P2P data replication and trustworthiness for a JXTA-Overlay P2P system using fuzzy logic

Spaho, Evjola; Barolli, Leonard; Xhafa, Fatos; Biberaj, Aleksander; Shurdi, Olimpion

doi:10.1016/j.asoc.2012.08.044

Cited by 6 publications

(4 citation statements)

References 14 publications

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“…Moreover, two fuzzy‐based methods for data replication and peer trustworthiness in the P2P platform have been proposed by Spaho et al The most reliable candidates are selected via the past experiences of peers stored in the database. Each time a peer joins the P2P platform, these parameters are fuzzified by the fuzzy system, and a reliable peer is selected.…”

Section: Review Of the Selected Data Replication Mechanismsmentioning

confidence: 99%

Data replication mechanisms in the peer‐to‐peer networks

Mohammadi

Navimipour

2019

Int J Communication

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Peer-to-peer (P2P) network is a distributed network in which nodes with similar capabilities exchange information with each other. Due to the nature of the P2P network distribution, numerous network message transformation is required to exchange the data between nodes over the network, which may increase access latency. Because of the high amount of the stored data in the P2P networks, the replication of data is very important. A large amount of data is handled using data replication to increase data access, reduce access latency, and increase data availability. This issue has an important role in the P2P networks, but there is no complete and systematic research in this field. Therefore, this paper aims to provide a comprehensive study of data replication mechanisms in the P2P networks. The 1027 papers have been identified and have been reduced to 213 main studies using the paper selection process. Moreover, in this paper, the major advances are reviewed in four main groups (structured, unstructured, super-peer, and hybrid networks), and the new challenges are also highlighted. Moreover, the open issues and guidelines for future studies are presented.

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Section: Review Of the Selected Data Replication Mechanismsmentioning

confidence: 99%

Data replication mechanisms in the peer‐to‐peer networks

Mohammadi

Navimipour

2019

Int J Communication

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“…Fuzzy Logic techniques work on the premise that there are degrees of membership for entities or objects within categories, and to what extent an entity or object belongs to or deviates from a category or 'set", is extremely useful for classification tasks and if-then rules. Fuzzy Logic techniques have the capability to improve data consistency problems in data replication functions [43].…”

Section: Big Data Storage Problems and Solutions In Data Replicationmentioning

confidence: 99%

NIST Big Data Interoperability Framework:

Subgroup.¹

2019

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NIST Special Publication series 1500 is intended to capture external perspectives related to NIST standards, measurement, and testing-related efforts. These external perspectives can come from industry, academia, government, and others. These reports are intended to document external perspectives and do not represent official NIST positions. Certain commercial entities, equipment, or materials may be identified in this document to describe an experimental procedure or concept adequately. Such identification is not intended to imply recommendation or endorsement by NIST, nor is it intended to imply that the entities, materials, or equipment are necessarily the best available for the purpose. There may be references in this publication to other publications currently under development by NIST in accordance with its assigned statutory responsibilities. The information in this publication, including concepts and methodologies, may be used by Federal agencies even before the completion of such companion publications. Thus, until each publication is completed, current requirements, guidelines, and procedures, where they exist, remain operative. For planning and transition purposes, Federal agencies may wish to closely follow the development of these new publications by NIST. Organizations are encouraged to review all publications during public comment periods and provide feedback to NIST. All NIST publications are available at http://www.nist.gov/publication-portal.cfm.

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“…The storage technologies presented in this paper have built-in support to replication, which in turn ensures data availability, fault tolerance, and less data accessing delay. For efficient replication, the ABC algorithm (Taheri et al, 2013), D2RS (Sun et al, 2012), and JXTA-overlay P2P platform (Spaho et al, 2013) are the famous techniques used. HAIL (Dittrich et al, 2012) provides an indexing solution for Hadoop, which improves the data search and retrieval process.…”

Section: Analysis Of Big Data Storage Technologies Based On Brewer's mentioning

confidence: 99%

Big data storage technologies: a survey

Siddiqa

Karim

Gani

2017

Frontiers Inf Technol Electronic Eng

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Abstract:There is a great thrust in industry toward the development of more feasible and viable tools for storing fast-growing volume, velocity, and diversity of data, termed 'big data'. The structural shift of the storage mechanism from traditional data management systems to NoSQL technology is due to the intention of fulfilling big data storage requirements. However, the available big data storage technologies are inefficient to provide consistent, scalable, and available solutions for continuously growing heterogeneous data. Storage is the preliminary process of big data analytics for real-world applications such as scientific experiments, healthcare, social networks, and e-business. So far, Amazon, Google, and Apache are some of the industry standards in providing big data storage solutions, yet the literature does not report an in-depth survey of storage technologies available for big data, investigating the performance and magnitude gains of these technologies. The primary objective of this paper is to conduct a comprehensive investigation of state-of-the-art storage technologies available for big data. A well-defined taxonomy of big data storage technologies is presented to assist data analysts and researchers in understanding and selecting a storage mechanism that better fits their needs. To evaluate the performance of different storage architectures, we compare and analyze the existing approaches using Brewer's CAP theorem. The significance and applications of storage technologies and support to other categories are discussed. Several future research challenges are highlighted with the intention to expedite the deployment of a reliable and scalable storage system.

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P2P data replication and trustworthiness for a JXTA-Overlay P2P system using fuzzy logic

Cited by 6 publications

References 14 publications

Data replication mechanisms in the peer‐to‐peer networks

Data replication mechanisms in the peer‐to‐peer networks

NIST Big Data Interoperability Framework:

Big data storage technologies: a survey

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