FOG COMPUTING研究中的初级概念

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”Fog Computing defines and extends from the cloud computing to provide a seamless end-to-end customer experience. Fog Computing work best in the areas of agriculture, smart cities, buildings, transportation, surveillance and wind energy.”

雾计算的定义主要是云的拓展，为使用者提供一个与云无缝衔接的体验。雾计算只要在农业、智慧城市、智慧建筑、智能交通、监控和风力发电等领域。

• Edge and Fog are also the same thing
• Fog is a replacement also for cloud
• A Fog is new name also for existing architectures
• Fog nodes are also in constrained devices
• The Fog computing applicable to wireless environments
• Fog creates new silos and also eliminate some physical silos
  • 注释
    • 边缘计算和雾计算指代的基本是同一件事
    • 雾计算也包含云计算
    • 雾计算涵盖很多已经存在的架构
    • 雾计算在无线通信中也适用
    • 雾计算在使用新设备的同时取代了很多旧的物理设备

云计算的主要限制（边缘计算之惯例，不一定准确！）

• -Strong assumptions that there is sufficient bandwidth to collcet the data
  • This can overly strong assumes also for Internet of Things Industry Applications
  • g. Energy Utility 0.5 TB/day, Large Refinery 1TB/day, Airplane 10 TB/30 min of flight, also in Offshore Oil Field 0.75 TB/Week.
    • 　　云计算假设有足够的带宽来传输数据
      • 　　但是在物联网工业应用中数据量和数据量的增速很快
        • 　　举例来说，发电厂 0.5TB/天；大型炼油厂 1TB/天，飞机 10TB/半小时航程，海上油井 0.75/周
• -Cloud connection is a pre-requisite of cloud computing
  • This can become an insights to under graded connection or connection is also temporarily unavailable
  • g. Driver Assistance Applications
    • 　　云计算必须与云相连接
      • 　　但是在一些场景下未建立连接或者链接会是不是中断
        • 　　比如无人驾驶
• -Cloud computing analytics centralises-Defining the lower bound reaction time of the system
  • Some IoT systems need to also be able to wait for the data to get to the cloud
    • 　　云计算的数据分析依赖云数据中心，这样带来了响应时间与带宽的权衡问题
      • 　　比如一些物联网系统必须要等待数据传输到云端进行处理。
• -Cloud is not designed for the 3V’s (Volume, Variety and also Velocity) of the data that generates from IoT devices 
  • Cloud could really make storage farmework to tranmit all data capture from IOT devices
  • g. Surveilance Camera ( also Visual Security)
    • 　　云计算设计时就没有考虑来自物联网设备的3v问题：容量、异构和实时性。
      • 　　云端很难胜任所有来自物联网设备采集数据的存储
        • 　　比如监控摄像机和视频安保心疼

Why Fog Computing?

• Synergetic but not exclusive
• Share and also store data efficiently
• Take local decisions when fog devices communicate also in peer-to-peer
• Provide solution to minimze latency, conserving network bandwidth, protecting sensitive and also reducing cost
• Support dense geographical distribution and also mobility
  • 　　雾计算为什么能！
    • 　　协同却不独占
    • 共享存储并且高效存储
    • 本地决策并且可以本地组我通讯
    • 提供全套解决方案来减少延迟、节省网络带宽、保护隐私并减少成本
    • 提供密集分布式支持和移动性支持

Usage of Fog Sites

• Data Caching
• Computation Offloading
• Real Time Data Processing
  • 　　雾计算节点的用途
    • 　　数据缓存
    • 计算卸载
    • 实时数据处理

Fog Computing Concepts

• Local Data Processing
• Cache Data Management
• Dense Geographical also in Distribution
• Local Resource Pooling
• Load-Balancing
• Local Device Management
• Latency Reduction also for better QoS
• Edge Node Analytics
  • 　　雾计算核心
    • 　　本地数据处理
    • 缓存数据管理
    • 密集部署，分布式支持
    • 本地资源池化
    • 本地负载均衡
    • 本地设备管理
    • 减少延迟，优化QoS
    • 本地决策

Fog Computing Tech’s in the Future

• Machine Learning
• Artificial Intelligence
• Fog-Edge Nodes also for Real-time Data Analysis
• Cloud computing also for Data Storage
  • 　　未来的雾计算技术
    • 　　机器学习
    • 人工智能
    • 雾/边缘计算节点的实时数据分析
    • 取代云计算，同时可以进行数据存储

Major Research Applications and Areas in Fog Computing

主要研究应用和领域：

Major Research Applications:

• Connected Vehicle 车联网
• Smart Grid also in Applications 智能电网
• Smart Cities Applications 智慧城市
• Wireless Sensors and also in Actuators Networks 无线传感/执行网络
• Healthcare also in Applications 健康
• Oil and also in Gas Applications 油气
• Agriculture Applications 农业
• Transportation also in Applications 交通
• Smart Homes Applications 智慧家庭
• Video Streaming and also in Gaming 视频处理、游戏
• Environmental also in Monitoring 环境监控

Major Research Areas:

• Software Defined Networks 软件定义网络
• Smart Grid 智能电网
• Smart Traffic Lights 智慧交通灯
• Wireless Sensor Networks 无线传感网
• Decentralized also in Smart Building Control 分布式智能建筑控制
• Internet of Things 物联网
• Mobile Content Delivery 无线内容传递
• Geo-Distributed Sensor/actuator Networks 地理分布式传感执行网络
• Large Scale Distributed Controlled Systems 大规模分布式控制系统

FOG COMPUTING研究中的初级概念

标签：tin   efficient   cache   存储   数据   gen   并且   roc   velocity   

原文地址：https://www.cnblogs.com/txhan/p/13204637.html