Internet of Things Architecture and Capabilities

© 2014 International Business Machines Corporation 1
IBM Internet of Things Architecture and Capabilities
Jerry Keesee
Director, Real-Time and Context Computing, IBM
jkeesee@us.ibm.com @jrkazoo

We have built the world’s broadest and deepest
portfolio in data, analytics, and cloud.
15,000
$24 billion $17 billion
invested to date to build IBM’s
capabilities in Big Data and
analytics, with $7 billion in
organic investment
of gross spend for Big
Data and analytics,
including more than 30
acquired companies
500
Analytics consultants
and 400 mathematicians
Analytics patents
generated each year
We have significantly increased analytics and cloud revenue through strategic investments, and new skills and capabilities.
Analytics Revenue
2013
2010
$16 billion
$11 billion
40
total cloud data centers across five continents
Cloud Revenue
2013
2012
$4.4 billion
$2.6 billion

IBM has been delivering Internet Of Things solutions for a
Smarter Planet since 2008
Leveraging the data generated
by digital technology provides
intelligence to help us do
things better, improving our
responsiveness
and ability to predict and
optimize for future events
INTELLIGENT
Digital technologies
(sensors and other
monitoring devices) are
being embedded into many
objects, systems and
processes
INSTRUMENTED
INTERCONNECTED
In the globalized, networked
world, people, systems,
objects and processes are
connected, and they
are communicating with one
another in entirely new ways

A utility giant uses big data analytics to identify real and potential
faults, helping reduce and prevent outages and maintain service
>50% of outages
restored before customers
are aware of a problem
Smarter Energy
Business Challenge: This utility in the southern United States could not
respond proactively to power outages and grid issues that negatively
affected customers’ service. Although smart meters, a meter data
management system and an outage management system delivered vast
quantities of data, the company had no way to integrate and analyze the
information, hindering efforts to ascertain grid health and identify and fix
faults before a problem occurred.
The Smarter Solution: The utility deployed an integrated big data platform
that collects, consolidates and analyzes billions of data measurement points
collected from across the grid, providing a near-real-time view into the
health and performance of the network. Should an outage occur or a
potential problem, such
as power strain, arise, the system immediately alerts grid operators so that
they can respond quickly to resolve the issue before customers’ service is
interrupted.
Through analytics, operators discern between actual outages and trouble
spots that will cause outages, fixing problems preemptively and keeping
customers’ lights on.
5%–10% savings
anticipated for customers by
reducing consumption levels
40% reduction
in trucks required to respond in
one emergency incident

• IBM® Informix® TimeSeries
IBM Business Partner Chronos Process
Integration Sdn Bhd
250% increase
in access to sensor data,
supporting more accurate
predictive capabilities
Solution Components
Business need: This utility company in Malaysia wanted to increase availability in its
combined-cycle power plant. It needed a powerful and sophisticated plant
management system with the capability to predict equipment failures and support
preventive maintenance.
The solution: Ranhill Powertron maintains a continuous power supply, preventing
unplanned outages with a plant operation and management solution. The system
captures sensor data from equipment across the power plant in
near-real time and combines it with inspection and maintenance logs, helping the
company monitor equipment, track historical patterns and identify anomalies that
could signal a bigger problem.
“We can predict a machine’s or equipment’s operating condition more accurately,
which helps us plan preventive and corrective measures to maintain high availability,
shorten outage duration and reduce our costs.”
—Ahmad Jaafar, senior general manager
99.8% faster
data retrieval speeds,
facilitating quick decisions to
help avoid outages
Reduces costs
while helping the power plant
exceed availability targets
Ranhill Powertron
Improves power plant availability by predicting and preventing equipment failures

Scottish Power
Scottish Power chooses best-in-class Meter Data Management (MDM) solution to
deliver benefits throughout their value chain, from suppliers to consumers.
Powered by Informix
Business needs
 Accelerating time-to-value gained from
smart meter data
 Minimizing storage and system costs
 Protecting smart meter investments
 Giving customers better insight and
control over how they use energy
Benefits
 Achieving up to 50 to 70 times faster
processing of meter data
 Requiring up to 2/3 less storage for
meter data
 Having consistent, scalable
performance for highly predictable
costs

