Grasping Popular Applications in Cellular Networks With Big Data Analytics Platforms

Fiadino, Pierdomenico; Casas, Pedro; D’Alconzo, Alessandro; Schiavone, Mirko; Baer, Arian

doi:10.1109/tnsm.2016.2558839

Cited by 10 publications

(3 citation statements)

References 51 publications

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“…With recent data mining statistical methods, the analysis of the structural data is not difficult; however, in doing so, such techniques as natural language processing (Quan et al 2019), multimedia analytics (Fiadino et al 2016), and text analytics need to be improved. It is also costly to process unstructured data for analysis as conducting a predictive analytic project (Seng and Ang 2019).…”

Section: • Structured Data Vs Unstructured Datamentioning

confidence: 99%

Big data and predictive analytics: A systematic review of applications

Jamarani,

Haddadi,

Sarvizadeh

et al. 2024

Artif Intell Rev

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Big data involves processing vast amounts of data using advanced techniques. Its potential is harnessed for predictive analytics, a sophisticated branch that anticipates unknown future events by discerning patterns observed in historical data. Various techniques obtained from modeling, data mining, statistics, artificial intelligence, and machine learning are employed to analyze available history to extract discriminative patterns for predictors. This study aims to analyze the main research approaches on Big Data Predictive Analytics (BDPA) based on very up-to-date published articles from 2014 to 2023. In this article, we fully concentrate on predictive analytics using big data mining techniques, where we perform a Systematic Literature Review (SLR) by reviewing 109 articles. Based on the application and content of current studies, we introduce taxonomy including seven major categories of industrial, e-commerce, smart healthcare, smart agriculture, smart city, Information and Communications Technologies (ICT), and weather. The benefits and weaknesses of each approach, potentially important changes, and open issues, in addition to future paths, are discussed. The compiled SLR not only extends on BDPA’s strengths, open issues, and future works but also detects the need for optimizing the insufficient metrics in big data applications, such as timeliness, accuracy, and scalability, which would enable organizations to apply big data to shift from retrospective analytics to prospective predictive if fulfilled.

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Section: • Structured Data Vs Unstructured Datamentioning

confidence: 99%

Big data and predictive analytics: A systematic review of applications

Jamarani,

Haddadi,

Sarvizadeh

et al. 2024

Artif Intell Rev

View full text Add to dashboard Cite

show abstract

“…Big data refers to data collection within a certain time range, managed and processed by conventional software tools [20] [21]. The purpose of big data analysis is to achieve better decision making, insight into the mass forces and process optimization, support a high growth, and the diversification of information assets.…”

Section: B Big Data Frameworkmentioning

confidence: 99%

Big Data Analysis-Based Secure Cluster Management for Optimized Control Plane in Software-Defined Networks

Dong

Ota

et al. 2018

IEEE Trans. Netw. Serv. Manage.

179

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In software-defined networks (SDN), the abstracted control plane is its symbolic characteristic, whose core component is the software-based controller. The control plane is logically centralized, but the controllers can be physically distributed and composed of multiple nodes. To meet the service management requirements of large-scale network scenarios, the control plane is usually implemented in the form of distributed controller clusters. Cluster management technology monitors all types of events and must maintain a consistent global network status, which usually leads to big data in SDNs. Simultaneously, the cluster security is an open issue because of the programmable and dynamic features of SDNs. To address the above challenges, this paper proposes a big data analysis-based secure cluster management architecture for the optimized control plane. A security authentication scheme is proposed for cluster management. Moreover, we propose an ant colony optimization approach that enables big data analysis scheme and the implementation system that optimizes the control plane. Simulations and comparisons show the feasibility and efficiency of the proposed scheme. The proposed scheme is significant in improving the security and efficiency SDN control plane.

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“…Dabek and Caban [11] have introduced a technique where a visualization mechanism is designed for modeling the user interaction. Fiadino et al [12] have presented a discussion towards using cellular network in the viewpoint of big data analytics. Ordonez et al [13] have introduced a technique that makes use of matrix multiplication in order to perform summarization of big data using statistical modeling.…”

Section: Introductionmentioning

confidence: 99%

A Novel Integrated Framework to Ensure Better Data Quality in Big Data Analytics over Cloud Environment

Sindhu¹,

Hegde²

2017

IJECE

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With advent of Big Data Analytics, the healthcare system is increasingly adopting the analytical services that is ultimately found to generate massive load of highly unstructured data. We reviewed the existing system to find that there are lesser number of solutions towards addressing the problems of data variety, data uncertainty, and data speed. It is important that an errorfree data should arrive in analytics. Existing system offers single-hand solution towards single platform. Therefore, we introduced an integrated framework that has the capability to address all these three problems in one execution time. Considering the synthetic big data of healthcare, we carried out the investigation to find that our proposed system using deep learning architecture offers better optimization of computational resources. The study outcome is found to offer comparatively better response time and higher accuracy rate as compared to existing optimization technqiues that is found and practiced widely in literature.

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Grasping Popular Applications in Cellular Networks With Big Data Analytics Platforms

Cited by 10 publications

References 51 publications

Big data and predictive analytics: A systematic review of applications

Big data and predictive analytics: A systematic review of applications

Big Data Analysis-Based Secure Cluster Management for Optimized Control Plane in Software-Defined Networks

A Novel Integrated Framework to Ensure Better Data Quality in Big Data Analytics over Cloud Environment

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