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Big Data and 
Analytics Use 
Cases for the 5G 
deployment 
We are drowning in data, but starving for 
knowledge! 
WWRF33 9/26/2014
Authors 
• Dimitris Tsaptsinos 
o Kingston University, UK 
o Squares on Blue, France 
• dtsaptsinos@kingston.ac.uk 
• Ioannis Papadopoulos 
o Squares on Blue, France 
• Arthur Dupont 
o Telecom Nancy, University of Lorraine, France 
WWRF33 9/26/2014
Proms in the park 
• 13 September 2014 
• 50000 people 
• Spent most of the time with E and GPRS unable to 
check football scores 
• Blamed my network provider, the English weather 
and Terry Wogan! 
• Not a good experience… 
WWRF33 9/26/2014
Can & How Telco 
benefit from big data 
analysis? 
And that is the question 
WWRF33 9/26/2014
YES 
WWRF33 9/26/2014
Pressure on the Network 
• 10000 times more traffic 
o Cloud computing 
o HQ streaming 
o M2M 
• Zero latency and response time 
o Real time applications 
• 100 times more devices 
o IoE 
• Up to 10 Gbps 
o For cloud computing 
• At least 1Gbps 
o For HQ streaming etc 
• Zero-second switching 
o To ensure seamless continuity of service 
• Energy consumption 
o To ensure devices’ batteries durability 
WWRF33 9/26/2014
Is this the future? 
• “Internet of things”. 
o WWWW - World Wide Wireless Web. 
WWRF33 9/26/2014
Internet of Things 
• direct device-to-device transmission and 
participation (the BitTorrent of mobile 
communication), 
• higher number and diversified devices connected 
at the same time and communicating to each 
other, 
• a pervasive network where the user is connected to 
more than just the “Provider’s network” 
• and also users could be potential cooperative 
nodes in the data transmission (BitTorrent like). 
WWRF33 9/26/2014
Understanding of 5G 
• Definitely not a linear extrapolation of 1G, 
2G, 3G, 4G... 
WWRF33 9/26/2014
Data Explosion 
• Regardless of the kind of industry we face a huge 
stream of data. 
• Data needs to be transformed to information 
• Information to be translated to new services 
We have produced more data in the past four years than in all the time after the 
Bing Bang 
WWRF33 9/26/2014
Big Data Definition 
• Not a single standard definition… 
o Big Data is data whose scale, diversity and 
complexity require new architectures, 
techniques, algorithms, and analytics to manage 
it and extract value and hidden knowledge from 
it… 
o Defined through the four dimensions 
WWRF33 9/26/2014
Sharepoint 
Text 
Forums 
Weather 
Sensor 
Location 
Financial 
records 
HR records 
Order records 
WWRF33 9/26/2014
4G/5G/BDA 
• Big Data Analytics is relevant now 
o but ever more importantly for 5G because of the nfold increase in data. 
• The same principles remain analysing 4G data but 
more challenging when it comes to the explosion of 
data with 5G. 
WWRF33 9/26/2014
Todays Model 
• Dump Pipes for service providers 
WWRF33 9/26/2014
Todays Modelling 
• Based on 
o Historical data 
o Batched data 
o Structured data 
WWRF33 9/26/2014
Tomorrows Model 
• Smart pipes 
Knowing Dimitris 
• 079345678 
• 192.168.20.45 
• Male 
• Lives in London 
• Uses Nokia 
Understanding 
Dimitris 
• Supports AEK 
• Researches 
villas in South 
France 
• Listens to 
Greek music 
Supporting 
Dimitris 
• Located half a mile 
from a music store 
that sells Greek 
music 
• Top recommended 
villas in South of 
France 
Personalise targeted products and marketing offers 
WWRF33 9/26/2014
Tomorrows Modelling 
• Based on (in addition to…) 
o Real time data 
o Unstructured data 
WWRF33 9/26/2014
BDA Benefits 
• Operational Support Systems for 5G 
o Building a suitable and flexible 5G network 
o Caching popular data 
o Smart core network 
• Business Support Systems for 5G 
o Intelligent marketing 
o Fraud intelligence 
WWRF33 9/26/2014
Building a suitable and 
flexible 5G network 
• Deploying and maintaining the network is one of 
the costliest operations for operators of cellular 
networks. 
• Antennas have to be placed in an optimal way to 
address present and future needs. 
WWRF33 9/26/2014
Challenge 
• An operator would benefit from these technologies 
only if the antennas are well placed. 
WWRF33 9/26/2014
Analysing data 
• Long-term trends 
o to determine the evolving needs for the network 
• Seasonal trends 
o to determine where and when consumptions peaks are 
expected so that node-drones are placed accordingly. 
• Short-term needs 
o in order to deploy accordingly node-drones or mobile BTS 
to absorb consumption peaks 
• Behavioural and opinion mining 
WWRF33 9/26/2014
Send the drones 
• With a Big Data Analytics solution one can predict 
how the needs in bandwidth change from one 
place to another throughout the day, week, month, 
etc. 
