000			03462nam a22005055i 4500
001			u375662
003			SIRSI
005			20160812084335.0
007			cr nn 008mamaa
008			110205s2011 gw | s |||| 0|eng d
020			_a9783642180842 _9978-3-642-18084-2
040			_cMX-MeUAM
050		4	_aQ342
082	0	4	_a006.3 _223
100	1		_aPouzols, Federico Montesino. _eauthor.
245	1	0	_aMining and Control of Network Traffic by Computational Intelligence _h[recurso electrónico] / _cby Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011.
300			_aXVI, 309 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStudies in Computational Intelligence, _x1860-949X ; _v342
505	0		_aInternet Science -- Modeling time series by means of fuzzy inference systems -- Predictive models of network traffic load -- Summarization and analysis of network traffic flow records -- Inference Systems for Network Traffic Control -- Open FPGA-Based Development Platform for Fuzzy Inference Systems.
520			_aAs other complex systems in social and natural sciences as well as in engineering, the Internet is hard to understand from a technical point of view. Packet switched networks defy analytical modeling. The Internet is an outstanding and challenging case because of its fast development, unparalleled heterogeneity and the inherent lack of measurement and monitoring mechanisms in its core conception. This monograph deals with applications of computational intelligence methods, with an emphasis on fuzzy techniques, to a number of current issues in measurement, analysis and control of traffic in the Internet. First, the core building blocks of Internet Science and other related networking aspects are introduced. Then, data mining and control problems are addressed. In the first class two issues are considered: predictive modeling of traffic load as well as summarization of traffic flow measurements. The second class, control, includes active queue management schemes for Internet routers as well as window based end-to-end rate and congestion control. The practical hardware implementation of some of the fuzzy inference systems proposed here is also addressed. While some theoretical developments are described, we favor extensive evaluation of models using real-world data by simulation and experiments.
650		0	_aEngineering.
650		0	_aInformation systems.
650		0	_aArtificial intelligence.
650		0	_aTelecommunication.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aCommunications Engineering, Networks.
650	2	4	_aInformation Systems Applications (incl.Internet).
700	1		_aLopez, Diego R. _eauthor.
700	1		_aBarros, Angel Barriga. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642180835
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v342
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-18084-2
596			_a19
942			_cLIBRO_ELEC
999			_c203542 _d203542