Getting Started
IBM
Bluemix
www.bluemix.net

Build Applications to Harness the Potential
IBM Bluemix – composable services development and ops
Run Your Apps
The developer can chose any language
runtime or bring their own.
DevOps
Development, monitoring, deployment and logging
tools allow the developer to run the entire
application.
APIs and Services
Broad catalog of IBM, 3rd party, and open source, APIs
and services to compose an application in minutes.
Cloud Integration
Build hybrid environments. Connect to on-premises
systems of record plus other public and private
clouds. Expose your own APIs to your developers.
Built on IBM SoftLayer
No need to worry about provisioning or managing
infrastructure.

Informix deploys quickly, scales on demand, offers pay-as-you-go option -
also via BlueMix
• Data sharding across enterprise replication
enhances scalability and elasticity
• Multi-tenant support allows hosting of multiple
logically independent server instances within one
single instance
• Delivering cost benefits on hardware
resources and software licenses
• Simplified administration for backup of multiple
database servers in Cloud
• Delivers Time Series Database service in
BlueMix
• Support for ARM and Intel for gateways,
consolidators and devices
TIME SERIES DATABASE SERVICE
•Accelerates time series analytics in the cloud
•Supports multiple data types including time
series, spatial, NoSQL & relational data
•SQL . Rest, and JSON interface
•Rapid application development

Bluemix Time Series Database Service - “Large” - Closed Beta
 Or try the Time Series Database
Small service available now in
BlueMix which provides:
– 10 Gb max size
– Private Database, Shared
Instance
– 10 connections per tenant
– https://bluemix.net
 Join the Time Series Database Large
Closed Beta to help evaluate potential
features and expanded capacity
including:
– 250GB of space
– Dedicated CPU(s)
– 1000 connections per tenant
– Data and Index compression
 Beta opens in mid-December
– Can accommodate up to 16
participants
 Beta Participant Requirements
– A BlueMix ID. Don’t have one yet?
Register for free: https://bluemix.net/
– Sign a Non-Disclosure Agreement &
Register for the Beta.
(rwozniak@us.ibm.com) at Insight

IoT as a Composable Business
IoT Foundation
IoT Related Bluemix services
Secure Device Registration
Scalable Device Connectivity
Historian
Visual wiring
Rules, Push, Geo location, Analytics, Asset management, Predictive Maintenance, …
Devices & Gateways
Device recipe
open
community
IoT end-end solutions
Connected appliance solutions, Smarter home solutions, …
App tips open
community
IoT SDKs

IBM IoT’s Functional Architecture
Streams
Deep Analytics Zone
Device/Sensors
Smart Gateways
Sensor Analytics Zone

Why Gateways and Real-Time Analytics are Key to Success
An Intelligent Gateway Should:
• Filter and aggregate for consolidated view
• Enable local processing and decision making
• Reduce latency, bandwidth and cost of backend cloud
• Reduce storage requirements
• Perform 80% simple operations locally
• Handle real-time and context computing on the edge
securely
• Deliver analytics and insights for data-in-motion
• Enable immediate action

Key Characteristics for Informix IoT Gateway
Database
SpatialTime-Series
NoSQL
Gateway to Cloud
Enterprise SQL
Clustering/Replication
Encryption/Authentication Ease of Admin Compression

Informix is Uniquely Positioned for Sensor Analytics
Performance
Embeddability
Scalable Cloud
Hybrid Support
App Development
• Optimized for TimeSeries and Spatial data
• High speed capture and real-time analysis
 Consolidated view across multiple data
types
 SQL and NoSQL/JSON hybrid integration
 Lower storage and latency requirements
• TimeSeries and Internet of Things in
Bluemix
Sensor

Context Computing for IoT

© 2014 IBM Corporation
Context Accumulation, definition
Incrementally contextualizing new
observations with historical
observations, dynamically, and in real
time.
17

