Powering Dynamic M2M Event Processing with OSGi - W Bowers

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As M2M gateways and aggregator devices continue to expand the ever-widening array of sensors and sensor protocols they manage, the number of data events being generated is growing exponentially. Some events need to be acted upon locally; others need to be sent to the cloud for global analysis. Some events require immediate action; other events can wait for later processing. More importantly, the M2M ecosystem needs the ability to dynamically change the local analytics and business rules, depending on the global analytics in the cloud. Using a Raspberry Pi and a temperature monitor, this presentation will demonstrate how OSGi powers dynamic M2M event processing. Bio: Walt is currently the Chief Architect, Software Solutions with Hitachi Communications Technologies America. For the past five years Walt has focused on building an OSGi Ecosystem to deliver advanced services and applications to home networks and M2M devices. He has been involved with Telecommunications and Java since 1996 and has extensive experience in Java and OSGi development both as a developer and as a development manager. Walt has a BS in Mathematics and Computer Science from the University of Georgia and over 25 years of experience in software engineering.

Transcript of 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

© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

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

© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

1. The Vs of Big Data

Dynamic Complex Event Processing and OSGi.

Powering Dynamic M2M Event Processing with OSGi

2

3 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

The Vs of Big Data

4 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

The missing “V” of Big Data

Extracting VALUE from VIABLE Data

WHERE It Matters and WHEN It Matters

The missing “V” of Big Data

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Rise of The Intelligent Device

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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

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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

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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

5 6

7

© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

2. Complex Event Processing

Dynamic Complex Event Processing and OSGi.

9

Powering Dynamic M2M Event Processing with OSGi

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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

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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

12 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Complex Event Processing (CEP)

Data/Msg. Feeds

Listener/SINK: User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

CEP Application Container

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Event Capture

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

CEP Application Container

• Events generated at sources

• Adaptor captures event and sends it into the Event Processing Network

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Event Processing

• Events processed in flight • Merging multiple event sources and types • Data enrichment by accessing external data sources

(e.g. databases)

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

CEP Application Container

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Event Dispatch

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

CEP Application Container

• Processing produces events • Adaptor receives event and sends it into the

downstream clients

© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

3. Dynamic Complex Event Processing

Dynamic Complex Event Processing and OSGi.

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Powering Dynamic M2M Event Processing with OSGi

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Dynamic Environment

• Devices do not operate in a static environment

• Inputs change

• Knowledge is gained from analytics

• Additional systems want to receive the output

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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

19 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Enter OSGi

Powered by

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

CEP Application Container

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

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OSGi Deployment Environment

OSGi Management System &

Repository

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

OSGi - CEP

OSGi Framework

Java

Remote Device

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Dynamically Changing Behavior

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

OSGi CEP

OSGi Management System &

Repository

Remote Device

Deployed System. Happily processing…

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Dynamically Changing Behavior

The Data Inputs Change

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

OSGi CEP

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Dynamically Changing Behavior

Update the adaptor

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

OSGi CEP OSGi Management System &

Repository

Remote Device

24 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Dynamically Changing Behavior

Process the Events Differently

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

OSGi CEP OSGi Management System

& Repository

Remote Device

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Dynamically Changing Behavior

Forward to additional locations for processing

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

OSGi CEP OSGi Management System &

Repository

Remote Device

26 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Dynamically Changing Behavior

Happily processing again…

OSGi Management System &

Repository

Remote Device

Data/Msg. Feeds Listener/SINK:

User Code (Plain Java)

Data Feed Adapters

Process Events (CEP)

OSGi CEP

© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

4. Demo

How OSGi and Java enables smart data on M2M aggregators and gateways. Powering Dynamic M2M Event Processing with OSGi

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28 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Example: JavaOne IoT In Motion

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The Components

LCD Display

Phidget Temp Sensor

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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

31 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Dynamic Behavior In Action

Start reporting temperature changes below ambient temperature

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Dynamic Behavior In Action

Change the rules and redeploy remotely

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Dynamic Behavior In Action

Now reporting temperature changes above ambient temperature

© Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Hitachi Communication Technologies America, Inc.

Dynamic Complex Event Processing and OSGi.

Powering Dynamic M2M Event Processing with OSGi

6/12/2014

Walt Bowers

Chief Architect OSGi Solutions

Walt.bowers@hitachi-cta.com

END

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Appendix

38 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

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

39 © Hitachi Communication Technologies America, Inc. 2014. All rights reserved.

Velocity

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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