COMPLEX EVENT PROCESSING APPROACH ON SUBSCRIBERS’ DATA OF TELECOM OPERATOR

Nowadays, the usage of mobile phones reached extremely large worldwide proportions and increasing dramatically, there is a stronger need to decrypt the important information that is hidden among them. Even all needed information is gained, the processes of companies remain static and can’t be changed dynamically to adapt to actual business needs, reducing the advantages that can be achieved. Every second, millions of raw information are generating by mobile users, which are handled by Telecom operators in data servers. By using the Complex Event Processing (CEP) approach in real-time, we can obtain the information that matters to our business and use it to monetize the vast amount of data that is being collected through mobile phone usage. In this paper, we present an internally developed framework that combines the strengths of CEP and business process implementations, which allows us to react to the needs of today’s fast-changing environment and requirements. We demonstrate 3 simple use case scenarios to show the effectiveness of the CEP approach in our situation. The importance of implementing the CEP approach on subscribers’ data should not be overlooked as means of trying to capitalize on new services but have to be considered as a challenge to allow subscribers get more customized offers and services.

1. https://datareportal.com/reports/digital-2019-global-digital-overview .

2. Digital 2019: Global digital overview.

3. Using Complex Event Processing for Dynamic Business Process Adaptation.

4. Gabriel Hermosillo, Lionel Seinturier, Laurence Duchien. 2010 IEEE International Conference on Services Computing.

5. Processing Flows of Information: From Data Stream to Complex Event Processing.

6. Alessandro Margara, Gianpaolo Cugola

7. SoLoMo analytics for telco Big Data monetization.

8. H. Cao, W. S. Dong L, S. Liu, C. Y. Ma, W. H. Qian, J. W. Shi, C. H. Tian, Y. Wang, D. Konopnicki, M. Shmueli-Scheuer, D. Cohen, N. Modani, H. Lamba, A. Dwivedi, A. A. Nanavati, M. Kumar.

9. MigCEP: Operator Migration for Mobility Driven Distributed Complex Event Processing.

10. Beate Ottenwa¨lder, Boris Koldehofe, Kurt Rothermel, Umakishore Ramachandran.

11. The 8 Requirements of Real-Time Stream Processing.

12. Michael Stonebraker, Ugur C¸ etintemel, Stan Zdonik.

13. Samza. http://samza.apache.org.

14. T. Akidau, A. Balikov, K. Bekiroglu, S. Chernyak, J. Haberman, R. Lax, S. McVeety, D. Mills, P. Nordstrom, and S. Whittle. Millwheel: Fault- tolerant stream processing at internet scale.

15. PVLDB, 6(11):1033-1044, Aug 2013

16. S. Kulkarni, N. Bhagat, M. Fu, V. Kedigehalli, C. Kellogg, S. Mittal, J. M. Patel, K. Ramasamy, and S. Taneja. Twitter heron: Stream processing at scale.

17. A. Toshniwal, S. Taneja, A. Shukla, K. Ramasamy, J. M. Patel, S. Kulkarni, J. Jackson, K. Gade, M. Fu, J. Donham, N. Bhagat, S. Mittal, and D. Ryaboy. Storm@twitter. In SIGMOD, pages 147–156, 2014

18. Realtime Data Processing at Facebook

19. Guoqiang Jerry Chen, Janet L. Wiener, Shridhar Iyer, Anshul Jaiswal, Ran Lei Nikhil Simha, Wei Wang, Kevin Wilfong, Tim Williamson, and Serhat Yilmaz Facebook, Inc

20. The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems.

21. D. C. Luckham Addison-Wesley Longman Publishing Co., Inc., 2001