Cloud Computing（云计算） - Igor Faynberg 英文版
标签： Cloud Computing - Igor Faynberg
上传时间： 2016-03-06
上传用户：yongsheng
Cloud Computing Bible
标签：
上传时间： 2014-04-07
上传用户：LouieWu
云计算（cloud computing）是基于互联网的相关服务的增加、使用和交付模式，通常涉及通过互联网来提供动态易扩展且经常是虚拟化的资源。
标签： 云计算
上传时间： 2016-03-29
上传用户：nugewo
There is a phenomenal burst of research activities in mobile cloud computing systems, which extends cloud computing functions, ser- vices, and results to the world of future mobile communications applications, and the paradigm of cloud computing and virtualization to mobile networks. Mobile applications demand greater resources and improved interactivity for better user experience.
标签： Mobile Cloud Computing Systems
上传时间： 2020-05-30
上传用户：shancjb
云计算（cloud computing）中涉及了分布式处理、并行处理和网格计算、网络存储、虚拟化、负载均衡等传统计算机技术和网络技术。本文从云计算的体系架构和服务角度出发，对云计算中实现的访问控制管理、数据管理和虚拟化功能所使用加密算法和虚拟化等关键技术，用计算机和网络知识分析了这些技术存在的问题，提出了需要改进的方向。
上传时间： 2013-10-16
上传用户：阳光少年2016
This book provides an overview of recent innovations and achievements in the broad areas of cyber-physical systems (CPS), including architecture, networking, systems, applications, security, and privacy. The book discusses various new CPS technologies from diverse aspects to enable higher level of innovation towards intelligent life. The book provides insight to the future integration, coordination and interaction between the physical world, the information world, and human beings. The book features contributions from renowned researchers and engineers, who discuss key issues from various perspectives, presenting opinions and recent CPS-related achievements.Investigates how to advance the development of cyber-physical systems Provides a joint consideration of other newly emerged technologies and concepts in relation to CPS like cloud computing, big data, fog computing, and crowd sourcing Includes topics related to CPS such as architecture, system, networking, application, algorithm, security and privacy
上传时间： 2019-04-21
上传用户：danyun
Five years have passed since the first edition of this book was published.Over the five years,the world has witnessed a technological revolution headlined by an array of exciting consumer and industrial products such as the Nintendo Wii, Apple iPod/iPad, sensor-rich smart phones, phones with cameras,new operating systems for mobile phones and apps,e-books,WiFi,voice- over-IP calls, social networking, 3D animated movies, and cloud computing, to name the major ones that affect everyday living
标签： Foundations MEMS of
上传时间： 2020-06-06
上传用户：shancjb
With the proliferation of cloud computing and Internet online services, more and more data and computation are migrated to geographical distributed Internet data centers (IDCs), which can provide reliability, management, and cost benefits. However, IDC operators encounter several major problems in IDC operations, such as huge energy consumption and energy cost, and high carbon emission. To deal with the above problems, IDC operators have to efficiently manage the way of energy consumption and energy supply. Considering the potential of smart grid, we focus on the energy management of IDCs in smart grid from several perspectives, i.e., power outage, carbon emission, heterogeneous service delay guarantees, and operation risk.
上传时间： 2020-06-07
上传用户：shancjb
Although state of the art in many typical machine learning tasks, deep learning algorithmsareverycostly interms ofenergyconsumption,duetotheirlargeamount of required computations and huge model sizes. Because of this, deep learning applications on battery-constrained wearables have only been possible through wireless connections with a resourceful cloud. This setup has several drawbacks. First, there are privacy concerns. Cloud computing requires users to share their raw data—images, video, locations, speech—with a remote system. Most users are not willing to do this. Second, the cloud-setup requires users to be connected all the time, which is unfeasible given current cellular coverage. Furthermore, real-time applications require low latency connections, which cannot be guaranteed using the current communication infrastructure. Finally, wireless connections are very inefficient—requiringtoo much energyper transferredbit for real-time data transfer on energy-constrained platforms.
标签： Embedded_Deep_Learning Algorithms
上传时间： 2020-06-10
上传用户：shancjb
newcastle upon tyne university ,computing science 专业 java基础讲义
标签： university newcastle computing science
上传时间： 2015-03-13
上传用户：lindor
