Table of ContentsIntroductionLiterature SurveyConclusionRecognitionThe usage of mobile traffic network is growing rapidly nowadays. Different techniques are used to boost traffic management and improve the performance of mobile networks. Some techniques are used to manage the network, such as Apache Hadoop, Mapreduce, wireless network virtualization, and information-centric networking. This article is based on the investigation of big data analysis in mobile cellular networks. Factors likely include various methods of minimizing network traffic and rapid growth in network performance. Say no to plagiarism. Get a tailor-made essay on “Why violent video games should not be banned”?Get the original essayIntroductionBig data are sets of data that are collected in mass, so they are large and complex and therefore become difficult to process on a daily basis. using traditional data processing methods or applications. Big Data is the main watchword in the IT field and new personal communication technologies are multiplying day by day. The initial requirement for Big Data came from big companies like Facebook, Google and YouTube etc. With the aim of analyzing large amounts of data in structured or even unstructured format. Therefore, volume is required wherever complex and large data sets are to be processed. With the recent development of wireless technologies, mobile networks are multiplying and mobile applications have become both generators and carriers of enormous data. In ancient times, Big Data was used for structured data, that is, data was well organized in relational databases and spreadsheets. Big data analytics has the ability to collect scattered data, to understand user usage patterns across multiple industries. It includes the user's lifestyle habits and schedules can be inferred from traffic usage covering different periods of the day, browsing patterns and frequently visited locations. or the range of activities can be discovered from personal location record (HLR) databases. Infrastructure is the important feature of big data analytics. Real-time infrastructure monitoring can be possible through big data analytics. And they can make autonomous and dynamic decisions. Service providers process a large amount of user-generated data i.e. call records, data records, SMS messages, etc. on a daily basis. Big Data helps analyze this data and can solve the most common problems my service providers face. The rapid increase in data traffic and mobile networks is handled by the hadoop framework and the Mapreduce programming model can be offered and ensure the security of high traffic data. Analyzing and minimizing such huge traffic like Hadoop framework is widely used everywhere. Literature Survey Collecting data from various sources is one of the parts of Big Data. When big data is processed and analyzed effectively and efficiently, businesses strive for better customer service and improved products and services, etc. In 5G mobile wireless networks, two techniques are defined in the software: wireless network visualization and information-centric networking (ICN). End-to-end network performance can be improvedthanks to ICN techniques integrating wireless network visualization. Visualization is the concept that allows the abstraction of physical computing resources into logical units. Physical resources in cellular networks consist of spectrum resources and infrastructure resources that include radio access networks. (RAN), core networks (CN) and transport networks. Virtualization is a crucial use of wireless sensor networks. Mobile user traffic is one of the detection areas that benefits from sensor virtualization. There is a way for Internet infrastructure to evolve, namely information-centric networking, but it can move away from the host-centric paradigm based on perpetual connectivity and end-to-end principle . The crucial needs are access to domain resources – no hosts, scalable distribution through replication and capture, good resolution/control routing and access. The network has a native ICN capture feature that allows them to cache content passing through it for a period of time and deliver it to users who request it. In the network caching mechanism, the content is already replicated and the probability of delivering this content to the user is increased. Spectrum is the most important factor in mobile communication and network radio. With spectrum sharing, part or all of the spectrum license held can be used by multiple operators based on the agreement. For example, operator A and operator B have entered into a contract such that they must share the spectrum band between them in order to benefit from more flexible frequency planning and diversity gain, which which has resulted in improved spectrum efficiency and network capacity. This paper presents the study on traffic network monitoring and analysis of large-scale cellular network with Hadoop. Network traffic monitoring and analysis aims to optimize network resources and improve user experience. Here we present a large-scale network based on Hadoop, an open source computing platform for distributed storage and distributed processing on commodity hardware. Hadoop includes many attractive features such as distributed parallel computing, low-cost scalability, and high fault tolerance. Important tools based on Hadoop are developed by Google, such as mapreduce and pig. Mapreduce is one such software framework which is used for parallel processing of large amount of data on large clusters. Pig is made up of two components: the first is the language itself called Pig Latin and the second is the runtime environment in which Pig Latin programs are executed. The system will be implemented via the Hadoop framework. It will efficiently process 4.2 bytes of traffic data from 123 GB/s links with high performance and low cost every day. J. Liu et al. introduced scalable wireless Bigdata traffic management and developed a wireless network supporting Bigdata. Scalable wireless Bigdata traffic management includes two hybrid network structures and hybrid signal processing models. In the hybrid network structure, the wireless system can adaptively choose only local processing at the base station or only central processing at the control unit or parallel processing at both levels. based on physical channel conditions and data content correlations. The hybrid signal processing model has a commercial optical link operating at a link rate of 10.