А. Zhumekenov


Nowadays the usage of mobile phones has reached extremely large worldwide proportions and is increasing dramatically. There is a stronger need to decrypt the important information that is hidden among them. Even all required information is gained, processes of companies remain static and can not be changed dynamically to adapt to actual business needs, reducing the advantages that can be achieved. Every second millions of raw information are being generated by mobile users, which handled by Telecom operators in data servers. By using Complex Event Processing (CEP) approach in real-time, we can obtain the information that really 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, however, have to be considered as a challenge to give subscribers the opportunity to get more customized offers and services.

Ключевые слова

Complex Event Processing, Telecom Data Analysis, Information Processing, Targeted campaigns.

Полный текст:

PDF (English)


Digital 2019: Global digital overview (2019).


Hermosillo, G., Seinturier, & L., Duchien, L. (2010, July 5-10). Using Complex Event Processing

for Dynamic Business Process Adaptation. IEEE International Conference on Services Computing,

Miami, FL, USA.

Cugola, G. & Margara, A. (2012). Processing Flows of Information: From Data Stream to Complex

Event Processing.

Cao, H., Dong, W. S., Liu, L, S., Ma, C. Y., Qian, W. H., Shi, J. W., Tian, C. H., Wang Y., Konopnicki, D.,

Shmueli-Scheuer, M., Cohen, D., Modani, N., Lamba, H., Dwivedi, A., Nanavati, A. A., & Kumar, M.

(2014). SoLoMo analytics for telco Big Data monetization. IBM Journal of Research and Development.

Ottenwalder, B., Koldehofe, B., Rothermel, K., & Umakishore, R. (2013, June). MigCEP: Operator

Migration for Mobility Driven Distributed Complex Event Processing. DEBS ‘13: The 7th ACM

International Conference on Distributed Event-Based Systems Arlington Texas USA.

Stonebraker, M., Cetintemel, U., & Zdonik, S. (2005). The 8 Requirements of Real-Time Stream

Processing. ACM SIGMOD Record, 34(4).


Akidau, T., Balikov, A., Bekiroglu, B., Chernyak, S., Haberman, J., Lax, R., McVeety, S., Mills, D.,

Nordstrom, P., & Whittle, S. (2013). Millwheel: Fault- tolerant stream processing at internet scale.

PVLDB, 6(11),1033–1044

Kulkarni, S., Bhagat N., Fu, M., Kedigehalli, V., Kellogg, C., Mittal, S.J., Patel, M., Ramasamy, K., & Taneja, S. (2015). Twitter heron: Stream processing at scale. In SIGMOD, 239–250.

Toshniwal, A., Taneja, S., Shukla, A., Ramasamy, K., Patel, J. M., Kulkarni, S., Jackson, J., Gade, K., Fu,

M., Donham, J., Bhagat, N., Mittal, S. & Ryaboy, D (2014). Storm@twitter. In SIGMOD, 147–156.

Chen, G., Wiener, J., Iyer, S., Jaiswal, A., Lei, R., Simha, N., Wang, W., Wilfong, K., Williamson, T., &

Yilmaz, S. Facebook, Inc. Realtime Data Processing at Facebook

Luckham, D. C. (2002). Addison-Wesley Longman Publishing Co., Inc., (2001). The Power of Events:

An Introduction to Complex Event Processing in Distributed Enterprise Systems. (1st edition).

Addison-Wesley Professional.


  • Ссылки не определены.

(P): 2707-9031
(E): 2707-904X

Бизнес-центр EXPO, блок C.1.
Казахстан, 010000