conclusion

• The thesis proposes a semi-centralized, agent-

based hierarchical model for peer discovery of the

JXTA network.

• It would provide better efficiency and load

balancing than a fully decentralized model.

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References

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References

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[13] Napster. Available from http://www.napster.com/;[14] Ratnasamy, Sylvia, Paul Francis, Mark Handley, Richard Karp, and Scott

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[18] M. Kelaskar, V. Matossian, P. Mehra, D. Paul, and M. Parashar, "A Study of Discovery Mechanisms for Peer-to-Peer Applications". Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ

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References

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References

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[27] Massimo Paolucci, Katia Sycara, Takuya Nishimura, and Naveen Srinivasan, "Using DAML-S for P2P Discovery". Carnegie Mellon University, USA

[28] Michael Moore and Tatsuya Suda, "Adaptable Peer-to-Peer Discovery of Objects that Match Multiple Keywords". In the proceeding of the 2004 International Symposium on Applications and the Internet Workshops, 2004

[29] Tie-Yan Li, Zhi-Gang Zhao, and Si-Zhen You, "A-peer: An Agent Platform Integrating Peer-to-Peer Network". In the proceeding of the Proceedings of the 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2003

[30] Jan Sacha, Jim Dowling, Raymond Cunningham, and René Meier, "Discovery of Stable Peers in a Self-Organizing Peer-to-Peer Gradient Topology". In the proceeding of International Federation for Information Processing

[31] Naveen Srinivasan and Timothy Finin, "Enabling Peer-to-Peer SDP". University of Maryland Baltimore County, Baltimore MD 21250

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Thank you!!

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