Network-System Research and Distributed Composite Algorithm Design
暫譯: 網路系統研究與分散式複合演算法設計

Li, Huaqing, Lü, Qingguo, Xia, Dawen

Network-System Research and Distributed Composite Algorithm Design
  • 出版商: Springer
  • 出版日期: 2025-11-25
  • 售價: $8,240
  • 貴賓價: 9.5 折 $7,828
  • 語言: 英文
  • 頁數: 241
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 9819509106
  • ISBN-13: 9789819509102
  • 相關分類: 大數據 Big-data

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

With the rapid advancement of sensor technology and digital system, the capabilities of network communication have significantly improved, allowing multiple computing nodes to exchange information and collaborate seamlessly through networks. This progress has accelerated the development of distributed optimization theory and its applications in emerging fields such as low altitude economy, big data, and artificial intelligence. These emerging domains usually involve solving complex large-scale optimization problems, making it difficult for traditional centralized methods to handle. Therefore, it is necessary to study distributed algorithms to solve complex optimization problems in large-scale networked systems. In addition, the emergence of applications of large language model further stimulates researchers' growing interest in distributed optimization. This book provides the advanced methods and techniques of distributed optimization in networked systems, and thus is necessary and important for the research community.

This book focuses on designing high-performance algorithms for solving more practical and complex optimization problems (multi-block optimization, composite optimization, constrained optimization, optimization with diversity objective functions, etc.) in the context of distributed optimization in networked systems and their successful application to real-world applications (model predictive control, smart grids, etc.). Readers may be particularly interested in the book on consensus and optimization protocols, forward-backward splitting methods, proximal gradient methods, primal-dual methods, fixed point methods, asynchronous communication/computaion mechanisms, randomized block coordinate techniques, operator splitting schemes, uncoordinated step sizes strategies, etc., in the process of distributed optimization in various networked systems.

This book will introduce readers to the latest and advanced techniques in "Network-System Research and Distributed Composite Algorithm Design", and help them develop their own novel distributed algorithms that have practical applications. The prerequisite for understanding this book is to master basic mathematical knowledge, including graph theory, matrix theory, linear algebra, probability theory, etc. This book is meant for the researcher and engineer who uses distributed optimization algorithms in fields like control theory, electronic information, artificial intelligence, and computer science, etc. It can also serve as complementary reading for distributed optimization in networked systems at the post-graduate level.

商品描述(中文翻譯)

隨著感測器技術和數位系統的快速進步，網路通信的能力顯著提升，使得多個計算節點能夠透過網路無縫地交換資訊和協作。這一進展加速了分散式優化理論的發展及其在新興領域（如低空經濟、大數據和人工智慧）的應用。這些新興領域通常涉及解決複雜的大規模優化問題，傳統的集中式方法難以應對。因此，有必要研究分散式演算法以解決大規模網路系統中的複雜優化問題。此外，大型語言模型應用的出現進一步激發了研究人員對分散式優化日益增長的興趣。本書提供了網路系統中分散式優化的先進方法和技術，因此對於研究社群來說是必要且重要的。

本書專注於設計高效能演算法，以解決在網路系統的分散式優化背景下更實際和複雜的優化問題（如多區塊優化、複合優化、受限優化、具有多樣性目標函數的優化等），並成功應用於現實世界的應用（如模型預測控制、智慧電網等）。讀者可能特別對於在各種網路系統中進行分散式優化過程中的共識與優化協議、前向-後向分割方法、近端梯度方法、原始-對偶方法、固定點方法、非同步通信/計算機制、隨機區塊坐標技術、運算子分割方案、無協調步長策略等內容感興趣。

本書將向讀者介紹「網路系統研究與分散式複合演算法設計」的最新和先進技術，並幫助他們開發具有實際應用的創新分散式演算法。理解本書的前提是掌握基本的數學知識，包括圖論、矩陣理論、線性代數、概率論等。本書適合在控制理論、電子資訊、人工智慧和計算機科學等領域使用分散式優化演算法的研究人員和工程師，也可作為研究生層級的網路系統分散式優化的補充閱讀材料。

作者簡介

Huaqing Li currently a Professor with the College of Electronic and Information Engineering, Southwest University, Chongqing, China. His main research interests include nonlinear dynamics and control, multi-agent systems, and distributed optimization. He has authored or coauthored more than 100 related to the proposed book's topic. He currently serves as an Editorial Board Member for the IEEE Transactions on Industrial Cyber-Physical Systems, IEEE Transactions on Systems, Man and Cybernetics: Systems, Neural Computing and Applications, Frontiers of Information Technology & Electronic Engineering, etc.

