Network performance and fault analytics for LTE wireless service providers

This book is intended to describe how to leverage emerging technologies big data analytics and SDN, to address challenges specific to LTE and IP network performance and fault management data in order to more efficiently manage and operate an LTE wireless networks. The proposed integrated solutions p...

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Bibliographic Details
Main Author: Kakadia, Deepak.
Other Authors: Yang, Jin., Gilgur, Alexander.
Format: eBook
Language: English
Published: New Delhi : Springer, 2017.
Subjects:
Long-Term Evolution (Telecommunications)
Network performance (Telecommunication)
elektronické knihy
electronic books
ISBN: 9788132237211
9788132237198
Physical Description: 1 online resource

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Table of contents

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100 1 |a Kakadia, Deepak. 
245 1 0 |a Network performance and fault analytics for LTE wireless service providers /  |c Deepak Kakadia, Jin Yang, Alexander Gilgur. 
260 |a New Delhi :  |b Springer,  |c 2017. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
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505 0 |a Preface; About the Book; Contents; About the Authors; Abbreviations; 1 Network Performance and Fault Analytics for LTE Wireless Service Providers; 1.1 Introduction; 1.2 Motivation; 1.3 Current Performance and Fault Management Architectures; 1.4 Proposed Next-Generation Performance and Fault Management Architectures; 1.5 Summary of Gaps in Current Network Performance and Fault Tools and Analytics; 1.6 Book Outline; 2 Analytics Fundamentals; 2.1 Statistical Process Control; 2.1.1 Central Limit Theorem; 2.1.2 Applications of Central Limit Theorem: Bernoulli Trials. 
505 8 |a 2.1.3 Examples of SPC for Bernoulli Trials2.2 Outliers; 2.2.1 QoS Outliers; 2.2.2 Outliers: What Are They?; 2.2.3 Outlier Detection: The Basic Approach; 2.2.4 Advanced Methods of Outlier Detection; 2.3 A Few Words About Queueing Systems; 2.3.1 "True" Process Distributions for LTE Network Components; 2.3.2 Little's Law: The "Big Three" of Queueing Dynamics; 2.3.3 System Performance Laws; 2.3.3.1 Amdahl's Law; 2.3.3.2 Universal Scalability Law; 2.3.4 Conclusion; 2.4 Forecasting; 2.4.1 Time Series: Definition and Assumptions; 2.4.2 Filling in the Gaps in Data; 2.4.2.1 Why? 
505 8 |a 2.4.2.2 Methods: Extension2.4.2.3 Methods: Interpolation; 2.4.3 Moving Averages; 2.4.4 EWMA; 2.4.5 EWMA Forecasting; 2.4.6 ARIMA Forecasting; 2.4.7 Selection of Forecasting Model; 2.5 Regression; 2.5.1 A Few Words on Terminology; 2.5.2 Linearizable Relationships; 2.5.3 The Main Idea Behind Regression; 2.5.4 Solving Eq. (2.5.2); 2.5.5 Goodness of Fit; 2.5.6 Model Competition; 2.5.7 Analysis of Residuals; 2.5.8 Advanced Regression Methods; 2.5.9 Do We Have to Compete?; 2.6 Clustering; 2.6.1 Bundling the Curves; 2.6.2 Geographic Clustering; 2.6.3 Geographic Clustering of Signal; 2.7 Conclusion. 
505 8 |a 3.5.2 Retainability3.5.3 Integrity; 3.5.4 Availability; 3.5.5 Mobility; 3.6 Summary; 4 Enhanced Packet Core Network; 4.1 EPC Architecture; 4.1.1 SAE Gateways; 4.1.2 Mobility Management Entity; 4.1.3 Policy and Charging Resource Function (PCRF); 4.1.4 Home Subscription Server (HSS); 4.1.5 Application Services Domain (AS); 4.2 EPC Interfaces Specifications; 4.2.1 S1-U Interface; 4.2.2 S1-C Interface; 4.2.3 S5/S8 and SGi Interfaces; 4.2.4 Gx/Gxc and Rx Interfaces; 4.3 EPC Network Management Model; 4.3.1 MME Mobility Measurements; 4.3.2 MME Session and Subscriber Management. 
504 |a Includes bibliographical references. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book is intended to describe how to leverage emerging technologies big data analytics and SDN, to address challenges specific to LTE and IP network performance and fault management data in order to more efficiently manage and operate an LTE wireless networks. The proposed integrated solutions permit the LTE network service provider to operate entire integrated network, from RAN to Core, from UE to application service, as one unified system and correspondingly collect and align disparate key metrics and data, using an integrated and holistic approach to network analysis. The LTE wireless network performance and fault involves the network performance and management of network elements in EUTRAN, EPC and IP transport components, not only as individual components, but also as nuances of inter-working of these components. The key metrics for EUTRAN include radio access network accessibility, retainability, integrity, availability and mobility. The key metrics for EPC include MME accessibility, mobility and capacity, SGW, PGW capacity and connectivity. In the first parts of the book, the authors describe fundamental analytics techniques, and various key network partitions - RAN, Backhaul, Metro and Core of a typical LTE Wireless Service Provider Network. The second part of the book develops more advanced analytic techniques that can be used to solve complex wireless network problems. The second part of this book also describes practical and novel solutions for LTE service network performance and fault management systems using big data engineering. Self-organizing network (SON) architecture is presented as a way to utilize network performance and fault analytics to enable network automation. SON can significantly improve operational efficiencies and speed up network deployment. This book provides various ways to leverage data science to more intelligently and reliably to automate and manage a wireless network. The contents of the book should be useful to professional engineers and networking experts involved in LTE network operations and management. The content will also be of interest to researchers, academic and corporate, interested in the developments in fault analytics in LTE networks. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Long-Term Evolution (Telecommunications) 
650 0 |a Network performance (Telecommunication) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Yang, Jin. 
700 1 |a Gilgur, Alexander. 
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