TeleDatA: data mining, social network analysis and statistics analysis system based on cloud computing in telecommunication industry

  • Authors:

  • Yuxiao Dong;Qing Ke;Yanan Cai;Bin Wu;Bai Wang

  • Affiliations:

  • Beijing University of Posts and Telecommunications, Beijing, China;Beijing University of Posts and Telecommunications, Beijing, China;Beijing University of Posts and Telecommunications, Beijing, China;Beijing University of Posts and Telecommunications, Beijing, China;Beijing University of Posts and Telecommunications, Beijing, China

  • Venue:
  • Proceedings of the third international workshop on Cloud data management
  • Year:
  • 2011

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Abstract

Telecommunication data analysis has been often used as a background application to motivate many problems. However, traditional analysis algorithms meet new challenges, as the continued exponential growth in both the volume and the complexity of telecom data. With respect to this challenge, a new class of techniques and computing framework, such as MapReduce model, which mainly put focus on scalability and parallelism, has been emerging. In this paper, we present our applied cloud-based system, TeleDatA, which combines data mining, social network analysis and statistics analysis with MapReduce framework, for knowledge discovery in telecommunications. As a full functionality system, it provides data-flow oriented preprocessing utilities, chain engine, expression evaluation engine and core analysis algorithms that are implemented by using our new computing model with MapReduce, which makes TeleDatA have the ability to handle tera even peta-scale data in Telecom industry. More importantly, TeleDatA is applied to a real-world telecom data by elaborating several application scenarios and it has a good scalability, effectiveness and efficiency.