(PDF) Big Data Analytics for Wireless and Wired Network Design: A Survey
(PDF) Big Data Analytics in Cloud Computing: An overview
Big Data Processing, Analysis and Applications in Mobile Cellular
(PDF) Big data and data analytics in 5G mobile networks
(PDF) Big Data Analytics and Artificial Intelligence in Next-Generation
(PDF) Optimization Big Data Real-time Analytics Using Mobile Phone Data
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Big Data Analytics in Transportation Agency Case Study
Leveraging Big Data Analytics for Enhanced Customer Experience in Telecommunications
CASE STUDIES FOR DATA ANALYTICS IN SOCIAL MEDIA || Big data analytics || 18CS71
Big Data Analytics 2022 Question Paper
Case Study: Real-Time Data Analytics Infrastructure Considerations for Real-Time AI/ML
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Mobile Big Data Analytics: Research, Practice, and Opportunities
The rapid expansion of broadband mobile networks by Telecom Operators, has introduced a versatile global infrastructure that internally generates vast amounts of spatio-temporal network-level data (e.g., User id, location, device type, etc.) At the same time, mobile app vendors have nowadays at their fingertips massive amounts of app-level data collected through implicit or explicit crowd ...
Big Data Analytics in Mobile Cellular Networks
Mobile cellular networks have become both the generators and carriers of massive data. Big data analytics can improve the performance of mobile cellular networks and maximize the revenue of operators. In this paper, we introduce a unified data model based on the random matrix theory and machine learning. Then, we present an architectural framework for applying the big data analytics in the ...
(PDF) Big Data Analytics in Mobile Cellular Networks
Big data analytics can improve the performance of mobile cellular networks and maximize the revenue of operators. In this paper, we introduce a unified data model based on the random matrix theory ...
Big data and data analytics in 5G mobile networks
Abstract. In this paper, we study the features of big data and data analytics. We see how Big Data contributes to mobile networks. We give a term in which big data generally refers to a large ...
Mobile Big Data Analytics: Research, Practice, and Opportunities
In the research of mobile network big data [1] [2][3][4], researchers believe that mobile big data contains a wealth of information to be explored, which brings new opportunities and challenges to ...
Editorial: Deep Learning for Big Data Analytics
In the context of big data, deep learning has important applications in a wide range of fields, especially, in bioinformatics and cancer classification to address the above-mentioned issues. Accordingly, the authors in the paper entitled "A Deep Neural Network Combined with Radial Basis Function for Abnormality Classification" [6], proposed ...
Big Data Processing, Analysis and Applications in Mobile Cellular Networks
The rest of this paper is structured as follows. Section 2 provides some background on mobile cellular networks and the nature of the data sets available. It also sets the basis for different approaches to anonymization. Section 3 presents a discussion of data-intensive approaches and architectures to deal with the computationally-demanding nature of detecting patterns from telecom data.
Mobile Big Data Analytics: Research, Practice, and Opportunities
This panel will explore how the academia and industry are tackling mobile big data analytic challenges and identify and debate the key challenges and opportunities, in terms of applications, queries, architectures, to which the mobile data management and mobile data mining communities should contribute to. The rapid expansion of broadband mobile networks by Telecom Operators, has introduced a ...
Mobile Big Data Based Network Intelligence
In this paper, we aspire to establish a holistic framework for mobile big data (MBD) based network intelligence. Combining the top-down and bottom-up approaches, we put in context the recent development in the mobile network architecture, resource-based management theory, MBD orchestration, and data analytics, and establish a hierarchical ...
Big Data Analytics in Mobile Cellular Networks
This paper proposes a novel mobile big data (MBD) architecture consisting of four layers, including storage layer, fusion layer, analysis layer and the application layer, and presents a data-driven user experience prediction as a case study of applying the proposed MBD architecture in wireless network. Expand. 5.
Big Data Analytics in Telecommunications: Literature Review and
Abstract. This paper focuses on facilitating state-of-the-art applications of big data analytics (BDA) architectures and infrastructures to telecommunications (telecom) industrial sector. Telecom companies are dealing with terabytes to petabytes of data on a daily basis. IoT applications in telecom are further contributing to this data deluge.