Qingguo Lü was a recipient of the Outstanding Ph.D. Thesis Award of ACM China (Chongqing Branch) in 2021, the Outstanding Master's Thesis Award of Chongqing in 2019, and the Best Poster Award of EEI 2024. He is currently an Associate Researcher at College of Computer Science, Chongqing University, Chongqing, China.

Dawen Xia is currently a Professor at the College of Microelectronics and Artificial Intelligence & College of Big Data Engineering & Engineering Research Center of Micro-nano and Intelligent Manufacturing, Ministry of Education, Kaili University, Kaili, China and the College of Data Science and Information Engineering, Guizhou Minzu University, Guiyang, China. His research interests include distributed optimization, big data analytics, artificial intelligence, and data mining.

Xin Wang, from 2018 to 2019, he was a Visiting Scholar with the Humboldt University of Berlin, Berlin, Germany, and with the Potsdam Institute for Climate Impact Research, Potsdam, Germany. Since 2018, he has been a Professor with the School of Electronic and Information Engineering, Southwest University, Chongqing, China.

Zheng Wang is currently a Lecture with the College of Electronic and Information Engineering, Southwest University, China. His research interests include multiagent systems, distributed optimization, game, and their applications in smart grids.

Lifeng Zheng is currently a lecturer with the College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China. His research interests include multi-agent systems, model predictive control, game theory, and distributed optimization.

Jun Li is currently working toward the PhD degree with the College of Electronic and Information Engineering, Southwest University, Chongqing, China. His research interests include multiagent systems, distributed optimization, and reinforcement learning.

Liang Ran is currently working toward the Ph.D. degree in computer science and technology. His research interests include game theory, cooperative control, multiagent systems, and distributed optimization.

作者簡介(中文翻譯)

李華清目前是中國重慶西南大學電子與信息工程學院的教授。他的主要研究興趣包括非線性動力學與控制、多智能體系統以及分散式優化。他已經發表或合著了超過100篇與本書主題相關的論文。他目前擔任《IEEE 工業網路物理系統期刊》、《IEEE 系統、人類與網路期刊：系統》、《神經計算與應用》、《信息技術與電子工程前沿》等期刊的編輯委員會成員。 呂青國於2021年獲得ACM中國（重慶分會）優秀博士論文獎，2019年獲得重慶優秀碩士論文獎，並於2024年獲得EEI最佳海報獎。他目前是中國重慶大學計算機科學學院的副研究員。 夏大文目前是中國凱里大學微電子與人工智慧學院、大數據工程學院及教育部微納智能製造工程研究中心的教授，以及貴州民族大學數據科學與信息工程學院的教授。他的研究興趣包括分散式優化、大數據分析、人工智慧和數據挖掘。 王鑫在2018年至2019年間曾擔任德國柏林洪堡大學及德國波茨坦氣候影響研究所的訪問學者。自2018年以來，他一直是中國重慶西南大學電子與信息工程學院的教授。 王正目前是中國重慶西南大學電子與信息工程學院的講師。他的研究興趣包括多智能體系統、分散式優化、博弈及其在智慧電網中的應用。 鄭立峰目前是中國重慶科技大學計算機科學與工程學院的講師。他的研究興趣包括多智能體系統、模型預測控制、博弈論和分散式優化。 李俊目前正在中國重慶西南大學電子與信息工程學院攻讀博士學位。他的研究興趣包括多智能體系統、分散式優化和強化學習。 冉亮目前正在攻讀計算機科學與技術的博士學位。他的研究興趣包括博弈論、協作控制、多智能體系統和分散式優化。

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