1,804 research outputs found
Ontology-based Search Algorithms over Large-Scale Unstructured Peer-to-Peer Networks
Peer-to-Peer(P2P) systems have emerged as a promising paradigm to structure large scale distributed systems. They provide a robust, scalable and decentralized way to share and publish data.The unstructured P2P systems have gained much popularity in recent years for their wide applicability and simplicity. However efficient resource discovery remains a fundamental challenge for unstructured P2P networks due to the lack of a network structure. To effectively harness the power of unstructured P2P systems, the challenges in distributed knowledge management and information search need to be overcome. Current attempts to solve the problems pertaining to knowledge management and search have focused on simple term based routing indices and keyword search queries. Many P2P resource discovery applications will require more complex query functionality, as users will publish semantically rich data and need efficiently content location algorithms that find target content at moderate cost. Therefore, effective knowledge and data management techniques and search tools for information retrieval are imperative and lasting.
In my dissertation, I present a suite of protocols that assist in efficient content location and knowledge management in unstructured Peer-to-Peer overlays. The basis of these schemes is their ability to learn from past peer interactions and increasing their performance with time.My work aims to provide effective and bandwidth-efficient searching and data sharing in unstructured P2P environments. A suite of algorithms which provide peers in unstructured P2P overlays with the state necessary in order to efficiently locate, disseminate and replicate objects is presented. Also, Existing approaches to federated search are adapted and new methods are developed for semantic knowledge representation, resource selection, and knowledge evolution for efficient search in dynamic and distributed P2P network environments. Furthermore,autonomous and decentralized algorithms that reorganizes an unstructured network topology into a one with desired search-enhancing properties are proposed in a network evolution model to facilitate effective and efficient semantic search in dynamic environments
Highly intensive data dissemination in complex networks
This paper presents a study on data dissemination in unstructured
Peer-to-Peer (P2P) network overlays. The absence of a structure in unstructured
overlays eases the network management, at the cost of non-optimal mechanisms to
spread messages in the network. Thus, dissemination schemes must be employed
that allow covering a large portion of the network with a high probability
(e.g.~gossip based approaches). We identify principal metrics, provide a
theoretical model and perform the assessment evaluation using a high
performance simulator that is based on a parallel and distributed architecture.
A main point of this study is that our simulation model considers
implementation technical details, such as the use of caching and Time To Live
(TTL) in message dissemination, that are usually neglected in simulations, due
to the additional overhead they cause. Outcomes confirm that these technical
details have an important influence on the performance of dissemination schemes
and that the studied schemes are quite effective to spread information in P2P
overlay networks, whatever their topology. Moreover, the practical usage of
such dissemination mechanisms requires a fine tuning of many parameters, the
choice between different network topologies and the assessment of behaviors
such as free riding. All this can be done only using efficient simulation tools
to support both the network design phase and, in some cases, at runtime
Self-Healing Protocols for Connectivity Maintenance in Unstructured Overlays
In this paper, we discuss on the use of self-organizing protocols to improve
the reliability of dynamic Peer-to-Peer (P2P) overlay networks. Two similar
approaches are studied, which are based on local knowledge of the nodes' 2nd
neighborhood. The first scheme is a simple protocol requiring interactions
among nodes and their direct neighbors. The second scheme adds a check on the
Edge Clustering Coefficient (ECC), a local measure that allows determining
edges connecting different clusters in the network. The performed simulation
assessment evaluates these protocols over uniform networks, clustered networks
and scale-free networks. Different failure modes are considered. Results
demonstrate the effectiveness of the proposal.Comment: The paper has been accepted to the journal Peer-to-Peer Networking
and Applications. The final publication is available at Springer via
http://dx.doi.org/10.1007/s12083-015-0384-
Searching in Unstructured Overlays Using Local Knowledge and Gossip
This paper analyzes a class of dissemination algorithms for the discovery of
distributed contents in Peer-to-Peer unstructured overlay networks. The
algorithms are a mix of protocols employing local knowledge of peers'
neighborhood and gossip. By tuning the gossip probability and the depth k of
the k-neighborhood of which nodes have information, we obtain different
dissemination protocols employed in literature over unstructured P2P overlays.
The provided analysis and simulation results confirm that, when properly
configured, these schemes represent a viable approach to build effective P2P
resource discovery in large-scale, dynamic distributed systems.Comment: A revised version of the paper appears in Proc. of the 5th
International Workshop on Complex Networks (CompleNet 2014) - Studies in
Computational Intelligence Series, Springer-Verlag, Bologna (Italy), March
201
On the Topology Maintenance of Dynamic P2P Overlays through Self-Healing Local Interactions
This paper deals with the use of self-organizing protocols to improve the
reliability of dynamic Peer-to-Peer (P2P) overlay networks. We present two
approaches, that employ local knowledge of the 2nd neighborhood of nodes. The
first scheme is a simple protocol requiring interactions among nodes and their
direct neighbors. The second scheme extends this approach by resorting to the
Edge Clustering Coefficient (ECC), a local measure that allows to identify
those edges that connect different clusters in an overlay. A simulation
assessment is presented, which evaluates these protocols over uniform networks,
clustered networks and scale-free networks. Different failure modes are
considered. Results demonstrate the viability of the proposal.Comment: A revised version of the paper appears in Proc. of the IFIP
Networking 2014 Conference, IEEE, Trondheim, (Norway), June 201
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