Big Data: Analytical Solutions, Research Challenges and Trends

Abstract

The term Big Data refers to an extensive collections of digital data generating every second. Produced datasets come in structured, semi-structured, and unstructured formats throughout the world, which is difficult for the traditional database management systems to analyze. Recently, big data analytics emerges as an essential research area due to the popularity of the Internet and the advent of new Web technologies. This growing area of research represents a multidisciplinary that attracts researchers from various research fields. Interested researchers are invited to design, develop, and implement several tools, technologies, architecture, and platforms for analyzing these large volumes of data. This paper begins with a brief introduction to big data and related concepts, including the main characteristics of big data, followed by discussions of the most significant open research challenges and emerging trends. Next, we review a study of big data analytics, the advantages of using big data solutions, and the preliminary assessments required before migrating from traditional solutions. Finally, we present a review of the recent main applications to obtain a broad perspective of big data analytics.

An intelligent Hybrid‐Q Learning clustering approach and resource management within heterogeneous cluster networks based on reinforcement learning

“…IoT and 5G‐enabled systems allow for the creation of more precise screening tools, more operative actions, and devices that increase the quality of natural life. When the Internet of Things (IoT) is in a health background, 22 it's known as IoMT (Internet of Medical Things) 23 . IoMT has revolutionized the medical industry by allowing remote healthcare for social benefits and discrimination by analyzing ailments and monitoring patients using resource‐efficient approaches.…”