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A TECHNICAL SEMINAR
ON
MOBILITY PREDICTION IN
TELECOM CLOUD
Presented by,
AFIYA RAJEE
S7 ECE A
Department Of Electronics and communication 1
STRUCTURE OF PRESENTATION
MOTIVATION
OVERVIEW
INTRODUCTION
MOBILITY PREDICTION IN TELECOM CLOUD
MPaaS : SYSTEM OVERVIEW
NEXT ME
RESULT
OPPURTUNITIES
CONCLUSION
2Department Of Electronics and communication
MOTIVATION
“These are the days of innovation ,one has seen how
experts of a particular domain falter in their own fields.
Just wait and watch how a semi IT ,semi telecom engineer
takes the lead in the coming times.” - Franco Bernabè
3Department Of Electronics and communication
OVERVIEW
Telecom cloud and cloud computing are two different
concepts.
The future locations of each mobile user can be
predicted .
Leveraging the telecommunication system and the
cloud computing facility user location can be predicted.
4Department Of Electronics and communication
INTRODUCTION
Convergence among mobile devices, wireless
communication, and cloud computing.
This sparked the development of location-based mobile
social services.
Here the relationship between telecom call patterns and their
mobility behaviour is investigated.
5Department Of Electronics and communication
EXISTING SYSTEMS
Department Of Electronics and communication
6
Human Community-Based Mobility
Inter-Call Mobility
Real-world mobile traces might not be available for public
access.
Different users exhibit different mobility patterns in a
loose manner.
Contd….
THEIR DRAW BACKS
PROPOSED SYSTEM
Consists of a cloud system of mobility prediction.
Contains processing mobile call logs and user traces,
call pattern recognition, and prediction modules.
It is capable of tackling symbolically represented
locations of cell towers.
7Department Of Electronics and communication
Contd….
1. Mobility prediction service
2. Telecommunication System
3. Telecommunication cloud
8Department Of Electronics and communication
Contd….
Our research is motivated by three observations :
MOBILITY PREDICTION IN TELECOM
CLOUD USING MOBILE CALLS
9Department Of Electronics and communication
10Department Of Electronics and communication
MPaaS : SYSTEM OVERVIEW
CELLULAR TRACE QUERY FROM TELECOM
SYSTEMS
11Department Of Electronics and communication
Querying each user’s cellular traces from each cell tower
Contd….
CONCEPTS OF INTER-CONTACT TIME AND INTER-
CALL-CONTACT TIME
The relationship between telecom calls and user mobility
patterns defines two kinds of events
1. Cellular call event
2. Co-cell event
For a pair of given users we introduce two concepts based
on these events
1. Inter-contact time
2. Inter-call contact time
12Department Of Electronics and communication
Contd….
13Department Of Electronics and communication
NEXT ME
How many cell towers user will go?
Which cell tower user will reach?
14Department Of Electronics and communication
Next Me consists of two sub goals:
Data pre-processing
Call pattern recognizing
Periodicity-based module
Social-based interplay module
Self-adjust learner
It consists of several components namely
15Department Of Electronics and communication
CELLULAR TRACES SHOWING UNNECESSARY
HANDOFFS AND OVERLAPPED AREA
16Department Of Electronics and communication
cells A, B, and C are mutually overlapped
Contd….
1. Data preprocessing:
To handle user mobility regularity.
2. Periodicity module:
Foretells a user location .
3. Social interplay module:
Forecasts user location .
17Department Of Electronics and communication
Contd….
4. A self-adjust learner:
It involves two steps ,top-L selection of cell towers and
prediction aggregation.
5. Call Pattern Recognition:
Identify when the social interplay-based predictor works.
Concepts of critical call patterns and critical calls have
been proposed.
18Department Of Electronics and communication
Contd….
Next Me will perform a call pattern monitoring algorithm for each
call pair, which aims to answer three questions
1) When will the call pair co-locate?
Once it gets a critical call
2) To where will the call pair co-locate?
Region of users preference
3) For how long will the pair co-locate?
Forthcoming one to six hours
19Department Of Electronics and communication
Contd….
RESULT
20Department Of Electronics and communication
OPPURTUNITES
21Department Of Electronics and communication
F
A
B
U
L
O
U
S
FLEXIBILITY
AGGREGATION
BILLING
ULTIMATE PERFORMANCE SPEEDS
LAUNCHES RICH SET OF SERVICES
OFFER SECURITY SRORAGE AND
NETWORK MANAGEMENT SERVICES
URGES ECONOMIES OF SCALE
SOPHISTICATION
CONCLUSION
Telecom call patterns are highly correlated with co-locate
patterns, and call patterns .
Next Me was proposed for predicting user location at the
cell tower level .
It is expected to deliver a public service running in the
telecom cloud.
22
Department Of Electronics and communication
THANK YOU
23Department Of Electronics and communication
THANK YOU

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Mobility prediction in telecom cloud using telecom calls.

  • 1. A TECHNICAL SEMINAR ON MOBILITY PREDICTION IN TELECOM CLOUD Presented by, AFIYA RAJEE S7 ECE A Department Of Electronics and communication 1
  • 2. STRUCTURE OF PRESENTATION MOTIVATION OVERVIEW INTRODUCTION MOBILITY PREDICTION IN TELECOM CLOUD MPaaS : SYSTEM OVERVIEW NEXT ME RESULT OPPURTUNITIES CONCLUSION 2Department Of Electronics and communication
  • 3. MOTIVATION “These are the days of innovation ,one has seen how experts of a particular domain falter in their own fields. Just wait and watch how a semi IT ,semi telecom engineer takes the lead in the coming times.” - Franco Bernabè 3Department Of Electronics and communication
  • 4. OVERVIEW Telecom cloud and cloud computing are two different concepts. The future locations of each mobile user can be predicted . Leveraging the telecommunication system and the cloud computing facility user location can be predicted. 4Department Of Electronics and communication
  • 5. INTRODUCTION Convergence among mobile devices, wireless communication, and cloud computing. This sparked the development of location-based mobile social services. Here the relationship between telecom call patterns and their mobility behaviour is investigated. 5Department Of Electronics and communication
  • 6. EXISTING SYSTEMS Department Of Electronics and communication 6 Human Community-Based Mobility Inter-Call Mobility Real-world mobile traces might not be available for public access. Different users exhibit different mobility patterns in a loose manner. Contd…. THEIR DRAW BACKS
  • 7. PROPOSED SYSTEM Consists of a cloud system of mobility prediction. Contains processing mobile call logs and user traces, call pattern recognition, and prediction modules. It is capable of tackling symbolically represented locations of cell towers. 7Department Of Electronics and communication Contd….
  • 8. 1. Mobility prediction service 2. Telecommunication System 3. Telecommunication cloud 8Department Of Electronics and communication Contd…. Our research is motivated by three observations :
  • 9. MOBILITY PREDICTION IN TELECOM CLOUD USING MOBILE CALLS 9Department Of Electronics and communication
  • 10. 10Department Of Electronics and communication MPaaS : SYSTEM OVERVIEW
  • 11. CELLULAR TRACE QUERY FROM TELECOM SYSTEMS 11Department Of Electronics and communication Querying each user’s cellular traces from each cell tower Contd….
  • 12. CONCEPTS OF INTER-CONTACT TIME AND INTER- CALL-CONTACT TIME The relationship between telecom calls and user mobility patterns defines two kinds of events 1. Cellular call event 2. Co-cell event For a pair of given users we introduce two concepts based on these events 1. Inter-contact time 2. Inter-call contact time 12Department Of Electronics and communication Contd….
  • 13. 13Department Of Electronics and communication
  • 14. NEXT ME How many cell towers user will go? Which cell tower user will reach? 14Department Of Electronics and communication Next Me consists of two sub goals: Data pre-processing Call pattern recognizing Periodicity-based module Social-based interplay module Self-adjust learner It consists of several components namely
  • 15. 15Department Of Electronics and communication
  • 16. CELLULAR TRACES SHOWING UNNECESSARY HANDOFFS AND OVERLAPPED AREA 16Department Of Electronics and communication cells A, B, and C are mutually overlapped Contd….
  • 17. 1. Data preprocessing: To handle user mobility regularity. 2. Periodicity module: Foretells a user location . 3. Social interplay module: Forecasts user location . 17Department Of Electronics and communication Contd….
  • 18. 4. A self-adjust learner: It involves two steps ,top-L selection of cell towers and prediction aggregation. 5. Call Pattern Recognition: Identify when the social interplay-based predictor works. Concepts of critical call patterns and critical calls have been proposed. 18Department Of Electronics and communication Contd….
  • 19. Next Me will perform a call pattern monitoring algorithm for each call pair, which aims to answer three questions 1) When will the call pair co-locate? Once it gets a critical call 2) To where will the call pair co-locate? Region of users preference 3) For how long will the pair co-locate? Forthcoming one to six hours 19Department Of Electronics and communication Contd….
  • 21. OPPURTUNITES 21Department Of Electronics and communication F A B U L O U S FLEXIBILITY AGGREGATION BILLING ULTIMATE PERFORMANCE SPEEDS LAUNCHES RICH SET OF SERVICES OFFER SECURITY SRORAGE AND NETWORK MANAGEMENT SERVICES URGES ECONOMIES OF SCALE SOPHISTICATION
  • 22. CONCLUSION Telecom call patterns are highly correlated with co-locate patterns, and call patterns . Next Me was proposed for predicting user location at the cell tower level . It is expected to deliver a public service running in the telecom cloud. 22 Department Of Electronics and communication
  • 23. THANK YOU 23Department Of Electronics and communication THANK YOU