Classes of Decentralized Peer-to-Peer Networks

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Decentralized Peer-to-Peer (P2P) overlay networks are distributed systems in nature, without any hierarchical organization or centralized control. They are typically divided in two main classes: structured and unstructured [39].
Structured P2P overlay network have tightly controlled topologies and content is placed at specified locations to efficiently solve queries. Some well-known examples are Content Addressable Network (CAN) [44], Chord [15] and Pastry [45]. Such overlays use a Distributed Hash Table (DHT) as substrate, where data objects (or values) are placed deterministically at the peers whose identifiers correspond to the data object’s unique key. In DHT-based systems, node identifiers are uniform-randomly assigned to the peers from a large space of identifiers. Similarly, unique identifiers, chosen from the same identifier space and called keys, are computed from data objects by means of a hash function. Keys are then mapped by the overlay network protocol to a unique live peer in the overlay network. The structured P2P overlay network support scalable storage and retrieval of {key,value} pairs. Given a key, operations like put(key,value) and get(key) can be invoked respectively to store and retrieve the data object corresponding to the key, which involves routing requests to the peer corresponding to the key. However, they only supports exact matching and are strongly affected by peer churn [31].
A Content Addressable Network [44] is designed around the idea of a virtual d-dimensional Cartesian coordinate space (i.e. d-torus), which is divided among the peers and used for assigning IDs to data resources. Each peer knows its neighbors’ IDs and IP addresses. While receiving a query, each node sends the message to a neigh...

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...ique uses the fact that nodes sharing a great amount of files tend to stay in the network for a longer time, and therefore, with querying this small portion of nodes, success rate is increased and search traffic is decreased.
To reduce the number of probed hosts and consequently reduce the overall search load, it has been proposed to replicate data on several hosts [67]. The location and the number of replica vary in different replication strategies. Thampi et al mention in [41] that there are three main site selection policies. Owner replication in which the object is replicated on the requesting node and the number of replica increases proportional to popularity of the file. Random replication in which replications are distributed randomly and the path replication in which the requested file is copied on all nodes on the path between the requesting node and source.

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