• Send radio access node-drones to the relevant 
locations and where antennas should be directed, 
so that consumption peaks are absorbed smoothly 
without compromising the user experience of the 
customers. 
WWRF33 9/26/2014
Caching popular data 
• With the raise of social networks, entertainment 
applications, and web sites, mobile users increasingly 
consume images and streaming content such as video 
and music. 
• Trends and recommendations cause some content 
pieces to become viral. 
• Every time a piece of content is requested, packets 
have to travel the entire network to reach the servers. 
Such data traffic often causes network congestion. 
• Predicting popular requests, and pre-caching 
information close to the end user, will reduce 
significantly backhaul traffic and peak data traffic. 
WWRF33 9/26/2014
Example 
• Imagine a tabloid newspaper revealing a shocking 
affair involving a celebrity popular among 
teenagers in the UK. 
• Big Data Analytics algorithms would identify that 
young people in big cities will increasingly request 
this particular piece of content. 
• At a given time, knowing where the majority of 
teenagers are located in the city of London, the 
newspaper’s content can be cached in specific 
BTS. 
WWRF33 9/26/2014
Extend and improve Operators BSS 
• With data from customers and from the 
network, Big Data & Analytics technologies 
can be used to cluster customers in different 
categories. 
• A specific set of services and pricing can be 
offered to each group 
o propose customised contracts for users and improve 
customer fidelity. 
WWRF33 9/26/2014
Example 
• Let’s imagine that it is hot and sunny, a customer is 
wearing a connected cloth that identifies 
dehydration then while s/he walks near an 
operator’s partner bar the operator can send a text 
message to the customer to offer him a discount on 
a drink for this specific bar. 
• Alternatively, a discount text for the restaurant near 
the office on a Friday night? 
WWRF33 9/26/2014
Survey Answers 
• The two main benefits of Big Data Analytics would 
be: 
• Maximisation of the global throughput of the 
network using a pro-active core network, with 
advanced packet priority and routing 
management, exploiting SDN technology. 
• Minimising jitter and latency using a pro-active core 
network, with advanced packet priority and routing 
management, exploiting SDN technology. 
• It seems that the use of the SDN technology is linked 
to the use of Big Data. 
WWRF33 9/26/2014
Essential Technology 
• Parallel Processing 
• Real-time processing 
• Predictive analytics – existing and new ways of 
crunching data 
o Structured and Unstructured 
• Visualisation algorithms 
• Distributed file systems 
o Hadoop 
WWRF33 9/26/2014
Research Problems 
• The research problems are related to 
o anonymisation of data, 
o processing extreme large amount of data in real time, 
o finding balance between local processing and transport of data etc. 
• From my experience 75% of our time will be taken 
by understanding our data (cleaning, reducing,…) 
and the rest for running and testing applications. 
WWRF33 9/26/2014
BDA offers an opportunity to gain a 
beUer picture of operations and 
customers, and to 
maximise profits and user satisfaction 
WWRF33 9/26/2014
WWRF33 9/26/2014

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Big Data Analytics - A use case for 5G deployment

  • 1. Big Data and Analytics Use Cases for the 5G deployment We are drowning in data, but starving for knowledge! WWRF33 9/26/2014
  • 2. Authors • Dimitris Tsaptsinos o Kingston University, UK o Squares on Blue, France • dtsaptsinos@kingston.ac.uk • Ioannis Papadopoulos o Squares on Blue, France • Arthur Dupont o Telecom Nancy, University of Lorraine, France WWRF33 9/26/2014
  • 3. Proms in the park • 13 September 2014 • 50000 people • Spent most of the time with E and GPRS unable to check football scores • Blamed my network provider, the English weather and Terry Wogan! • Not a good experience… WWRF33 9/26/2014
  • 4. Can & How Telco benefit from big data analysis? And that is the question WWRF33 9/26/2014
  • 6. Pressure on the Network • 10000 times more traffic o Cloud computing o HQ streaming o M2M • Zero latency and response time o Real time applications • 100 times more devices o IoE • Up to 10 Gbps o For cloud computing • At least 1Gbps o For HQ streaming etc • Zero-second switching o To ensure seamless continuity of service • Energy consumption o To ensure devices’ batteries durability WWRF33 9/26/2014
  • 7. Is this the future? • “Internet of things”. o WWWW - World Wide Wireless Web. WWRF33 9/26/2014
  • 8. Internet of Things • direct device-to-device transmission and participation (the BitTorrent of mobile communication), • higher number and diversified devices connected at the same time and communicating to each other, • a pervasive network where the user is connected to more than just the “Provider’s network” • and also users could be potential cooperative nodes in the data transmission (BitTorrent like). WWRF33 9/26/2014
  • 9. Understanding of 5G • Definitely not a linear extrapolation of 1G, 2G, 3G, 4G... WWRF33 9/26/2014
  • 10. Data Explosion • Regardless of the kind of industry we face a huge stream of data. • Data needs to be transformed to information • Information to be translated to new services We have produced more data in the past four years than in all the time after the Bing Bang WWRF33 9/26/2014
  • 11. Big Data Definition • Not a single standard definition… o Big Data is data whose scale, diversity and complexity require new architectures, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it… o Defined through the four dimensions WWRF33 9/26/2014
