building the internet of everything
TRANSCRIPT
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2 © 2014 Cisco and/or its affiliates. All rights reserved. Cisco Confidential
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3 © 2014 Cisco and/or its affiliates. All rights reserved. Cisco Confidential
© 2014 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 3
It’s Huge, but How Huge?
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4 © 2014 Cisco and/or its affiliates. All rights reserved. Cisco Confidential
© 2014 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 4
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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© 2014 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 5
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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