Building the Internet of Everything

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Transcript of Building the Internet of Everything

Page 1: Building the Internet of Everything
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2 © 2014 Cisco and/or its affiliates. All rights reserved. Cisco Confidential

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It’s Huge, but How Huge?

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It’s Huge, but How Huge?

•  IoT hype has surpassed Big Data •  Press has increased 10X in one year

•  CAGR of IoT 2013-2020 is projected to be ~ 35%/year •  This is not a market

This is a collection of loosely related markets

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Is This the IoT Market?

•  In # of devices: •  Commercial / industrial will pass consumer around 2018

•  In $: •  Until 2020, consumer IoT will be greater •  Long term, commercial / industrial will be 2X consumer

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“The network will play a crucial part in how we develop the car; gathering data, learning from it and adapting will ultimately determine our season” Christian Horner

Team Principal, Infiniti Red Bull Racing

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Edge Devices

Data Computing Tiers Optional Fog Nodes for Better Performance

Edge Devices

Data Center and

Applications IoT Data System

Fog Node

Fog Node

Data Center and

Applications

3 or More Tiered System 2 Tiered System

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Basic Premises

Devices send and receive data interacting with the

Network where the data is transmitted, normalized, and filtered using

Edge Computing before landing in

Data storage / Databases accessible by

Applications which process it and provide it to people who will

Act and Collaborate

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IoT World Forum Reference Model Levels

Application (Reporting, Analytics, Control)

Data Abstraction (Aggregation & Access)

Data Accumulation (Storage)

Edge Computing (Data Element Analysis & Transformation)

Connectivity (Communication & Processing Units)

Physical Devices & Controllers (The “Things” in IoT)

Collaboration & Processes (Involving People & Business Processes)

1

2

3

4

5

6

7

Sensors, Devices, Machines, Intelligent Edge Nodes of all types

Center

Edge

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Internet of Things Design Issues

Sensors, Devices, Machines, Intelligent Edge Nodes of all types

Center

Edge

IT

OT

Query Based

Event Based

Data at Rest

Data in Motion

Non-real Time

Real Time

Levels

1

2

3

4

5

6

7

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Bridging IT and OT

Sensors, Devices, Machines, Intelligent Edge Nodes of all types

Center

Edge

Key Point: IT – OT

IT

OT

Levels

1

2

3

4

5

6

7

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Bridging IT and OT: Introducing IoT “Edgeware”

Devices Edge

Edge computing

Device Control •  Configure (from the device provider) •  Status (from the device provider)

Device Interactions •  Discovery •  Addressing •  Protocol conversion

Middleware •  Listeners (Zigbee), brokers (MQTT) •  Event grouping / batch interactions

Data •  Normalize (standardize codes for the app) •  Filter (against pre-set criteria from the app) •  Expand (decode/expand cryptic codes) •  Aggregate (generate statistics) •  Notify/alert (to the app)

Combine the functions above •  Schedule (when to comm with the device) •  BPM (when multiple steps are needed) Security •  Roles •  Privileges

An individual edge software function may serve many

applications

Edge software can be sourced completely separately from the vertical application

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Cisco IoE Sub-Systems

Data Transport

Data Collection

Data Leverage

Sec

urity

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Key Points: •  IT – OT •  Decoupling

Issue: Devices may generate data faster than apps can ingest it

Devices

Apps

Bridging IT and OT: Handling the Volume of Data

Sensors, Devices, Machines, Intelligent Edge Nodes of all types

Center

Edge

Levels

1

2

3

4

5

6

7

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Edge Devices

Application IoT Data System

Data is Queried as Needed from the Application to the IDS

Data is Pushed Through IDS as Generated from Edge Devices to the Application

Edge Devices

Application IoT Data System

Subscribe

Query

IoT Data System “Flow”

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Apps

Apps

BI (reporting)

Apps Apps

Supervisory Control

Systems

Data Transport

Data Collection

Data Leverage

IoE Consumers Analytics

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Data Transformation

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Serving Reporting (BI) and Applications

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Apps Apps Apps

Data Transport

Data Collection

Data Leverage

IoE Consumers Analytics

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IoE Analytics Introduces New Complexities

Key Issues: •  The velocity and volume of data may be huge •  In some cases, most of the data is unimportant

Traditional Capture Data

Store Data

Analyze Data

Edge Computing Becomes Crucial

IoT Analyze Data

Store Data

Capture Data from Devices

Reduce Data at the Edge

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Machine Data Meets Analytics

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Apps

Apps

BI (reporting)

Apps Apps

Data Transport

Data Collection

Data Leverage

IoE Consumers

Analytics

Time Series

Relational st

ream

ing

fast

deep

Hadoop

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Requirements for an IoE Platform

•  Reusable (modules)

•  Framework (for edge processing and data transport)

•  Options (fast data, deep data, streaming data)

•  Flexible (for integration with IT)

•  Easy (GUI tools)

•  Completely open system (with multiple vendors)

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The Complete IoE System

Key Points: •  Bridging IT & OT •  Decoupling

-  Scalability -  Agility

•  Interoperability •  Legacy Compatibility •  Analytics •  Integrated with the Enterprise

Sensors, Devices, Machines, Intelligent Edge Nodes of all types

Center

Edge

Levels

1

2

3

4

5

6

7

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Example IoE System Design

Edge Processing

Data Center

Fog Processing 300 Platforms

IT Central

7,000 Oil Wells

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Thank you.

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Requirements for an IoE Platform

•  Reusable modules for collecting data from, and providing control to, devices and machines •  Framework for edge processing •  Options for reliable transport of data through the system, encompassing both batch and real-time streaming options •  Flexible mechanisms for integration with IT systems, reporting, and analytics •  Easy to use GUI tools to simplify development and deployment for all aspects of the system •  A completely open system, where 3rd parties can provide devices, processing, modules, analytics, applications or any combination

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