This paper is a review on Business to Consumer (B2C) electronic commerce (e-commerce) and it studies its evolution over the last decade. The Internet characteristics that affect B2C are the Internet growth, which at first includes the number of Internet users and secondly, the infrastructure, which is basically the quality and speed of the lines. Moreover, the way the Internet growth has affected the B2C e-commerce growth over the last ten years is studied in three major countries-areas. The USA because it is an Internet developed country with vast e-commerce sales, China because it is a rapidly developing Internet country with a large number of users and fast e-commerce activity growth in the last decade and finally, the European Union, because of its diversity in Internet and e-commerce growth. This paper focuses on the aforementioned three geographic areas and extracts its conclusions from the observations of B2C behavior growth in these areas.

In this paper, our study focused on the framework of big data-driven and mobile optimization. We will study the significant points of 5G and previous mobile networks, and mostly we have a look at past mobile technologies. After that, we will focus on the future 5G Mobile Technology. We will make an essential reference to the architecture of the 5G Mobile Network. We will see the two OSI levels (network level and Internet Protocol (IP)). The purpose of IP is to ensure adequate control data (in IP header) for proper routing of IP packets belonging to specific application connections or sessions between client and server applications somewhere on the Internet. Also, we mention the primary points of 5G. The device-based architectures, the millimeter-wave, the massive multiple inputs - multiple outputs, the smarter devices, and the manual support for machine-to-machine communication.Finally, in this paper, we will see how much faster will be the future 5G mobile network and services can support. Those services, including experience at speeds of at least 1 Gbps or higher, 10 Gbps data transfer, zero secondary switches, enormous capacity, and reduce power consumption, are the areas of 5G network we see in this study.

In this paper we mention deep learning. Deep learning can be used to improve computing service provider revenue in the mobile blockchain network or to use a machine to study standard mobile detection tasks (e.g., activity recognition). Using deep neural networks can compare results with learning techniques in more common use. Also, we see the deep learning for massive amounts of data and deep learning for a wide variety of data and high-velocity data. Beyond all applications Big Data and Machine learning can be used to improve education, and its practices and procedures.

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 amount of digital data. Also, we estimate that the amount processed by "Big Data" systems will double every two years. Hence, Big Data on mobile networks need to be analyzed in-depth according to retrieve exciting and useful information. Big Data provides unprecedented opportunities for internet service providers to understand the behavior and requirements of their users, which in turn enables real-time decision making across a wide range of applications. After that, we mention the dimensions often describe the 4Vs of Big Data. We continue with the study about the use of big data analytics in mobile networks. As we see, new technologies for managing big data in a highly scalable, cost-effective, and damage-resistant manner are required. So, beyond 2020 the system capacity and data rates in mobile networks must support thousands of times more traffic than 2010 levels. Furthermore, we mention the end-to-end latency, the massive number of connections, the cost, the Quality of Experience, the Issues, and finally, the big data management. We continue with the study about the big data analytics in 5G. The 5G networks standardizing and the 5G mobile optimization are crucial areas. There are new research areas were exploring new analytics techniques in big data according to discover new patterns and extract knowledge from the data are collected. Big data analytics can provide organizations with the ability to profile and segment customers based on distinct socioeconomic characteristics and increase customer satisfaction and retention levels. Also, Big Data analytics techniques can provide telecom providers with in-depth knowledge of networks before making informed decisions. Also, as we see, these analytics techniques can help Telecommunication providers to monitor and analyze various types of data as well as event messages on networks. Important information, like business intelligence, can be extracted from momentary and stored data. Hence, the mass adoption of smartphones, mobile broadband modems, tablets, and mobile data applications has been overwhelmingly wireless. Operators bend under the pressure and cost of continuously adding capacity and improving coverage while maximizing the use of the existing components of their range. Advanced radio access technologies, and all Internet Protocols, open internet network architectures must evolve smoothly from 4G systems. So those needs are leading us to make a study about the heterogeneous network or else HetNet for 5G networks. We are continuing with the challenges, and we mention about the curse of modularity, dimensions procedure, feature engineering, non-linearity, Bonferonni's principle, category report, variance and bias, data locality, data heterogeneity, noisy data, data availability, real-time processing, and streaming, data provenance, and data security.