Reliable and Intelligent Optimization in Multi-Layered Cloud Computing Architectures

One of the major developments in the computing field has been cloud computing, which enables users to do complicated computations that local devices are unable to handle. The computing power and flexibility that have made the cloud so popular do not come without challenges. It is particularly challenging to decide which resources to use, even when they have the same configuration but different levels of performance because of the variable structure of the available resources. Cloud data centers can host millions of virtual machines, and where to locate these machines in the cloud is a difficult problem. Additionally, fulfilling optimization needs is a complex problem.

Reliable and Intelligent Optimization in Multi-Layered Cloud Computing Architectures examines ways to meet these challenges. It discusses virtual machine placement techniques and task scheduling techniques that optimize resource utilization and minimize energy consumption of cloud data centers. Placement techniques presented can provide an optimal solution to the optimization problem using multiple objectives. The book focuses on basic design principles and analysis of virtual machine placement techniques and task allocation techniques. It also looks at virtual machine placement techniques that can improve quality-of-service (QoS) in service-oriented architecture (SOA) computing. The aims of virtual machine placement include minimizing energy usage, network traffic, economical cost, maximizing performance, and maximizing resource utilization. Other highlights of the book include:

• Improving QoS and resource efficiency
• Fault-tolerant and reliable resource optimization models
• A reactive fault tolerance method using checkpointing restart
• Cost and network-aware metaheuristics.
• Virtual machine scheduling and placement
• Electricity consumption in cloud data centers

Written by leading experts and researchers, this book provides insights and techniques to those dedicated to improving cloud computing and its services.

在計算領域中，雲計算是一項重大發展，它使用戶能夠進行本地設備無法處理的複雜計算。雲端的計算能力和靈活性使其受到廣泛歡迎，但也面臨著挑戰。在可用資源的可變結構下，即使具有相同配置但性能不同，決定使用哪些資源是一個特別具有挑戰性的問題。雲端數據中心可以托管數百萬個虛擬機器，如何在雲端中定位這些機器是一個困難的問題。此外，滿足優化需求也是一個複雜的問題。

《可靠且智能的多層雲計算架構優化》探討了應對這些挑戰的方法。它討論了優化雲端數據中心資源利用和能源消耗的虛擬機器放置技術和任務調度技術。所提出的放置技術可以使用多個目標提供優化問題的最佳解決方案。該書著重於基本設計原則和虛擬機器放置技術和任務分配技術的分析。它還關注可以改善服務導向架構（SOA）計算中服務質量（QoS）的虛擬機器放置技術。虛擬機器放置的目標包括最小化能源使用、網絡流量、經濟成本，最大化性能和資源利用。該書的其他亮點包括：

- 提高QoS和資源效率
- 容錯和可靠的資源優化模型
- 使用檢查點重啟的反應式容錯方法
- 成本和網絡感知的元啟發式方法
- 虛擬機器調度和放置
- 雲端數據中心的電力消耗

這本書由領先的專家和研究人員撰寫，為致力於改進雲計算及其服務的人提供了洞察和技術。

Madhusudhan H. S. is an Associate Professor in the Department of Computer Science and Engineering at Vidyavardhaka College of Engineering, Mysuru, Karnataka, India.

Satish Kumar T. is an Associate Professor in the Department of Computer Science and Engineering at BMS Institute of Technology and Management, Bengaluru, Karnataka, India.

Punit Gupta is an Post Doc Fellow, School of Computer Science, University College Dublin, Dublin, Ireland.

Dinesh Kumar Saini is a Full Professor at the School of Computing and Information Technology, Manipal University Jaipur, Jaipur, Rajasthan, India.

Kashif Zia is a Research Associate at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, United Kingdom.

Madhusudhan H. S. 是印度卡納塔克邦梅索爾市 Vidyavardhaka College of Engineering 的計算機科學與工程系副教授。

Satish Kumar T. 是印度卡納塔克邦班加羅爾市 BMS Institute of Technology and Management 的計算機科學與工程系副教授。

Punit Gupta 是愛爾蘭都柏林市 University College Dublin 計算機科學學院的博士後研究員。

Dinesh Kumar Saini 是印度拉賈斯坦邦班奈爾市 Manipal University Jaipur 計算機與資訊技術學院的教授。

Kashif Zia 是英國格拉斯哥市 University of Glasgow MRC/CSO Social and Public Health Sciences Unit 的研究助理。