scholarly journals Real-Time Based Big Data and E-Learning: A Survey and Open Research Issues

2021 ◽  
Vol 15 (2) ◽  
pp. 225-243
Author(s):  
Wael Hadeed ◽  
Dhuha Abdullah
2017 ◽  
Vol 19 (3) ◽  
pp. 1457-1477 ◽  
Author(s):  
Shikhar Verma ◽  
Yuichi Kawamoto ◽  
Zubair Md. Fadlullah ◽  
Hiroki Nishiyama ◽  
Nei Kato

Author(s):  
Ramgopal Kashyap

A large vault of terabytes of information created every day from present-day data frameworks and digital innovations, for example, the internet of things and distributed computing. Investigation of this enormous information requires a ton of endeavors at different dimensions to separate learning for central leadership. An examination is an ebb-and-flow territory of innovative work. The fundamental goal of this paper is to investigate the potential effect of enormous information challenges, open research issues, and different instruments related to it. Subsequently, this article gives a stage to study big data at various stages. It opens another skyline for analysts to build up the arrangement in light of the difficulties, and open research issues. The article comprehended that each large information stage has its core interest. Some of this is intended for bunch handling while some are great at constant scientific. Each large information stage likewise has explicit usefulness. Unique procedures were utilized for the investigation.


2022 ◽  
pp. 1249-1274
Author(s):  
Ramgopal Kashyap

A large vault of terabytes of information created every day from present-day data frameworks and digital innovations, for example, the internet of things and distributed computing. Investigation of this enormous information requires a ton of endeavors at different dimensions to separate learning for central leadership. An examination is an ebb-and-flow territory of innovative work. The fundamental goal of this paper is to investigate the potential effect of enormous information challenges, open research issues, and different instruments related to it. Subsequently, this article gives a stage to study big data at various stages. It opens another skyline for analysts to build up the arrangement in light of the difficulties, and open research issues. The article comprehended that each large information stage has its core interest. Some of this is intended for bunch handling while some are great at constant scientific. Each large information stage likewise has explicit usefulness. Unique procedures were utilized for the investigation.


2016 ◽  
Vol 2016 ◽  
pp. 1-27 ◽  
Author(s):  
Vikas Bhandary ◽  
Amita Malik ◽  
Sanjay Kumar

With the advancement of wireless sensor networks (WSNs) and technology, applicability of WSNs as a system is touching new heights. The development of multimedia nodes has led to the creation of another intelligent distributed system, which can transfer real-time multimedia traffic, ubiquitously. Wireless multimedia sensor networks (WMSNs) are applicable in a wide range of areas including area monitoring and video surveillance. But due to unreliable error-prone communication medium and application specific quality of service (QoS) requirements, routing of real-time multimedia traffic in WMSNs poses a serious problem. The paper discusses various existing routing strategies in WMSNs, with their properties and limitations which lead to open research issues. Further, detailed classification and analytical comparison of discussed protocols are also presented.


2020 ◽  
Vol 3 (1) ◽  
pp. 54-64
Author(s):  
Nova Nurviana

Smart analytic nowadays was very popular because today big data is booming. Back several years ago, people were fascinating with statictics which surveys or cencus become a gun for describing or forecasting some issues as of decision making or planning. By migrating to big data, smart analytic is very needed to filter which data is useful and producing some worthy information.


Nowadays, a huge volume of terabytes of data is generated from digital technologies and modern information systems, namely Internet of Things and cloud computing. The extraction of knowledge for making decisions from the analysis of these massive data, leads to requires a huge effort at multiple levels. Hence, the researchers focused on Big Data Analysis (BDA) for better development. Traditional platforms and data techniques are very less efficient in Big Data (BD) context, which shows the lack of accuracy, performance, scalability and slow responsiveness. Several works are carried out to address the complex BD challenges by developing new technologies and different types of distributions. In this research work, various technologies which are developed for BD are described and the impact of open research issues, challenges and tools for processing the BD are discussed. Then, the impacts on key business performances for BD are evaluated. At last, this work presented the four major technical and managerial challenges, which provides a platform for exploring BD at numerous stages


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