IndexIntroductionLiterature SurveyConclusionAcknowledgementsThe usage of mobile traffic network is rapidly increasing nowadays. Various techniques are used to enhance traffic management and improve performance in mobile networks. Some techniques are used for network management such as Apache Hadoop, Mapreduce, wireless network virtualization and information-centric networking. This paper is based on the investigation of big data analytics in mobile cellular networks. Factors likely include various methods to minimize network traffic and rapid growth in network performance. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get Original Essay IntroductionBig data is mass collection data sets, so it is large and complex, therefore it becomes difficult to process it with the help of traditional data processing methods or applications Big data is the main buzzword in IT industry and new personal communication technologies increase day by day. The initial requirement of big data started from big companies like Facebook, Google and YouTube etc. For the purpose of analyzing large amounts of data that are in structured or even unstructured format. Therefore, the large is needed wherever it comes to processing complex and bulky data sets. With the recent development of wireless technologies, mobile networks and mobile applications have become both generators and carriers of enormous amounts of 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 sparse data, to understand user usage patterns from multiple industries. It includes users' lifestyle habits and time can be inferred from traffic usage, covers different time periods of the day, browsing patterns and frequently visited places, or you can find out the range of activities from location log databases of residence (HLR). Infrastructure is the significant 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 large amounts of user-generated data on a daily basis, such as call records, data records, SMS, etc. 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 proposed and provides security for high traffic data. Analyzing and minimizing such huge hadoop traffic 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 efficiently and effectively, businesses are profound to achieve better customer service, improved products and services, etc. In 5G mobile wireless networks, two techniques are defined in the software which are wireless network visualization and information-centric network (ICN). End-to-end network performance can be improved through ICN techniques with the integration of 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) etransport networks. Virtualization is a crucial use of wireless sensor networks. Mobile user traffic is one sensing area that benefits from sensor virtualization. There is one way the Internet infrastructure can evolve and that is information-centric networking, but it can move away from the host-centric paradigm based on perpetual connectivity and the end-to-end principle. The critical needs are access named resources – not hosts, scalable distribution via replication and capture, good control resolution/routing, and access. The network has a native ICN capture feature so that the node can cache content passing through it for a while and deliver it to requesting users. In the network caching mechanism, it is already replicated and the probability of delivery of 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 under the agreement. For example, Operator A and Operator B contracted such that they had to share spectrum band between each other in order to have more flexible frequency scheduling and diversity gain and this led to better spectrum efficiency and network capacity. This paper shows the study on traffic network monitoring and large-scale cellular network analysis with Hadoop. Network traffic monitoring and analysis serves to optimize network resources and improve user experience. We present here a large-scale network based on Hadoop, an open source computing platform for distributed storage and distributed processing on commodity hardware. Hadoop consists of many attractive features such as distributed parallel computing, low-cost scaling capabilities, and high fault tolerance. Important Hadoop based tools are developed by Google such as mapreduce and pig. Mapreduce is a software framework used for parallel processing of large amounts 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 run. The system will be managed using the Hadoop framework. Efficiently processes 4.2 bytes of traffic data from 123 GB/sec links with high performance and low cost every day. J. Liu et al introduced the scalable management of wireless bigdata traffic and the development of bigdata-aware wireless network. Scalable wireless bigdata traffic management includes two hybrid network structure models and hybrid signal processing models. In the hybrid network structure, the wireless system can adaptively choose only local processing at the base station level or only central processing at the control unit level or parallel processing at both levels. based on the physical conditions of the channel and correlations with the data content. The hybrid signal processing model has a commercial optical link operating at a link speed of 10 Gbps for digital communication over a single optical carrier. Therefore; Under the capacity constraints of the forward transport link, the system performance is optimized. Here to improve throughput and reliability on both mobile terminals and base station of high-speed wireless services MIMO antenna technology is used extensively. In this paper, the new method based on Jaccard measurement was proposed to recognize cellular device patterns from network traffic data. This comes.