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008			220601s2010 sz | s |||| 0|eng d
020			_a9783031799952
024	7		_a10.1007/978-3-031-79995-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aT57.77 _b2010 EB
100	1		_aNeely, Michael J. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687844
245	1	0	_aStochastic Network Optimization with Application to Communication and Queueing Systems _cby Michael Neely
250			_a1st edition 2010
264		1	_aCham _bSpringer International Publishing _c2010
300			_a1 recurso en línea (XII, 199 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Learning Networks and Algorithms _x2690-4314
505	0		_aIntroduction -- Introduction to Queues -- Dynamic Scheduling Example -- Optimizing Time Averages -- Optimizing Functions of Time Averages -- Approximate Scheduling -- Optimization of Renewal Systems -- Conclusions.
520			_aThis text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energy-efficient and profit-maximizing decisions must be made without knowing the future. Topics in the text include the following: - Queue stability theory - Backpressure, max-weight, and virtual queue methods - Primal-dual methods for non-convex stochastic utility maximization - Universal scheduling theory for arbitrary sample paths - Approximate and randomized scheduling theory - Optimization of renewal systems and Markov decision systems Detailed examples and numerous problem set questions are provided to reinforce the main concepts. Table of Contents: Introduction / Introduction to Queues / Dynamic Scheduling Example / Optimizing Time Averages / Optimizing Functions of Time Averages / Approximate Scheduling / Optimization of Renewal Systems / Conclusions.
988			_aSynthesis Collection of Technology_2010
650		7	_2embne _9673656 _aLyapunov, Funciones de
650		7	_2embne _9158044 _aSistemas de comunicación inalámbricos
650		7	_2embne _9405190 _aProcesos estocásticos
776	0	8	_iPrinted edition: _z9783031799945
776	0	8	_iPrinted edition: _z9783031799969
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-79995-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI