An Ontology-Based P2P Network for Semantic Search

This article presents an ontology-based peer-to-peer network that facilitates efficient search for data in wide-area networks. Data with the same semantics are grouped together into one-dimensional semantic ring space in the upper-tier network. This is achieved by applying an ontology-based semantic clustering technique and dedicating part of node identifiers to correspond to their data semantics. In the lower-tier network, peers in each semantic cluster are organized as Chord identifier space. Thus, all the nodes in the same semantic cluster know which node is responsible for storing context data triples they are looking for, and context queries can be efficiently routed to those nodes. Through the simulation studies, the authors demonstrate the effectiveness of our proposed scheme.

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An Ontology-Based P2P Network for Semantic Search

International Journal of Grid and High Performance Computing ◽

10.4018/jghpc.2009070803 ◽

2009 ◽

Vol 1 (4) ◽

pp. 26-39 ◽

Cited By ~ 1

Author(s):

Tao Gu ◽

Daqing Zhang ◽

Hung Keng Pung

Keyword(s):

Simulation Studies ◽

One Dimensional ◽

Semantic Clustering ◽

Lower Tier ◽

Data Semantics ◽

Peer Network ◽

Context Data ◽

Semantic Cluster ◽

Peer To Peer Network ◽

Ring Space

This article presents an ontology-based peer-to-peer network that facilitates efficient search for data in widearea networks. Data with the same semantics are grouped together into one-dimensional semantic ring space in the upper-tier network. This is achieved by applying an ontology-based semantic clustering technique and dedicating part of node identifiers to correspond to their data semantics. In the lower-tier network, peers in each semantic cluster are organized as Chord identifier space. Thus, all the nodes in the same semantic cluster know which node is responsible for storing context data triples they are looking for, and context queries can be efficiently routed to those nodes. Through the simulation studies, the authors demonstrate the effectiveness of our proposed scheme.

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AToM: Active topology monitoring for the bitcoin peer-to-peer network

Peer-to-Peer Networking and Applications ◽

10.1007/s12083-021-01201-7 ◽

2021 ◽

Author(s):

Federico Franzoni ◽

Xavier Salleras ◽

Vanesa Daza

Keyword(s):

Reference Model ◽

Peer To Peer ◽

Network Protocol ◽

P2p Network ◽

Malicious Nodes ◽

The Past ◽

Side Channels ◽

Peer Network ◽

Topology Information ◽

Peer To Peer Network

AbstractOver the past decade, the Bitcoin P2P network protocol has become a reference model for all modern cryptocurrencies. While nodes in this network are known, the connections among them are kept hidden, as it is commonly believed that this helps protect from deanonymization and low-level attacks. However, adversaries can bypass this limitation by inferring connections through side channels. At the same time, the lack of topology information hinders the analysis of the network, which is essential to improve efficiency and security. In this paper, we thoroughly review network-level attacks and empirically show that topology obfuscation is not an effective countermeasure. We then argue that the benefits of an open topology potentially outweigh its risks, and propose a protocol to reliably infer and monitor connections among reachable nodes of the Bitcoin network. We formally analyze our protocol and experimentally evaluate its accuracy in both trusted and untrusted settings. Results show our system has a low impact on the network, and has precision and recall are over 90% with up to 20% of malicious nodes in the network.

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Quality Assurance for Reusable Learning Objects on a Peer-To-Peer Network

International Journal of Emerging Technologies in Learning (iJET) ◽

10.3991/ijet.v11i10.5881 ◽

2016 ◽

Vol 11 (10) ◽

pp. 4 ◽

Cited By ~ 1

Author(s):

Rajendra G. Singh ◽

Margaret A. Bernard

Keyword(s):

Subject Matter ◽

Learning Objects ◽

Peer To Peer ◽

P2p Network ◽

Subject Matter Experts ◽

Reusable Learning Objects ◽

Peer Network ◽

First Time ◽

Peer To Peer Network

In this research, improving on the quality of Reusable Learning Objects (RLOs) on a Peer-To-Peer (P2P) network is considered. The RLO was first redesigned to have a fundamentally inherent pedagogical structure, which gave it an immediate foundational level of quality in terms of opportunities related to reusability. Applying the Learning Object Review Instrument 1.5 (LORI 1.5) demonstrated that some of the elements are inherent in this new RLO design, so there was no need to constantly have such features evaluated with LORI. A modified LORI was therefore developed in order to evaluate the remaining features of the RLO. The research identified these remaining elements to produce a Review Rubric for scoring the RLO’s quality. In addition, an algorithm is given which considers one or more subject-matter experts as part of a review process. Utilizing the subject-matter experts in a P2P network involved the creation of special nodes to ensure data integrity and post-availability of the review scores for RLOs. The research concludes that the redesigned RLOs along with the corresponding Review Rubric and scoring algorithm produces a system suitable for a P2P network, where for the first time, RLOs can be shared of assured quality to promote eLearning within P2P networks.

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Organizing XML Documents on a Peer–to–Peer Network by Collaborative Clustering

Advances in Data Mining and Database Management - XML Data Mining ◽

10.4018/978-1-61350-356-0.ch018 ◽

2011 ◽

pp. 449-466

Author(s):

Francesco Gullo ◽

Giovanni Ponti ◽

Sergio Greco

Keyword(s):

Distributed Algorithm ◽

P2p Network ◽

Distributed Environment ◽

Document Collections ◽

Xml Documents ◽

Collaborative Clustering ◽

Peer Network ◽

Xml Document ◽

Peer To Peer Network ◽

Content Information

In this chapter we address the problem of clustering XML documents in a collaborative distributed environment. We developed a clustering framework for XML sources distributed on a P2P network. XML documents are modeled based on a transactional representation which uses both XML structure and content information. The clustering method employs a centroid-based partitional scheme suitably adapted to work on a P2P network. Each peer is enabled to compute a clustering solution over its local repository and to exchange the resulting cluster representatives with the other peers. The exchanged cluster representatives are hence used to compute the global clustering solution in a collaborative way. Effectiveness and efficiency of the framework were evaluated on real XML document collections varying the number of peers. Experimental results have shown significant improvements of our collaborative distributed algorithm with respect to the centralized clustering setting in terms of execution time, achieving clustering solutions that still remain accurate with a moderately low number of nodes in the network.

