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Structural Ranking

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Structured Peer-to-Peer Systems

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Abstract

Open P2P networks are subject for selfish and incorrect behavior of nodes and even intentional attacks. A maintenance protocol must preserve topology structure not only according with the rules of the efficient graph for routing, but also accounting the cooperation level of nodes. Although the actions taken by intermediate nodes in the P2P network are hidden from the source node, the latter must have some guarantees on their correctness. This problem leads to incentive mechanisms to encourage cooperation of nodes. Such mechanisms provide each node with estimates of others behavior and the node makes own decisions when it selects its actions. In Chap. 6 we consider local ranking models when a node u decides its actions for node v based solely on directly observed past behavior of v. In this chapter, we focus on structural ranking models when network topology structure essentially information for computing ranks of nodes, as it is assumed in such well-known graph-based algorithms as PageRank and EigenTrust. We study models with partial knowledge and distributed computations when each node maintains some knowledge about the global network topology. The knowledge is a topology subgraph that aggregates, in form of cycles, direct and indirect observations of past behavior of nodes.

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Authors and Affiliations

  1. Helsinki Institute for Information Technology, Aalto University, Aalto, Finland

    Dmitry Korzun

  2. Department of Computer Science, Petrozavodsk State University, Petrozavodsk, Russia

    Dmitry Korzun

  3. Centre for Wireless Communications, University of Oulu, Oulu, Finland

    Andrei Gurtov

Authors
  1. Dmitry Korzun
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  2. Andrei Gurtov
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10.4 Summary of Part III

10.4 Summary of Part III

This part has discussed some models and methods that allow a node to collect additional knowledge about the global network. The local knowledge scope can be too limited for some problems, especially in a large-scale system. On the other hand, the global knowledge approach is inappropriate since such information typically requires Θ(N 2) storage (representation of the topology graph) and subject to frequent changes due to churn and other dynamic events.

The models and methods we considered provide tradeoffs between local and global knowledge. The problem is often called the partial knowledge problem. Typically, an effective solution to this problem requires that the local knowledge extension is incremental and started from a base P2P protocol. The latter provides default amount of local knowledge per node. If a node is interested it can append its local knowledge with additional information. This extension, as previously, follows some arrangement model to embed effective composition structure into the overall system of many nodes.

As particular cases we considered the following extensions. HDHT architectures is the evolution result of hierarchical routing schemes. Extended knowledge in HDHT is structured with a layered topology structure, an excellent evidence of the generic decomposition principle to prioritize potentially available knowledge. The CR method supports a wide family of DHT routing protocols when nodes can benefit from additional look-ahead information. Local cyclic structure is a snapshot of what is happening beyond the neighbors. Diophantine routing provides the theoretical framework for P2P routing in general. The framework allows formulating particular models that compactly describe certain routes in the P2P overlay, including routes that consists of multiple paths because of multipath routing. Structural ranking is a generic method that a node can locally use for ranking other nodes based on additional information about the network topology. We considered cyclic ranking when this information is represented as a cyclic structure, similarly to the CR method.

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Korzun, D., Gurtov, A. (2013). Structural Ranking. In: Structured Peer-to-Peer Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5483-0_10

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  • DOI: https://doi.org/10.1007/978-1-4614-5483-0_10

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