The Resource Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book)
Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book)
Resource Information
The item Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.
This item is available to borrow from 1 library branch.
 Summary
 This 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 timevarying channels, mobility, and randomly arriving traffic. A simple driftpluspenalty framework is used to optimize time averages such as throughput, throughpututility, power, and distortion. Explicit performancedelay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energyefficient and profitmaximizing decisions must be made without knowing the future
 Language
 eng
 Extent
 1 electronic text (xii, 199 p. : ill.)
 Contents

 1. Introduction  Example opportunistic scheduling problem  General stochastic optimization problems  Lyapunov drift and Lyapunov optimization  Differences from our earlier text  Alternative approaches  On general Markov decision problems  On network delay  Preliminaries 
 2. Introduction to queues  Rate stability  Stronger forms of stability  Randomized scheduling for rate stability  Exercises 
 3. Dynamic scheduling example  Scheduling for stability  Stability and average power minimization  Generalizations 
 4. Optimizing time averages  Lyapunov drift and Lyapunov optimization  General system model  Optimality via [omega]only policies  Virtual queues  The min driftpluspenalty algorithm  Examples  Variable V algorithms  Placeholder backlog  Noni.i.d. models and universal scheduling  Exercises  Appendix 4.A, proving theorem 4.5 
 5. Optimizing functions of time averages  Solving the transformed problem  A flowbased network model  Multihop queueing networks  General optimization of convex functions of time averages  Nonconvex stochastic optimization  Worst case delay  Alternative fairness metrics  Exercises 
 6. Approximate scheduling  Timeinvariant interference networks  Multiplicative factor approximations 
 7. Optimization of renewal systems  The renewal system model  Driftpluspenalty for renewal systems  Minimizing the driftpluspenalty ratio  Task processing example  Utility optimization for renewal systems  Dynamic programming examples  Exercises 
 Isbn
 9781608454556
 Label
 Stochastic network optimization with application to communication and queueing systems
 Title
 Stochastic network optimization with application to communication and queueing systems
 Statement of responsibility
 Michael J. Neely
 Language
 eng
 Summary
 This 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 timevarying channels, mobility, and randomly arriving traffic. A simple driftpluspenalty framework is used to optimize time averages such as throughput, throughpututility, power, and distortion. Explicit performancedelay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energyefficient and profitmaximizing decisions must be made without knowing the future
 Cataloging source
 CaBNvSL
 http://library.link/vocab/creatorName
 Neely, Michael J
 Illustrations
 illustrations
 Index
 no index present
 Literary form
 non fiction
 Nature of contents

 dictionaries
 abstracts summaries
 bibliography
 Series statement

 Synthesis digital library of engineering and computer science.
 Synthesis lectures on communication networks
 Series volume
 7.
 http://library.link/vocab/subjectName

 Dynamic programming
 Queuing networks (Data transmission)
 Stochastic systems
 Lyapunov functions
 Target audience

 adult
 specialized
 Label
 Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book)
 Bibliography note
 Includes bibliographical references (p. 181198)
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 1. Introduction  Example opportunistic scheduling problem  General stochastic optimization problems  Lyapunov drift and Lyapunov optimization  Differences from our earlier text  Alternative approaches  On general Markov decision problems  On network delay  Preliminaries 
 2. Introduction to queues  Rate stability  Stronger forms of stability  Randomized scheduling for rate stability  Exercises 
 3. Dynamic scheduling example  Scheduling for stability  Stability and average power minimization  Generalizations 
 4. Optimizing time averages  Lyapunov drift and Lyapunov optimization  General system model  Optimality via [omega]only policies  Virtual queues  The min driftpluspenalty algorithm  Examples  Variable V algorithms  Placeholder backlog  Noni.i.d. models and universal scheduling  Exercises  Appendix 4.A, proving theorem 4.5 
 5. Optimizing functions of time averages  Solving the transformed problem  A flowbased network model  Multihop queueing networks  General optimization of convex functions of time averages  Nonconvex stochastic optimization  Worst case delay  Alternative fairness metrics  Exercises 
 6. Approximate scheduling  Timeinvariant interference networks  Multiplicative factor approximations 
 7. Optimization of renewal systems  The renewal system model  Driftpluspenalty for renewal systems  Minimizing the driftpluspenalty ratio  Task processing example  Utility optimization for renewal systems  Dynamic programming examples  Exercises 
 Dimensions
 unknown
 Extent
 1 electronic text (xii, 199 p. : ill.)
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9781608454556
 Issn
 19354193
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 digital file.
 Reformatting quality
 access
 Specific material designation
 remote
 System details
 System requirements: Adobe Acrobat Reader
 Label
 Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book)
 Bibliography note
 Includes bibliographical references (p. 181198)
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 1. Introduction  Example opportunistic scheduling problem  General stochastic optimization problems  Lyapunov drift and Lyapunov optimization  Differences from our earlier text  Alternative approaches  On general Markov decision problems  On network delay  Preliminaries 
 2. Introduction to queues  Rate stability  Stronger forms of stability  Randomized scheduling for rate stability  Exercises 
 3. Dynamic scheduling example  Scheduling for stability  Stability and average power minimization  Generalizations 
 4. Optimizing time averages  Lyapunov drift and Lyapunov optimization  General system model  Optimality via [omega]only policies  Virtual queues  The min driftpluspenalty algorithm  Examples  Variable V algorithms  Placeholder backlog  Noni.i.d. models and universal scheduling  Exercises  Appendix 4.A, proving theorem 4.5 
 5. Optimizing functions of time averages  Solving the transformed problem  A flowbased network model  Multihop queueing networks  General optimization of convex functions of time averages  Nonconvex stochastic optimization  Worst case delay  Alternative fairness metrics  Exercises 
 6. Approximate scheduling  Timeinvariant interference networks  Multiplicative factor approximations 
 7. Optimization of renewal systems  The renewal system model  Driftpluspenalty for renewal systems  Minimizing the driftpluspenalty ratio  Task processing example  Utility optimization for renewal systems  Dynamic programming examples  Exercises 
 Dimensions
 unknown
 Extent
 1 electronic text (xii, 199 p. : ill.)
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9781608454556
 Issn
 19354193
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 digital file.
 Reformatting quality
 access
 Specific material designation
 remote
 System details
 System requirements: Adobe Acrobat Reader
Library Links
Embed
Settings
Select options that apply then copy and paste the RDF/HTML data fragment to include in your application
Embed this data in a secure (HTTPS) page:
Layout options:
Include data citation:
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Stochasticnetworkoptimizationwithapplication/CQtHwgV_jZE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Stochasticnetworkoptimizationwithapplication/CQtHwgV_jZE/">Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book)</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>
Note: Adjust the width and height settings defined in the RDF/HTML code fragment to best match your requirements
Preview
Cite Data  Experimental
Data Citation of the Item Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book)
Copy and paste the following RDF/HTML data fragment to cite this resource
<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Stochasticnetworkoptimizationwithapplication/CQtHwgV_jZE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Stochasticnetworkoptimizationwithapplication/CQtHwgV_jZE/">Stochastic network optimization with application to communication and queueing systems, Michael J. Neely, (electronic book)</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>