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Mobility prediction in telecom cloud using telecom calls.

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Mobility prediction in telecom cloud using telecom calls.

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Mobility prediction in telecom cloud using telecom calls.

  1. 1. A TECHNICAL SEMINAR ON MOBILITY PREDICTION IN TELECOM CLOUD Presented by, AFIYA RAJEE S7 ECE A Department Of Electronics and communication 1
  2. 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. 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. 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. 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. 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. 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. 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. 9. MOBILITY PREDICTION IN TELECOM CLOUD USING MOBILE CALLS 9Department Of Electronics and communication
  10. 10. 10Department Of Electronics and communication MPaaS : SYSTEM OVERVIEW
  11. 11. CELLULAR TRACE QUERY FROM TELECOM SYSTEMS 11Department Of Electronics and communication Querying each user’s cellular traces from each cell tower Contd….
  12. 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. 13. 13Department Of Electronics and communication
  14. 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. 15. 15Department Of Electronics and communication
  16. 16. CELLULAR TRACES SHOWING UNNECESSARY HANDOFFS AND OVERLAPPED AREA 16Department Of Electronics and communication cells A, B, and C are mutually overlapped Contd….
  17. 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. 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. 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….
  20. 20. RESULT 20Department Of Electronics and communication
  21. 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. 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. 23. THANK YOU 23Department Of Electronics and communication THANK YOU

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