This document proposes applying big data analytics to improve mobile cellular networks. It presents an architectural framework that collects big data from mobile networks, including signaling data, traffic data, location data, and radio waveforms. The data is analyzed using platforms like Apache Hadoop. Analytics can optimize network operations and enhance the subscriber experience through applications like identifying coverage issues and facilitating location-based services. Open challenges remain in fully leveraging big data to advance cellular networks.

1. Big Data Analytics in
Mobile Cellular Networks
Shubham patil
TE(IT)

2. Abstract
• Mobile Cellular Network have generators & massive data.
• Big data analytics can improve the performance of mobile
cellular networks and maximize the revenue of operators.
• we present an architectural framework for applying the big data
analytics in the mobile cellular networks.
• including big signaling data, big traffic data, big location data,
big radio waveforms data, in mobile cellular networks.
• Finally, we discuss a number of open research challenges of
the big data analytics in the mobile cellular networks

3. Introduction
• Recent years tremendous advances in wireless cellular
networks.
• With data constantly accumulated in the database and
the technologies of big data analytics rapidly
developed.
• We discuss several case studies of big data analytics
in MCN, including big signaling data,big traffic data,big
location data,big radio waveforms data.
• Make full use of big data analytics to improve the
performance of mobile cellular networks.

4. • big data analytics is the study of huge amount of stored data in order to
structured, unstructured or semi-structured data.
• The big data definition given includes the 5V properties:
Volume, Variety, Velocity, Value and Veracity.
• It contains massive volume of both structured and unstructured data that is
difficult to process using traditional database and software techniques
• 90% of the data available in the world today has been created over the last
two year.
• More than 2.5 trillion bytes of information are generated every day through
our smartphones,gps devices,bank cards
• analyzing and providing meaning of gread value for companies and
government.
What is Big Data Analytics..?

5. Proposed system work

6. • In our proposed system there is a sender is mobile,which is exchange the
data over the network.
• the information get arranged in signal, traffic, waveform, location data in
cellular network
• take an information document from the mobile or the system as info and
pass it to the network
Proposed System Work

7. An Architectural Framework To Support Big Data
Analytics In Mobile Cellular Networks
DATA COLLECTION
•Big data in mobile cellular networks can be gathered from either internal or
external sources.
•Methods of Data collection can be divided into two cate-gories:
(1)Through data sources
(2)Through auxiliary tools
Mobile devices themselves are data collection tools

8. BIG DATA ANALYTICS PLATFORMS AND TOOLS:
•Apache HadoopApache Hadoop is an open-source software framework which is used for Big
data analytics platform.
•Hadoop gradually turns into a general-purpose big data operating plat-forms.
•All the features make Hadoop peculiarly adapt to processing or analyzing the
data in mobile cellular networks, such as CDRs, GPS data, web clickstream.

9. BIG DATA ANALYTICS APPLICATIONS
The applications of big data analytics in MCN can be divided into two
categories:
1) Internal business supporting applications
The internal business support-ing applications mainly include the
operational effiency, subscribers' experience, tailored marketing, etc.
2)External innovative business model development.
such as the third-party data providers for various enterprises without
infringement of subscribers' privacy.

10. Case studies of Big Data Analytics in Mobile
Cellular Networks

11. This archi-tecture mainly consists of three components:
(1)data collecting (2) data analysing (3) applications.
For example:
Celibi et al. [40] analyzed the BSSAP messages from A interface in a
Hadoop platform to identify handovers from 3G to 2G. The simulation results
show that the identi ed 3G coverage holes are consistent with the drive test
results

12. With the widespread usage of mobile Internet, the volume of traffic data increases at
an unprecedented rate.

13. The location-based big data arising from GPS sensors, WiFi, bluetooth through
mobile devices, have become precious strategic resources. These resources would
provide support for gov-ernment administration, such as public facility planning,

14. • Big data analytics will be an indispensable part of the mobile cellular
operators' consideration of network operation, and even the design of the
next-generation mobile cellular network architectures.
• We provided a broad overview of big data analytics based on radom matrix
theory.
• an architectural framework for the applications of big data analytics in
cellular networks was presented.
• we discussed some research challenges and big data analytics' prospects
for next-generation cellular networks. Future work is in progress to address
these challenges.
CONCLUSIONS AND FUTURE WORK

15. • Information-centric network function virtualization over 5G mobile
wireless networks,'' IEEE Netw., vol. 29, no. 3, pp. 68 74, May/Jun.
2015.
• Wireless network virtualization: A survey, some research issues and
challenges,'' IEEE Commun. Surveys Tuts., vol. 17, no. 1, pp. 358
380, Mar. 2015.
REFERENCES