Title:
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A cluster based incentive mechanism for P2P systems
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Peer-to-Peer (P2P) networking is distributed computing paradigm, in which the nodes
are self-organized and can directly exploit resources from each other without
dedicated servers. Free riders in. the Peer-to-Peer systems are the nodes that only
consume services but provide little or nothing in return. They seriously degrade the
fault-tolerance, scalability and content availability of the Peer-to-Peer systems. The
solution to this problem in Peer-to-Peer systems is to have incentive mechanisms that
aim to improve the network utility by influencing the nodes to become more
cooperative.
This thesisp roposess evend esignr equirementsf or an incentivem echanisma ccording
to the characteristics of Peer-to-Peer systems, latest distributed computing
development trends and the related implementation techniques. This thesis also
provides a classification of the existing incentive mechanisms for Peer-to-Peer
systems. For each category, the thesis, outlines their principle, provides typical
examples, applications and discusses their limitations. Bartering exchange ring based
incentive mechanism was found to have the potential of fulfilling all the proposed
design requirements. It organizes the nodes with asymmetric interests in the bartering
exchange rings, enforcing the nodes to contribute while consuming. However the
existing bartering exchanger ing formation approacheso nly rely on historical search
records which may lead to a risk of using out of date information. Moreover, these
incentive mechanismsla ck of accountability so that the self-interestedr ational nodes
can still obtain complete resources and only contribute before finishing the
consumption.
A novel cluster based incentive mechanism (CBIM) is proposed in this thesis which
enables dynamic ring formation by modifying the Query Protocol of the underlyingP2P systems. The query messages become the media that the nodes can use to publish
supply and demand information on. The nodes can then cooperate to form a cluster
through the query messages while searching. A cluster can be formed when every
node publishes same number of requests and provisions in a query message and all the
requests can be satisfied. Graph theoretically, a cluster consists of one or more
bartering exchange rings. The CBIM also uses a reputation system to alleviate the
effect of malicious behaviours. The nodes try to identify free riders by fully utilizing
their local transaction information. The identified free riding nodes are blacklisted and
thus isolated. The simulation results indicate that by applying the CBIM, the overall
request success rate of the network can be considerably improved since the rational
nodes are forced to become more cooperative and the free riding behaviours can be
identified to a certain extent
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