Enhancing the quality of communication of cellular networks using big
Both software-defined networking and big data have gained approval and preferences from both industry and academia. These two important realms have conventionally been addressed independently in wireless cellular networks. The discussion taken into consideration in this study was to analyze the wireless cellular technologies with the contrast of efficient and enhanced spectral densities at a ...
A survey on data analysis on large-Scale wireless networks: online
Mobile Big Data (MBD) is the large data volume generated from mobile devices that cannot be processed on a single machine [].Figure 1 outlines the layers that compose the MBD. The first layer is the Collection Layer, in which Sourcing represent the variety of mobile devices that generate data using technologies such as Wi-Fi, Global Positioning System (GPS), and cellular communication.
Deep Learning for Network Traffic Monitoring and Analysis (NTMA): A
Modern communication systems and networks, e.g., Internet of Things (IoT) and cellular networks, generate a massive and heterogeneous amount of traffic data. In such networks, the traditional network management techniques for monitoring and data analytics face some challenges and issues, e.g., accuracy, and effective processing of big data in a ...
A Review Paper on Big Data Analytics in Mobile Networks
Abstract. Mobile cellular networks have evolved into both data producers and data carriers. Big data analytics can enhance the operation of mobile cellular networks while increasing operator ...
A comprehensive and systematic literature review on the big data
The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for ...
Big Data: A Survey: Mobile Networks and Applications: Vol 19, No 2
In this paper, we review the background and state-of-the-art of big data. We first introduce the general background of big data and review related technologies, such as could computing, Internet of Things, data centers, and Hadoop. We then focus on the four phases of the value chain of big data, i.e., data generation, data acquisition, data ...
PDF A Case Study on Big Data Analytics in Mobile Cellular Networks
We aim to introduce the general background of data generated by mobile cellular networks and review certain technologies related to this. In this study we are about to discuss various analysis methods and the case studies involving mobile big data Keywords: Big Data Analytics, Mobile cellular networks, Hadoop
Behavior detection of mobile phone use at work based on big data and
Mobile Big Data Analytics: Research, Practice, and Opportunities MDM '14: Proceedings of the 2014 IEEE 15th International Conference on Mobile Data Management - Volume 01 The rapid expansion of broadband mobile networks by Telecom Operators, has introduced a versatile global infrastructure that internally generates vast amounts of spatio ...
Big data analytics for wireless and wired network design: A survey
The role of big data analytics in optical networks. This section discusses research papers that employ big data analytics for optical network design, the topics are classified as follows: 1-Network optimization: Here the parallel processing merits of Hadoop are utilized to reduce the execution time of different (bin-packing) optimization ...
Big data analytics meets social media: A systematic review of
In this paper, we demonstrate how big data analytics meets social media, and a comprehensive review is provided on big data analytic approaches in social networks to search published studies between 2013 and August 2020, with 74 identified papers. ... classify, and compare the existing research reviews on big data analytics in social networks ...
Real-Time Cybersecurity threat detection using machine learning and big
The findings suggest that integrating ML and big data analytics in real-time threat detection systems significantly improves cybersecurity defenses, providing organizations with the tools to proactively counteract cyber threats. The rapid digitization of industries and the proliferation of connected devices have exponentially increased the surface area for cyber threats, making traditional ...
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The rapid expansion of broadband mobile networks by Telecom Operators, has introduced a versatile global infrastructure that internally generates vast amounts of spatio-temporal network-level data (e.g., User id, location, device type, etc.) At the same time, mobile app vendors have nowadays at their fingertips massive amounts of app-level data collected through implicit or explicit crowd ...
Mobile cellular networks have become both the generators and carriers of massive data. Big data analytics can improve the performance of mobile cellular networks and maximize the revenue of operators. In this paper, we introduce a unified data model based on the random matrix theory and machine learning. Then, we present an architectural framework for applying the big data analytics in the ...
Big data analytics can improve the performance of mobile cellular networks and maximize the revenue of operators. In this paper, we introduce a unified data model based on the random matrix theory ...
Abstract. In this paper, we study the features of big data and data analytics. We see how Big Data contributes to mobile networks. We give a term in which big data generally refers to a large ...
In the research of mobile network big data [1] [2][3][4], researchers believe that mobile big data contains a wealth of information to be explored, which brings new opportunities and challenges to ...