  • 12. Sharepoint Text Forums Weather Sensor Location Financial records HR records Order records WWRF33 9/26/2014
  • 13. 4G/5G/BDA • Big Data Analytics is relevant now o but ever more importantly for 5G because of the nfold increase in data. • The same principles remain analysing 4G data but more challenging when it comes to the explosion of data with 5G. WWRF33 9/26/2014
  • 14. Todays Model • Dump Pipes for service providers WWRF33 9/26/2014
  • 15. Todays Modelling • Based on o Historical data o Batched data o Structured data WWRF33 9/26/2014
  • 16. Tomorrows Model • Smart pipes Knowing Dimitris • 079345678 • 192.168.20.45 • Male • Lives in London • Uses Nokia Understanding Dimitris • Supports AEK • Researches villas in South France • Listens to Greek music Supporting Dimitris • Located half a mile from a music store that sells Greek music • Top recommended villas in South of France Personalise targeted products and marketing offers WWRF33 9/26/2014
  • 17. Tomorrows Modelling • Based on (in addition to…) o Real time data o Unstructured data WWRF33 9/26/2014
  • 18. BDA Benefits • Operational Support Systems for 5G o Building a suitable and flexible 5G network o Caching popular data o Smart core network • Business Support Systems for 5G o Intelligent marketing o Fraud intelligence WWRF33 9/26/2014
  • 19. Building a suitable and flexible 5G network • Deploying and maintaining the network is one of the costliest operations for operators of cellular networks. • Antennas have to be placed in an optimal way to address present and future needs. WWRF33 9/26/2014
  • 20. Challenge • An operator would benefit from these technologies only if the antennas are well placed. WWRF33 9/26/2014
  • 21. Analysing data • Long-term trends o to determine the evolving needs for the network • Seasonal trends o to determine where and when consumptions peaks are expected so that node-drones are placed accordingly. • Short-term needs o in order to deploy accordingly node-drones or mobile BTS to absorb consumption peaks • Behavioural and opinion mining WWRF33 9/26/2014
  • 22. Send the drones • With a Big Data Analytics solution one can predict how the needs in bandwidth change from one place to another throughout the day, week, month, etc. • Send radio access node-drones to the relevant locations and where antennas should be directed, so that consumption peaks are absorbed smoothly without compromising the user experience of the customers. WWRF33 9/26/2014
  • 23. Caching popular data • With the raise of social networks, entertainment applications, and web sites, mobile users increasingly consume images and streaming content such as video and music. • Trends and recommendations cause some content pieces to become viral. • Every time a piece of content is requested, packets have to travel the entire network to reach the servers. Such data traffic often causes network congestion. • Predicting popular requests, and pre-caching information close to the end user, will reduce significantly backhaul traffic and peak data traffic. WWRF33 9/26/2014
  • 24. Example • Imagine a tabloid newspaper revealing a shocking affair involving a celebrity popular among teenagers in the UK. • Big Data Analytics algorithms would identify that young people in big cities will increasingly request this particular piece of content. • At a given time, knowing where the majority of teenagers are located in the city of London, the newspaper’s content can be cached in specific BTS. WWRF33 9/26/2014
  • 25. Extend and improve Operators BSS • With data from customers and from the network, Big Data & Analytics technologies can be used to cluster customers in different categories. • A specific set of services and pricing can be offered to each group o propose customised contracts for users and improve customer fidelity. WWRF33 9/26/2014
  • 26. Example • Let’s imagine that it is hot and sunny, a customer is wearing a connected cloth that identifies dehydration then while s/he walks near an operator’s partner bar the operator can send a text message to the customer to offer him a discount on a drink for this specific bar. • Alternatively, a discount text for the restaurant near the office on a Friday night? WWRF33 9/26/2014
  • 27. Survey Answers • The two main benefits of Big Data Analytics would be: • Maximisation of the global throughput of the network using a pro-active core network, with advanced packet priority and routing management, exploiting SDN technology. • Minimising jitter and latency using a pro-active core network, with advanced packet priority and routing management, exploiting SDN technology. • It seems that the use of the SDN technology is linked to the use of Big Data. WWRF33 9/26/2014
  • 28. Essential Technology • Parallel Processing • Real-time processing • Predictive analytics – existing and new ways of crunching data o Structured and Unstructured • Visualisation algorithms • Distributed file systems o Hadoop WWRF33 9/26/2014
  • 29. Research Problems • The research problems are related to o anonymisation of data, o processing extreme large amount of data in real time, o finding balance between local processing and transport of data etc. • From my experience 75% of our time will be taken by understanding our data (cleaning, reducing,…) and the rest for running and testing applications. WWRF33 9/26/2014
  • 30. BDA offers an opportunity to gain a beUer picture of operations and customers, and to maximise profits and user satisfaction WWRF33 9/26/2014