© 2014 IBM Corporation
Context Computing & IoT Relations
 Context Computing will be a consumer of the IoT
– The IoT will be a source of new observations for Context Computing
 IoT will be a consumer of Context Computing
– Context Computing decisions will influence IoT behaviors e.g., when to
pay more or less attention
 Context Computing will live in the IoT
– Contextualizing past and present observations for at-the-sensor and in-
the-moment decision making
18

© 2013 IBM Corporation20 IBM Confidential
Resolve Entities and
Accumulate Context
Context Accumulation to enable context-driven insight and action
Streaming Data
Text Data
Applications
Data
Time Series
Geo Spatial
Relational
• Resolve entities across
data sources (people,
places, things...)
Social Network
Video &
Image
Many Data Sources
(The Observation Space)
Determine Relevance Insight and Action
Significant Relationship
Son
Mother
Birthday
Date
Temporal Reasoning
(e.g., customer journey)
&
Spatial Reasoning
A
&
• Company data
• Shared data
• 3rd Party data
• Public data
• Integrate new
observations with
previous ones
• Unica
• Smarter
Commerce
• ILOG
• Other ISVs.
• I2 Analyst NB
• Curam
• Etc.
Alert
Automated
Process
Case
Management
Analysis
Correlation & others...
• Direct to
workflow

The Right Analytics, At The Right Layer,
At The Right Time, To Generate Actionable Insights
cs
Tier 1: Devices / Sensors (Things)
Tier 2: Protocol Gateways
analytics
zone
model dev. ,
training and
operationalizat
ion
real-time event
management
Tier 3: Operational Gateways
Analytics
pushdown
Internet
Tier4: Data &
Analytics Zone

No company provides all the pieces
Internet of Things solutions need an ecosystem
Solutions & Applications
Smarter
Cities
Transport
& Rail
Energy
& Utilities
Consumer
Electronics
Life Science
& Healthcare
Oil
& Gas
Connected
Vehicle
Industrial
Manufacturing
Devices Gateways CloudsNetworks
IBM Industry
Solutions,
GBS
IBM SWG
MessageSight
Streams
SDK SDK Partnerships
Maximo
IoC
IBM IoT Ecosystem
partner program
launching soon!

Smarter
Communications Retail
Tracking
Smarter
Energy
Key Partnerships
Connected
Home

IBM, the IBM logo, and ibm.com are trademarks of IBM Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies.
A current list of IBM trademarks is available on the web at “Copyright and trademark information” at ibm.com/legal/copytrade.shtml. © Copyright IBM Corporation 2014.

Backup

Solve the Big Data Challenge of Sensor Data
Unprecedented performance and scalability for managing time series data
•NEW! Able to replicate time series data across multiple servers in a clustered grid
•NEW! Support for data retention rules and enhanced storage optimization
with ability to automatically remove data outside of defined window of time
•NEW! Enhanced usability enables faster and easier development of time series applications
• GUI simplifies creating, loading and manipulating time series data
•NEW! Spatial feature upgraded to ESRI 10.1 for easy and cost effective spatial applications
•No additional installations or license fees required for time series and spatial capabilities!
27
5 times the performance < 1/5 the resources
… with significantly simpler management using a single node system
Daily Readings
(meters * registers * intervals)
970,000,000
4,900,000,000
The
Competition
Informix
TimeSeries
CPU Resources
(cores)
16
Competition
– db cores
Informix
TimeSeries
total cores
+ app server
cores
48
180

Capability Comparison
IBM
Informix
SQLite PostgreS
QL
Cassandr
a
MySQL Oracle
Berkeley DB
Enterprise DB on the
Gateway Device
Yes No Yes Yes Yes No
Same DB on Gateway
and Cloud
Native NoSQL Support Yes No Yes Yes No Yes
Native Time-Series
Support
Yes No No Yes No No
Support for Geo Spatial
data
Yes Yes Yes No Yes Yes
Support for Relational
data
Yes Yes Yes No Yes No
REST interface support Yes Yes Yes Yes Yes No
Multiple Replication,
Clustering and scaling
options
Yes No No Yes No No
Security –
Encryption/Authenticati
on
Ease of use and
administration
Yes Yes No No Yes Yes
Data Compression for
both Read & Write Yes No Yes Yes Yes No

Internet of Things Architecture and Capabilities

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