In the context of big data, deep learning has important applications in a wide range of fields, especially, in bioinformatics and cancer classification to address the above-mentioned issues. Accordingly, the authors in the paper entitled "A Deep Neural Network Combined with Radial Basis Function for Abnormality Classification" [6], proposed ...
The rest of this paper is structured as follows. Section 2 provides some background on mobile cellular networks and the nature of the data sets available. It also sets the basis for different approaches to anonymization. Section 3 presents a discussion of data-intensive approaches and architectures to deal with the computationally-demanding nature of detecting patterns from telecom data.
This panel will explore how the academia and industry are tackling mobile big data analytic challenges and identify and debate the key challenges and opportunities, in terms of applications, queries, architectures, to which the mobile data management and mobile data mining communities should contribute to. The rapid expansion of broadband mobile networks by Telecom Operators, has introduced a ...
In this paper, we aspire to establish a holistic framework for mobile big data (MBD) based network intelligence. Combining the top-down and bottom-up approaches, we put in context the recent development in the mobile network architecture, resource-based management theory, MBD orchestration, and data analytics, and establish a hierarchical ...
This paper proposes a novel mobile big data (MBD) architecture consisting of four layers, including storage layer, fusion layer, analysis layer and the application layer, and presents a data-driven user experience prediction as a case study of applying the proposed MBD architecture in wireless network. Expand. 5.
Abstract. This paper focuses on facilitating state-of-the-art applications of big data analytics (BDA) architectures and infrastructures to telecommunications (telecom) industrial sector. Telecom companies are dealing with terabytes to petabytes of data on a daily basis. IoT applications in telecom are further contributing to this data deluge.
Both software-defined networking and big data have gained approval and preferences from both industry and academia. These two important realms have conventionally been addressed independently in wireless cellular networks. The discussion taken into consideration in this study was to analyze the wireless cellular technologies with the contrast of efficient and enhanced spectral densities at a ...
Mobile Big Data (MBD) is the large data volume generated from mobile devices that cannot be processed on a single machine [].Figure 1 outlines the layers that compose the MBD. The first layer is the Collection Layer, in which Sourcing represent the variety of mobile devices that generate data using technologies such as Wi-Fi, Global Positioning System (GPS), and cellular communication.
Modern communication systems and networks, e.g., Internet of Things (IoT) and cellular networks, generate a massive and heterogeneous amount of traffic data. In such networks, the traditional network management techniques for monitoring and data analytics face some challenges and issues, e.g., accuracy, and effective processing of big data in a ...
Abstract. Mobile cellular networks have evolved into both data producers and data carriers. Big data analytics can enhance the operation of mobile cellular networks while increasing operator ...
The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for ...
In this paper, we review the background and state-of-the-art of big data. We first introduce the general background of big data and review related technologies, such as could computing, Internet of Things, data centers, and Hadoop. We then focus on the four phases of the value chain of big data, i.e., data generation, data acquisition, data ...
We aim to introduce the general background of data generated by mobile cellular networks and review certain technologies related to this. In this study we are about to discuss various analysis methods and the case studies involving mobile big data Keywords: Big Data Analytics, Mobile cellular networks, Hadoop
Mobile Big Data Analytics: Research, Practice, and Opportunities MDM '14: Proceedings of the 2014 IEEE 15th International Conference on Mobile Data Management - Volume 01 The rapid expansion of broadband mobile networks by Telecom Operators, has introduced a versatile global infrastructure that internally generates vast amounts of spatio ...
The role of big data analytics in optical networks. This section discusses research papers that employ big data analytics for optical network design, the topics are classified as follows: 1-Network optimization: Here the parallel processing merits of Hadoop are utilized to reduce the execution time of different (bin-packing) optimization ...
In this paper, we demonstrate how big data analytics meets social media, and a comprehensive review is provided on big data analytic approaches in social networks to search published studies between 2013 and August 2020, with 74 identified papers. ... classify, and compare the existing research reviews on big data analytics in social networks ...
The findings suggest that integrating ML and big data analytics in real-time threat detection systems significantly improves cybersecurity defenses, providing organizations with the tools to proactively counteract cyber threats. The rapid digitization of industries and the proliferation of connected devices have exponentially increased the surface area for cyber threats, making traditional ...