This document provides an overview and agenda for a presentation on creating a "Hello World" program with Cisco's Data in Motion (DMo) software. The presentation introduces DMo and how it can manage and analyze data at the edge. It discusses how DMo represents a paradigm shift with edge intelligence and provides examples of railway and utilities use cases. The document explains DMo's programming model involving dynamic data definitions, patterns, conditions, and actions. It also demonstrates how to set up a DMo instance, create timer and event rules to read a light sensor and control an LED based on the sensor readings.

2. Create a Hello World with
Data in Motion
David A. Maluf, Ph.D.
DEVNET-1163

3. • Introduction
• Paradigm Shift At the Edge
• Examples and Use Cases
• Programming Data in Motion
• Create a Hello World Now
• Q & A
Agenda

4. Introduction

5. Data in Motion and IoT
• The Internet of Things (IoT) is a computing concept that describes a future
where everyday physical objects will be connected to the Internet and be able to
identify themselves to other devices.
• Cisco Data in Motion (DMo) is a software technology that provides data
management and first-order analysis at the edge.
• Cisco Data in Motion provides mechanisms to capture data and control flows
within the network translating data into information and ultimately into knowledge
for use by higher order applications within a system.

6. Paradigm Shift with Edge Intelligence
Unified Platform
Network Compute Storage
CLOUD CLOUDEDGE
STORE ANALYZE ACT NOTIFY

7. Examples and Use Cases

8. Railway Systems
Fear of Derailment
Underutilized Equipment

9. Immediate Response
to Equipment Failure
Real-time Health Status
of Trains
REPLACE
BEARINGS
CAR 07

10. Poor Leak Detection
Limitations in Network
Connectivity
Costly Maintenance
and Management

11. Proactive Leak Detection
Predictive Management
S6 | C026 Pressure
Drop
kPa
ACTION
REQUIRED

12. ENERGYUSE
HIGH
LOW
MONDAY FRIDAYTHURSDAYTUESDAY WEDNESDAY

13. ENERGYUSE
HIGH
LOW
20-30% Energy Cost Savings
MONDAY FRIDAYTHURSDAYTUESDAY WEDNESDAY

14. Programming Data in
Motion

15. Data In Motion Model (details)
• Context: Sandbox for an
application with separate URP
allowing for the creation and
interaction of multiple data analysis
operations.
• Dynamic Data Definitions (aka
D3): A set of patterns, rules, and
actions for a specific analysis task.
Multiple D3s may exist within a
single context and reference each
other for compound or recursive
analysis.
Context
D3 D3 D3
D3 D3 D3
D3

16. The D3 Model (details)
• Dynamic Data Definition involve the
relationship of three simple concepts
• Pattern
• Condition
• Action
D3
Pattern
Protocol Patterns
Condition
Content (aka Payload)
Parameters – Output of
Operations
Action
Event (Condition Met)
Call Another D3 within
Context
Send to Dynamic Data
Stream
Dynamic Data Request
Timer
Call Another D3 within
Context
Send to Dynamic Data
Stream
Dynamic Data Request

17. The D3 Model (details)
• Dynamic Data Definition involve the
relationship of three simple concepts
• Pattern
• Condition
• Action
• Ultimately this breaks down into:
• Meta information
• Network definition
• Application to monitor
• Action(s) to take
D3
Meta (1)
D3_Id, Context_ID, Processing Method (Timer, Cache)
Network (01)
Filterby: (protocol {tcp/ip, UDP}
Source/Dest IP, Source/Dest Port (multiple ANDed)
Decode: (variable A=first 8 Bits, var B=next 16 bits, etc….)
Application (01)
Filterby:
Protocol: http
Field: content-type:json, etc.
Content
Example: variable Temperature>56
Action (>1)
Type: Primitive
payload
Header
Type: Procedure
FetchData
Gpsupdate()
syslog
Type: Timed
FetchData
Gpsupdate()
syslog

18. The D3 Model (details)
Sensors
Cloud
DataCenter
D3
Meta (1)
D3_Id, Context_ID, Processing Method (Timer, Cache)
Network (01)
Filterby: (protocol {tcp/ip, UDP}
Source/Dest IP, Source/Dest Port (multiple ANDed)
Decode: (variable A=first 8 Bits, var B=next 16 bits, etc….)
Application (01)
Filterby:
Protocol: http
Field: content-type:json, etc.
Content
Example: variable Temperature>56
Action (>1)
Type: Primitive
payload
Header
Type: Procedure
FetchData
Gpsupdate()
syslog
Type: Timed
FetchData
Gpsupdate()
syslog
{JSON : {
Rules can express:
Predicates and Filters
Data / Information
conversion
Summarization
Pattern Matching
Categorization &
Classification
Event Trigger analysis
Notifications
}}
• Putting it Together

19. www.slideshare.net/kartben/whats-new-at-eclipse-iot-eclipsecon-2014
Data in Motion API as an Open Source Project
• Krikkit initiative originates from Cisco
Data in Motion project
 Promotion of Data in Motion products and
Data in Motion proliferation across industry
 Maintain Leadership in industry for IoT efforts
 IoT does not have many Standards and Open
Source is way to accelerate IoT innovations
with Cisco products
 Krikkit is the public API for Data in Motion
»http://eclipse.org/proposals/technology.krikkit/

20. Create Hello World with
Data in Motion

26. Login To DMo
Login Page
Point your browser to the IP address
unique to your workstation
http://[your unique IP]:8000
Requires an IP address of the DMo
instance, the port number, a context and
the associated password:
IP: 127.0.0.1
Port: 443
Context Name: dmolab
Context Password: dmo123

27. Clean Start
An Empty Context
We need to make sure there are no
pre-existing rules.
A Programmed Context
if your screen looks similar to
the screen below, please click
the Trash Can Icon and Delete
rules.

28. Create a Timer Rule
Polling a Sensor
Most Real life sensors are Asynchronous,
as a result, we need to create a timer rule
that will poll the sensors to retreive the
Data.
A timer rule is a process that runs
periodically (units in millseconds and
above) and estabishes a connection to the
sensor.

29. Verifying the Timer Rule
The JSON Payload
if you want to see what the resulting
JSON code would look like, you can
press the 'see JSON' button.

30. Create an Event Rule
Turn LED ON
Now that we have Setup a Timer Rule and we are
polling the Sensors for Data.
We will need to create an Event Rule to apply a filter to
the data coming back from the sensor and take action
depending on the data value.
• Filter Data
• Turn LED OFF [output Port0] when light Sensor
[input Port1] is Dimmed [Value < 100]

31. Create another Event Rule
Turn LED OFF
Now that we have turned the LED ON when Dimming
the light on the sensor, we would like to turn the LED
back off when the Light Sensor is lit
• Filter Data
• Turn LED OFF [output Port0] when light Sensor
[input Port1] is not Dimmed [Value > 100]

32. Bonus Lab
• Setup a Rule that will turn the LED ON when Pressing on the Pressure Sensor
[Pressure Threshold > 10]
• Setup another Rule that will turn the LED OFF when depressing the Pressure
Sensor [Pressure Threshold < 10]
• Useful Information
• LED is on [Output Port 1]
• LED value 0 Turns OFF
• LED value 1 Turns ON
• Pressure Sensor is on [Input Port 1]

33. Thank you