| 书目名称 | Performance Modeling of Communication Networks with Markov Chains | | 编辑 | Jeonghoon Mo | | 视频video | | | 丛书名称 | Synthesis Lectures on Learning, Networks, and Algorithms | | 图书封面 |  | | 描述 | This book is an introduction to Markov chain modeling with applications to communication networks. It begins with a general introduction to performance modeling in Chapter 1 where we introduce different performance models. We then introduce basic ideas of Markov chain modeling: Markov property, discrete time Markov chain (DTMC) and continuous time Markov chain (CTMC). We also discuss how to find the steady state distributions from these Markov chains and how they can be used to compute the system performance metric. The solution methodologies include a balance equation technique, limiting probability technique, and the uniformization. We try to minimize the theoretical aspects of the Markov chain so that the book is easily accessible to readers without deep mathematical backgrounds. We then introduce how to develop a Markov chain model with simple applications: a forwarding system, a cellular system blocking, slotted ALOHA, Wi-Fi model, and multichannel based LAN model. The examples cover CTMC, DTMC, birth-death process and non birth-death process. We then introduce more difficult examples in Chapter 4, which are related to wireless LAN networks: the Bianchi model and Multi-Channel | | 出版日期 | Book 2010 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-79989-1 | | isbn_softcover | 978-3-031-79988-4 | | isbn_ebook | 978-3-031-79989-1Series ISSN 2690-4306 Series E-ISSN 2690-4314 | | issn_series | 2690-4306 | | copyright | Springer Nature Switzerland AG 2010 |
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发表于 2025-3-21 19:05:32