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Research of Key Nodes of Botnet Based on P2P

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.88-89.386 ◽

2011 ◽

Vol 88-89 ◽

pp. 386-390

Author(s):

Jian Gao ◽

Kang Feng Zheng ◽

Yi Xian Yang ◽

Xin Xin Niu

Keyword(s):

Directed Graph ◽

Undirected Graph ◽

Detection Algorithm ◽

P2p Network ◽

P2p Networks ◽

Cut Vertex ◽

Peer Network ◽

Simulation Results ◽

Peer To Peer Network ◽

Key Nodes

The paper applies the segmentation of peer-to- peer network to the defense process of P2P-based botnet, in order to cause the greatest damage on the P2P network. A lot of papers have been researching how to find the key nodes in P2P networks. To solve this problem, this paper proposes distributed detection algorithm NEI and centralized detection algorithm COR for detecting cut vertex, NEI algorithm not only apply to detect cut vertex of directed graph but also to the undirected graph. COR algorithm can reduce the additional communication. Then, this paper carries out simulation on P2P botnet, the simulation results show that the maximum damage on the botnet can be achieved by destructing key nodes.

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Topology Construction Mechanism of Behavior-Controllable Hierarchical Military Peer to Peer Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.765-767.1254 ◽

2013 ◽

Vol 765-767 ◽

pp. 1254-1258

Author(s):

Ai Xia Zhou ◽

Lian Feng Gao ◽

Jing Feng ◽

Li Yu ◽

Xue Yan Zhang

Keyword(s):

Special Needs ◽

Network Topology ◽

Peer To Peer ◽

P2p Network ◽

Topology Construction ◽

Peer Network ◽

Military Applications ◽

New Construction ◽

Peer To Peer Network

In order to meet the special needs of military applications, network users were classified according to characteristics of users and a hierarchical behavior-controllable P2P network topology construction was designed. In the new construction, different information has different circulation range and the survivability and expansion characteristics of the P2P network were made full use.

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An EnhanEigen Algorithm Trust Model in P2P Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.791-793.1105 ◽

2013 ◽

Vol 791-793 ◽

pp. 1105-1108

Author(s):

Xia Li Li ◽

Jing Jing Xiang ◽

Su Juan Zhang ◽

Xiao Hua Yang

Keyword(s):

Execution Time ◽

Trust Model ◽

P2p Network ◽

Trust Evaluation ◽

False Feedback ◽

Simulation Experiments ◽

Trust Value ◽

Malicious Attack ◽

Peer Network ◽

Peer To Peer Network

EigenTrust is a typical global trust model which presents a distributed and secure method to compute the global trust values for peer to peer network, but it cant judge the authenticity of the evaluation from the requesting service peer. To alleviate the problem, we present an improved algorithm based on EigenTrust trust model, called EnhanEigen. We use malicious percentage (mp) and feedback consistency percentage (fcp) as the new trust evaluation criterion to filter malicious peers. By changing the ways in which peers submit feedbacks and using comprehensive trust value, our trust model can distinguish false feedback to resist to malicious attack. Simulation experiments demonstrate that it has a better performance on ensuring the success rate of transactions and has the shorter algorithm execution time.

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A Hybrid P2P Network-Based Remote Treatment SaaS Cloud Computing

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.b1132.1292s319 ◽

2019 ◽

Vol 9 (2S3) ◽

pp. 575-583

Keyword(s):

Cloud Computing ◽

Cloud Services ◽

Software As A Service ◽

P2p Network ◽

Cloud Architecture ◽

It Systems ◽

Peer Network ◽

Reliable Solution ◽

Peer To Peer Network ◽

Hybrid P2p

Cloud Computing has emerged as a new model for managing and using IT systems that has become a key topic in the field. The technology consists of deporting to remote servers the treatments, storage and management of data usually performed locally in order to access it as a service. Having so many opportunities also costs a lot in terms of infrastructure. The idea is to create a Cloud without infrastructure for providing to clients services in software as a service "SaaS" form. The solution consists of using a hybrid P2P network as an infrastructure for our Cloud. Cloud services are initially offered by the Cloud but hosted and executed through P2P network peers. The realized prototype and simulation results (with PeerSim) are encouraging and prove that a distributed and dynamic Cloud architecture based on a peer-to-peer network can be a reliable solution to infrastructure issues.

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Study of Adaptive Routing Method in Peer-to-Peer Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.40-41.392 ◽

2010 ◽

Vol 40-41 ◽

pp. 392-397

Author(s):

Den Ming Fan ◽

Qi Zhu

Keyword(s):

Adaptive Routing ◽

Peer To Peer ◽

P2p Network ◽

Simulation Experiments ◽

Peer Network ◽

Routing Method ◽

Peer To Peer Network

This paper aim To analyze and discuss a Query-based Routing Method in P2P network (QRM) , In this algorithm,the node records the received query and the nodes that can answer the query very well,in these nodes, Simulation experiments demonstrate that the method can enhance the searching efficiency very well with the number of queries becoming more and more.

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