期刊全称 | Analytical Methods for Network Congestion Control | 影响因子2023 | Steven H. Low | 视频video | | 学科分类 | Synthesis Lectures on Learning, Networks, and Algorithms | 图书封面 |  | 影响因子 | The congestion control mechanism has been responsible for maintaining stability as the Internet scaled up by many orders of magnitude in size, speed, traffic volume, coverage, and complexity over the last three decades. In this book, we develop a coherent theory of congestion control from the ground up to help understand and design these algorithms. We model network traffic as fluids that flow from sources to destinations and model congestion control algorithms as feedback dynamical systems. We show that the model is well defined. We characterize its equilibrium points and prove their stability. We will use several real protocols for illustration but the emphasis will be on various mathematical techniques for algorithm analysis.Specifically we are interested in four questions:1. How are congestion control algorithms modelled?2. Are the models well defined?3. How are the equilibrium points of a congestion control model characterized?4. How are the stability of these equilibrium points analyzed?For each topic, we first present analytical tools, from convex optimization, to control and dynamical systems, Lyapunov and Nyquist stability theorems, and to projection and contraction theore | Pindex | Book 2017 |
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