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Introduction to Fog Computing Solutions (FOGINT-WS)

Course Description Schedule Course Outline

Detailed Course Outline

Module 1: Fog Computing and the Marketplace

Objective: Understanding the drivers across multiple industries, with use cases described from energy and power grid to air crafts and construction.

  • Fog Computing for Energy & the Power Grid: Generation, Distribution and Smart Metering use cases)
  • Fog Computing for Oil and Gas: Pipeline and Oil Well Monitoring and Control
  • Wind and Solar Farm Use Cases
  • Mining use Cases
  • Manufacturing Use Cases
  • Robotics Use Cases
  • Construction and Crane Use Cases
  • Transportation Use Cases (Air, Rail, Smart City, Buses, Urban Environments and Traffic Management)
  • Physical Asset Management
  • Surveillance and Security System Use Cases
  • Water System Use Cases: Collection, Purification, Distribution, and Consumption.

Module 2: Fog Computing Technology and Scope

Objective: Understanding the technological landscape of the Internet of Things in the Enterprise

  • Consumer IoT: Cloud-connected Mobile devices and Personal Sensors
  • Enterprise IoT and Fog Compute Models
  • Types of Things: Sensors, Activators and SCADA Systems
  • Industrial Networks, Protocols
  • Industrial Modernization: Opportunities and Requirements driving IP Network adoption

Module 3: Fog Computing and Business Outcomes for Enterprise IoT

Objective: Detailing the Business Outcomes and Challenges driving Fog Computing Models

  • Industrial IoT Business Objectives: Efficiency of Equipment and of Operations
  • Challenges of Limited Bandwidth, Latency concerns, Network reliability and cost models

Module 4: High Level Overview of Fog / Cloud Architecture

Objective: Defining the High level Architectural requirements for implementing Fog Compute Solutions.

  • Cloud Architecture and Limitations
  • Fog Architecture High Level
  • Designing at the Edge: the client, control and configuration, measurement & control signaling, resource pooling and caching
  • Applications in the Fog: Data Collection, local (edge) use, central (Cloud) use

Module 5: The Cisco Fog Computing Solution

Objective: Understanding the Cisco Fog Computing Architecture and Portfolio

  • High Level Cisco Fog Infrastructure
  • IOx Architecture
  • The Cisco Fog Compute Platform: Hardened edge servers, Embedded Compute, Embedded Storage, Accessible Interfaces and Application Enablement
  • The IOx SDK
  • Application management and Security
  • Sensors and End Point: Bringing intelligence and connectivity to legacy unconnected devices
  • Cisco Fog-Ready Portfolio: Cisco 819, Cisco Grid Connected Router 1120 and 1240
  • Infrastructure Components for a Fog Compute Solution BOM including UCS components
  • Fog Services – Data Acquisition and Transformation
  • Big Data and Cisco Fog Computing Solutions
  • Cisco Data In Motion (DMo):
    • Information Processing, Data acquisition and transformation, Event Detection and Aggregation
    • Rules-based Normalization and Dynamic Sensor Polling
    • Understanding Unstructured Data
    • Publisher Subscriber API
    • Rules and Pattern based Filtering
  • Data in Motion Use Cases
    • Data reduction and compression
    • Sensor virtualization
    • Plug and Play
  • Data in Motion Model (D3 Model)
  • Cisco Fog Computing and Security
  • Cisco Fog Compute Application Market Place
  • Applications, Hypervisors and VMs in a Cisco Grid Connected Router (CGR)
  • IOx on the Cisco Grid Router
  • Applications on IOx

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