Stochastic network optimization with application to communication and queueing systems

Stochastic network optimization with application to communication and queueing systems

by Michael J. Neely

Book 7 of Synthesis lectures on communication networks --

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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 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.

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    How does Neely’s framework of making optimal decisions without knowing the future change the way you approach uncertainty in your own professional or personal life?

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    If you had to explain the core concept of Lyapunov drift and penalty to someone completely outside of engineering or mathematics using a real-world metaphor, what analogy would you use?

  3. 3

    The text emphasizes explicit performance-delay tradeoffs in communication systems; how do you see this balance between speed and efficiency playing out in other complex systems, such as project management or human organizations?

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