商品描述
This book applies several intelligent approaches for efficient resource scheduling in networks. It discusses Mobile Edge Computing aided intelligent IoT and focuses mainly on the resource sharing and edge computation offloading problems in mobile edge networks. The blockchain-based IoT (which allows fairly and securely renting resources and establishing contracts) is discussed as well.
The Internet of Things refers to the billions of physical devices that are now connected to and transfer data through the Internet without requiring human-to-human or human-to-computer interaction. According to Gartner's prediction, there will be more than 37 billion IoT connections in the future year of 2025. However, with large-scale IoT deployments, IoT networks are facing challenges in the aspects of scalability, privacy, and security. The ever-increasing complexity of the IoT makes effective monitoring, overall control, optimization, and auditing of the network difficult. Recently, artificial intelligence (AI) and machine learning (ML) approaches have emerged as a viable solution to address this challenge. Machine learning can automatically learn and optimize strategy directly from experience without following pre-defined rules. Therefore, it is promising to apply machine learning in IoT network control and management to leverage powerful machine learning adaptive abilities for higher network performance.
This book targets researchers working in the Internet of Things networks as well as graduate students and undergraduate students focused on this field. Industry managers, and government research agencies in the fields of the IoT networks will also want to purchase this book.
商品描述(中文翻譯)
本書提供了物聯網網路和機器學習的概述,並介紹了物聯網架構。它設計了一種新的智能物聯網網路架構,並介紹了不同的機器學習方法來探討解決方案。書中討論了機器學習如何幫助網路感知並實現網路智能控制。它還討論了能夠促進智能物聯網網路發展的新興網路技術。
本書應用了幾種智能方法來提高網路中的資源調度效率。它討論了移動邊緣計算輔助的智能物聯網,主要集中在移動邊緣網路中的資源共享和邊緣計算卸載問題上。書中也討論了基於區塊鏈的物聯網(該技術允許公平且安全地租用資源並建立合約)。
物聯網是指數十億個物理設備,這些設備現在通過互聯網連接並傳輸數據,而不需要人與人或人與計算機之間的互動。根據Gartner的預測,到2025年,物聯網連接數量將超過370億。然而,隨著大規模物聯網的部署,物聯網網路在可擴展性、隱私和安全性方面面臨挑戰。物聯網日益增加的複雜性使得有效監控、整體控制、優化和審計網路變得困難。最近,人工智慧(AI)和機器學習(ML)方法已成為解決這一挑戰的可行方案。機器學習可以自動從經驗中學習和優化策略,而無需遵循預定義的規則。因此,將機器學習應用於物聯網網路控制和管理,以利用強大的機器學習自適應能力來提高網路性能,具有良好的前景。
本書的目標讀者是從事物聯網網路研究的研究人員,以及專注於該領域的研究生和本科生。物聯網網路領域的行業管理者和政府研究機構也會希望購買本書。
作者簡介
Mohsen Guizani (Fellow, IEEE) received his BS (with distinction), MS, and Ph.D. degrees in electrical and computer engineering from Syracuse University, NY. He is currently a professor and an associate provost at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, UAE. Previously, he worked in different institutions in the United States. His research interests include applied machine learning and artificial intelligence, the Internet of Things, intelligent systems, smart city, and cybersecurity. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2019, 2020, and 2021. He has won several research awards including the 2015 IEEE Communications Society Best Survey Paper Award as well as four Best Paper Awards from IEEE ICC and GLOBECOM. He is the author of 10 books and more than 800 publications. He is also the recipient of the 2017 IEEE Communications Society Wireless Technical Committee (WTC) Recognition Award, the 2018 Ad Hoc Technical Committee Recognition Award, and the 2019 IEEE Communications and Information Security Technical Recognition (CISTC) Award. He served as the Editor-in-Chief of IEEE Network and is currently serving on the Editorial Boards of many IEEE transactions and magazines. He was the Chair of the IEEE Communications Society Wireless Technical Committee and the Chair of the TAOS Technical Committee. He served as an IEEE Computer Society Distinguished Speaker and is currently an IEEE ComSoc Distinguished Lecturer.
作者簡介(中文翻譯)
姚海鵬(IEEE 高級會員)於2011年獲得中國北京郵電大學電信工程系的博士學位。他目前是北京郵電大學的教授。他在知名的同行評審期刊和會議上發表或共同發表了超過150篇論文。他的研究興趣包括未來網路架構、網路人工智慧、網路、空地一體化網路、網路資源分配以及專用網路。姚博士曾擔任《IEEE 可持續計算期刊》(IEEE Transactions on Sustainable Computing)、《IEEE Access》的副編輯,以及《IEEE 計算機學會開放期刊》(IEEE Open Journal of the Computer Society)和《Springer 網路與系統管理期刊》(Springer Journal of Network and Systems Management)的客座編輯。他獲得了多項研究獎項,包括2022年IEEE ICC最佳論文獎、2021年IEEE IWCMC最佳論文獎和2020年IEEE ICCC最佳論文獎。他曾擔任多個國際會議的技術程序委員會成員及研討會主席,包括IWCMC 2019研討會主席,以及ACM TUR-C SIGSAC2020出版主席。
穆罕默德·古伊扎尼(IEEE 會士)在美國紐約州的雪城大學獲得電機與計算機工程的優異學士、碩士和博士學位。他目前是阿布達比的穆罕默德·本·扎耶德人工智慧大學(MBZUAI)的教授及副教務長。此前,他曾在美國的不同機構工作。他的研究興趣包括應用機器學習和人工智慧、物聯網、智能系統、智慧城市和網路安全。他在2019年、2020年和2021年被列為Clarivate Analytics計算機科學高被引研究者。他獲得了多項研究獎項,包括2015年IEEE通訊學會最佳調查論文獎,以及來自IEEE ICC和GLOBECOM的四項最佳論文獎。他是10本書籍的作者,並發表了超過800篇論文。他還獲得了2017年IEEE通訊學會無線技術委員會(WTC)表彰獎、2018年特設技術委員會表彰獎,以及2019年IEEE通訊與資訊安全技術表彰獎(CISTC)。他曾擔任《IEEE Network》的主編,並目前在多個IEEE期刊和雜誌的編輯委員會中任職。他曾擔任IEEE通訊學會無線技術委員會主席及TAOS技術委員會主席。他曾擔任IEEE計算機學會的傑出演講者,並目前是IEEE ComSoc的傑出講師。