000			04380nam a22005055i 4500
999			_c11761 _d11761
001			978-81-322-3721-1
003			DE-He213
005			20211214101019.0
008			170927s2017 ii | s |||| 0|eng d
020			_a9788132237211
040			_cAIKTC-KRRC
041			_aENG
072		7	_aTJK _2bicssc
072		7	_aTEC041000 _2bisacsh
072		7	_aTJK _2thema
082	0	4	_a621.382 _223
100	1		_aKakadia, Deepak. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aNetwork Performance and Fault Analytics for LTE Wireless Service Providers _h[electronic resource] /
250			_a1st ed. 2017.
264		1	_aNew Delhi : _bSpringer India : _bImprint: Springer, _c2017.
300			_aXVIII, 204 p. 146 illus. _bCard Paper
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
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.
650		0	_aEXTC Engineering _94619
653			_aCommunications Engineering, Networks.
653			_aComputer Communication Networks.
653			_aInformation Systems and Communication Service.
700	1		_aYang, Jin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aGilgur, Alexander. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9788132237198
776	0	8	_iPrinted edition: _z9788132237204
776	0	8	_iPrinted edition: _z9788132238959
856	4	0	_uhttps://doi.org/10.1007/978-81-322-3721-1 _zClick here to access eBook in Springer Nature platform. (Within Campus only.)
942			_cEBOOKS _2ddc