Powering Dynamic M2M Event Processing with OSGi - W Bowers

© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.
Powering Dynamic M2M Event
Processing with OSGi
Dynamic Complex Event Processing and
OSGi
Hitachi Communication Technologies America, Inc.
6/12/2014
Walt Bowers
Chief Architect OSGi Solutions

Contents
1. The Vs of Big Data
2. Complex Event Processing
3. Dynamic Complex Event Processing
Dynamic Complex Event Processing and OSGi.
Powering Dynamic M2M Event Processing with OSGi
1
4. Demo

1. The Vs of Big Data
2

3© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.
The Vs of Big Data

The missing “V” of Big Data
Extracting VALUE from VIABLE Data
WHERE It Matters and WHEN It Matters
The missing “V” of Big Data

Rise of The Intelligent Device

Key Elements of Connected Intelligence
Intelligent
Devices
Always-on devices
connected to variety
of sensors and
running multiple
software
applications
1
Real-Time
Analytics
High-frequency
data analysis for
instant decision
making and
automation of
information flows
2
Big Data
Integration of data
from connected
devices with
enterprise
applications and
historical data
3

Dynamic Predictive Analytics
• Local analytics and business rules are controlled by
global analytics
– In-flight data analytics on the device
– Near real time response on the device
• Global Analytics for the Big Patterns
– Big Data post processing
– Discover Hidden Patterns/dependencies
• Dynamically Adjust the Rules
– Update new rules to the local device
– Enhances the devices local analytics
• Rinse and Repeat

Transportation Example
Passenger
Counter
M2M Gateway)
1 Location tracking (LBS)
Camera (Normal operation,
local storage; emergencies such
as Amber alert, streaming to
emergency authorities)
Digital signage (Information
and advertising - Location
aware)
Vehicle diagnostics
(Sensors throughout
vehicle)
Route monitoring (Time of
day optimization)
Fraud detection
(Passenger counter,
camera, fare collection)
3
2
4
56
7

2. Complex Event Processing
9

Intelligence Is Real-Time, Event-Based Analytics
Communication
Events
Machine
Events
Security
Events
Environmental
Events
Business
Logic
Events
Complex Events Processing
enables real-time business insights from edge devices

Complex Event Processing (CEP)
• Event-driven Architecture
• A generic data management infrastructure for
processing in-flight data before data is
potentially stored to deliver results in near
real-time
• Programming language for defining rules
• It allows users to
Aggregate/Correlate/Enrich/Detect Patterns
in high speed streaming data

Complex Event Processing (CEP)
Data/Msg.
Feeds
Listener/SINK:
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
CEP Application Container

Event Capture
Data/Msg.
Feeds Listener/SINK:
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
• Events generated at sources
• Adaptor captures event and sends it into the
Event Processing Network

Event Processing
• Events processed in flight
• Merging multiple event sources and types
• Data enrichment by accessing external data sources
(e.g. databases)
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)

Event Dispatch
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
• Processing produces events
• Adaptor receives event and sends it into the
downstream clients

3. Dynamic Complex Event Processing
16

Dynamic Environment
• Devices do not operate in a static environment
• Inputs change
• Knowledge is gained from analytics
• Additional systems want to receive the output

Dynamic Behavior
• Our Complex Event Processing engine needs
to be dynamic
• Ability to change behavior without stopping the
flow
• Allow a higher level system to change the
processing rules

Enter OSGi
Powered by
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi Framework
Java
• Dynamic Modular System for Java
• Mature Lightweight Application
Framework
– Ideal for embedded environments
• Supports Module Lifecycle
– Install/start/stop/uninstall/upgrade
– Remotely manageable
– Versioning
• Services Model
– Advertise and discover services
– Modules are dependent on service
not implementation

OSGi Deployment Environment
OSGi Management System
&
Repository
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi - CEP
OSGi Framework
Java
Remote Device

Dynamically Changing Behavior
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi CEP
&
Repository
Remote Device
Deployed System. Happily processing…

The Data Inputs Change
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi CEP

Update the adaptor
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi CEPOSGi Management System
&
Repository
Remote Device

Process the Events Differently
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi CEP
&
Repository
Remote Device

Forward to additional locations for processing
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi CEP
&
Repository
Remote Device

Happily processing again…
&
Repository
Remote Device
Data/Msg.
User Code
(Plain Java)
Data Feed
Adapters
Process
Events
(CEP)
OSGi CEP

4. Demo
How OSGi and Java enables smart data on M2M aggregators and gateways.
27

Example: JavaOne IoT In Motion

The Components
LCD
Display
Phidget
Temp
Sensor

The Components
• OSGi based
• Continuous Query Language (CQL) for defining rules
• http://www.oracle.com/us/technologies/java/embedded/event-
processing/overview/index.html?ssSourceSiteId=opn
• Arm Based Linux platform
• http://www.raspberrypi.org/
• USB hardware devices
• Open and inexpensive
• http://www.phidgets.com/
• Hitachi’s OSGi Framework

Dynamic Behavior In Action
Start reporting temperature changes below ambient temperature

Change the rules and redeploy remotely

Now reporting temperature changes above ambient
temperature

Hitachi Communication Technologies America, Inc.
6/12/2014
Walt Bowers
Chief Architect OSGi Solutions
Walt.bowers@hitachi-cta.com
END
34

Powering Dynamic M2M Event Processing with OSGi - W Bowers

Volume
3 006 477 107 200 GB added to the “digital universe”
~30% of it generated by machines
42 949 673 000 000 GB – 15 x increase
42 % will be generated by devices
Assuming
2GB/hr it will
take 2.3 billion
years to
download
According to IDC’s “Digital Universe in 2020“ study published in December
2012

Velocity

Variety
•Clickstream Data
•Twitter Feeds
•Facebook Postings
•Web Content
Web and Social Media
•Smart Meters Readings
•RFID Readings
•Oil Rig Sensors
•GP Signals
Machine-to-Machine
•Healthcare Claims
•Telecommunication Call Details Record
•Utility Billing Records
Big Transaction Data
•Facial Recognition
•Genetics
Biometrics
•Call Center Voice Recording
•Email
•Electronic Medical Records
Human Generated

Powering Dynamic M2M Event Processing with OSGi - W Bowers

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Powering Dynamic M2M Event Processing with OSGi - W Bowers