A proposed architecture for Big Data analytics systems for telecommunication industry /

The competitive nature of the telecommunication industry needs fast decisions, and proactive solutions based on complete and updated views of business, customers, and network. However, current telecommunication information systems and mainly Data Warehouses were designed to implement predefined anal...

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Bibliographic Details
Main Author: Elagib, Sara Babiker Omer (Author)
Format: Thesis
Language:English
Published: Kuala Lumpur : Kulliyyah of Engineering, International Islamic University Malaysia, 2017
Subjects:
Online Access:Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library.
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040 |a UIAM  |b eng  |e rda 
041 |a eng 
043 |a a-my--- 
050 0 0 |a QA76.9.B45 
100 1 |a Elagib, Sara Babiker Omer,  |e author 
245 1 2 |a A proposed architecture for Big Data analytics systems for telecommunication industry /  |c by Sara Babiker Omer Elagib 
264 1 |a Kuala Lumpur :  |b Kulliyyah of Engineering, International Islamic University Malaysia,  |c 2017 
300 |a xiv, 109 leaves :  |b illustrations ;  |c 30cm. 
336 |2 rdacontent  |a text 
347 |2 rdaft  |a text file  |b PDF 
502 |a Thesis (MSCIE)--International Islamic University Malaysia, 2017. 
504 |a Includes bibliographical references (leaves 87-93). 
520 |a The competitive nature of the telecommunication industry needs fast decisions, and proactive solutions based on complete and updated views of business, customers, and network. However, current telecommunication information systems and mainly Data Warehouses were designed to implement predefined analytics, and they are challenged by large-scale and fast growing telecom data, and the variety of its applications. The main aim of this research is to address the issues of high volume, velocity of data in telecommunication industry, and the variety of its usages, to achieve Big Data analytics system architecture. This architecture is proposed to facilitate developing heterogeneous telecom data analytics, and to support real and near real time use cases. Therefore, in this work, telecom analytics applications that require Big Data processing were investigated, and their requirements were analyzed. Then the architecture was designed based on the collected requirements. The proposed architecture uses Spark as a general purpose processing engine for implementing heterogeneous stream and batch analytics applications. Hadoop Distributed File System HDFS and Cassandra are the data stores, and Kafka is used for data streaming and pipelining. The architecture was then evaluated based on its functional completeness and its performance. The performance figures of the proposed architecture were calculated using performance figures of Spark, Cassandra, and Kafka. The results showed that the proposed architecture can support real-time and large-scale analytics applications with average 15 ms latency and 2-8min processing time respectively. 
596 |a 1 
655 7 |a Theses, IIUM local 
690 |a Dissertations, Academic  |x Department of Electrical and Computer Engineering  |z IIUM 
710 2 |a International Islamic University Malaysia.  |b Department of Electrical and Computer Engineering 
856 4 |u http://studentrepo.iium.edu.my/handle/123456789/4782  |z Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library. 
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