000			03805nam a22005535i 4500
001			978-3-319-32721-1
003			DE-He213
005			20180206183051.0
007			cr nn 008mamaa
008			160601s2016 gw | s |||| 0|eng d
020			_a9783319327211 _9978-3-319-32721-1
050		4	_aTK1-9971
072		7	_aTJK _2bicssc
072		7	_aTEC041000 _2bisacsh
082	0	4	_a621.382 _223
100	1		_aZhang, Shan. _eauthor.
245	1	0	_aWireless Traffic Steering For Green Cellular Networks _h[recurso electrónico] / _cby Shan Zhang, Ning Zhang, Sheng Zhou, Zhisheng Niu, Xuemin (Sherman) Shen.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016.
300			_aXI, 128 p. 43 illus., 41 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aIntroduction -- Literature Review on Green Communications -- Dynamic Network Planning with Intra-Tier Traffic Steering -- Dynamic Network Planning with Inter-Tier Traffic Steering -- Inter-Tier Traffic Steering with Renewable Energy Harvesting -- Concluding Remarks.
520			_aThis book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consumption. Dynamic network planning adjusts cell density with traffic variations to provide on-demand service, which reduces network power consumption with quality of service provisioning during off-peak hours. With intra- or inter-tier traffic steering, cell density is dynamically optimized with regards to the instant traffic load for conventional homogeneous and multi-tier heterogeneous cellular networks, respectively. This book is beneficial for researchers and graduate students interested in traffic management and future wireless networking.
650		0	_aEngineering.
650		0	_aRenewable energy resources.
650		0	_aComputer communication systems.
650		0	_aElectrical engineering.
650		0	_aRenewable energy sources.
650		0	_aAlternate energy sources.
650		0	_aGreen energy industries.
650	1	4	_aEngineering.
650	2	4	_aCommunications Engineering, Networks.
650	2	4	_aRenewable and Green Energy.
650	2	4	_aComputer Communication Networks.
700	1		_aZhang, Ning. _eauthor.
700	1		_aZhou, Sheng. _eauthor.
700	1		_aNiu, Zhisheng. _eauthor.
700	1		_aShen, Xuemin (Sherman). _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319327198
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://dx.doi.org/10.1007/978-3-319-32721-1
912			_aZDB-2-ENG
942			_cLIBRO_ELEC
999			_c226948 _d226948