000 04977nam a22005775i 4500
001 978-3-030-15028-0
003 DE-He213
005 20220801214739.0
007 cr nn 008mamaa
008 190426s2019 sz | s |||| 0|eng d
020 _a9783030150280
_9978-3-030-15028-0
024 7 _a10.1007/978-3-030-15028-0
_2doi
050 4 _aTK5103.2-.4885
072 7 _aTJKW
_2bicssc
072 7 _aTEC061000
_2bisacsh
072 7 _aTJKW
_2thema
082 0 4 _a621.384
_223
100 1 _aYao, Haipeng.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_940200
245 1 0 _aDeveloping Networks using Artificial Intelligence
_h[electronic resource] /
_cby Haipeng Yao, Chunxiao Jiang, Yi Qian.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXI, 248 p. 116 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aWireless Networks,
_x2366-1445
505 0 _aPreface vii -- Acknowledgements ix -- Table of Contents xi -- Chapter 1 Introduction 1 -- Chapter 2 Intelligence-Driven Networking Architecture 13 -- Chapter 3 Intelligent Network Awareness 31 -- Chapter 4 Intelligent Network Control 79 -- Chapter 5 Intelligent Network Resource Management 151 -- Chapter 6 Intention Based Networking Management 191 -- Chapter 7 Conclusions and Future Challenges 237 -- Index 241.
520 _aThis book mainly discusses the most important issues in artificial intelligence-aided future networks, such as applying different ML approaches to investigate solutions to intelligently monitor, control and optimize networking. The authors focus on four scenarios of successfully applying machine learning in network space. It also discusses the main challenge of network traffic intelligent awareness and introduces several machine learning-based traffic awareness algorithms, such as traffic classification, anomaly traffic identification and traffic prediction. The authors introduce some ML approaches like reinforcement learning to deal with network control problem in this book. Traditional works on the control plane largely rely on a manual process in configuring forwarding, which cannot be employed for today's network conditions. To address this issue, several artificial intelligence approaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box approach, the authors present some ML methods to solve the complexity network resource allocation problems. Finally, semantic comprehension function is introduced to the network to understand the high-level business intent in this book. With Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5th Generation Wireless Systems (5G) development, the global network is undergoing profound restructuring and transformation. However, with the improvement of the flexibility and scalability of the networks, as well as the ever-increasing complexity of networks, makes effective monitoring, overall control, and optimization of the network extremely difficult. Recently, adding intelligence to the control plane through AI&ML become a trend and a direction of network development This book's expected audience includes professors, researchers, scientists, practitioners, engineers, industry managers, and government research workers, who work in the fields of intelligent network. Advanced-level students studying computer science and electrical engineering will also find this book useful as a secondary textbook. .
650 0 _aWireless communication systems.
_93474
650 0 _aMobile communication systems.
_94051
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer networks .
_931572
650 1 4 _aWireless and Mobile Communication.
_940201
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Communication Networks.
_940202
700 1 _aJiang, Chunxiao.
_eauthor.
_0(orcid)0000-0002-3703-121X
_1https://orcid.org/0000-0002-3703-121X
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_940203
700 1 _aQian, Yi.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_940204
710 2 _aSpringerLink (Online service)
_940205
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030150273
776 0 8 _iPrinted edition:
_z9783030150297
776 0 8 _iPrinted edition:
_z9783030150303
830 0 _aWireless Networks,
_x2366-1445
_940206
856 4 0 _uhttps://doi.org/10.1007/978-3-030-15028-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c76703
_d76703