Michael Enescu - Cloud + IoT at IEEE

© 2014 Cisco and/or its affiliates. All rights reserved. 1 © 2014 Cisco and/or its affiliates. All rights reserved. 1

Michael Enescu CTO/Head of Open Source Initiatives

March 14, 2013

© 2014 Cisco and/or its affiliates. All rights reserved. 2 2

•  How did we get here: virtualization

•  What is Fog Computing and IoT

•  Where are we going: the “Open” future of IoT

© 2014 Cisco and/or its affiliates. All rights reserved. 3

7.2 6.8 7.6

Rapid Adoption rate of digital infrastructure: 5X faster than electricity and telephony

50 Billion Internet connected things

50

2010 2015 2020

0

40

30

20

10

Bill

ions

of d

evic

es

25

12.5

Inflection point

Timeline

Source: Cisco IBSG, 2011

© 2014 Cisco and/or its affiliates. All rights reserved. 4 *Cisco VNI Study 2012

of “things” are unconnected

99%

Traffic Growth

4x Transition to Cloud*

Mobility

Wi-Fi 50% of Traffic (Video over Mobile Devices)*

The Network Has to

Change

Intelligent

Device Growth

2.5/Person BYOD

Programmable

Mobile and Cloud

Simple

The Network Is the Platform to Connect the Previously Unconnected


Internet of Things

Cloud

Any Device

Video

Virtual

Mobile Packet

Switched Routed

Network as Platform

Bridged

Unconnected DC

PC Voice & Data

Dedicated Fixed

Circuit Shared

The Network Is the Platform to Connect the Previously Unconnected


Centralized -> Decentralized

Decentralized -> Centralized

Fixed, role based model

Easier ops model, new apps

New devices, P2P, M2M

Dedicated compute loads

On-Demand, XaaS, AAA

New PIN’s, improved protocols

Mainframe & Client-Server

Virtualization & Cloud

IoT & Fog

1st 2nd 3rd Moore Nielsen Prediction

Pow

er +

com

pute

reac

h A

AA

Centralized -> Decentralized


•  Storage and Compute declining faster •  Network scales very differently than compute

Sensors will evolve faster than bandwidth Distributed computing more compelling over time

•  Data gravity?

Computation

Storage

Communication

Moore’s and Nielsen’s predictions hold


1.1x109 dp/day Data points generated by sensors .5x1012 B/week

Data generated by an offshore oil rig

1x1012 B/day Data generated by an oil refinery

2x1013 B/hour Data generated by a jet engine

90% of the world’s data created in last 2 years IoT = Small sensors + Big Data + Action

IoT Traffic will grow at 82% CAGR through 2017* brings new dimensions we are barley beginning to sense


•  Networking is changing: 50B+ Devices coming – Immense amount of data No longer about “data transport” Moving to “intelligence about data”: Understanding and taking actions

•  Analytics are changing: Massive data => can not move data fast enough to analytics => move analytics to the data Real-time actions => processing compute closer to the source

•  Consequently three new trends emerge: Dramatic growth in number of applications (+optimization/specialization) for analytics at the edge Dramatic growth in the computational complexity to ETL only essential data information to the core The drive to instrument the “data” to be “open” not closed/locked-in (more on this later)

Traditional model: Store First, Query Later

•  Fetch, •  Analyze, •  Report

!

Generate Actionable Events, Integrate with Policy/Mgmt System

Store raw data or filtered data for further mining.

Data in Motion model: Process First, Store Optional

Input Data

Input Data

Rules can express: •  Predicates and Filters •  Contextual/Dimension Data •  Aggregations •  Pattern Matching •  Categorization & Classification •  Sub-queries …

•  Fetch, •  Analyze, •  Report

Data-base waiting for Queries

Query-base waiting for Data


Time Present

Data Sources

M2M Gateway

Intermediate Server/Gateway

Data Center

Achieved Data

Achieved Data

Achieved Data

Data-Mining, Machine Learning, Pattern Recognition, Cause-Effect, etc.

Future

Predict


Cloud

Device/Smart Object

North/South Flows East/West Flows Fog

Fog Nodes can be multi-tenant Shared, public or private (like cloud)

Highly virtualized environment Secured & isolated tenants, QoS, workload distribution

Mixed ownership & operation Single entity, federation of agencies

Service Mobility Ability to migrate a running instance from cloud to edge

Fog is the distributed, hierarchically organized platform where the Internet meets the physical world at M2M scale


•  Operating System: Linux – by far the most successful open source project ever

•  Virtualization: Hypervisor: xen, kvm, … Network: OpenDaylight Controller, OVS, NFV, …

•  Cloud: Open Stack, Cloud Stack, oVirt, …

•  Applications: …

•  Internet of Things: Eclipse M2M – over a dozen new projects: kura, krikkitt, … Linux Foundation AllSeen Multiple P2P


•  “All IoT Software will be Open Source” •  Why?

Open Source = collaboration (at the largest possible scale) Open Source = credibility Open Source dominates virtualization:

Hypervisor, OS, FS, … Cloud compute is a direct consequence of virtualization

Of the physical machine (compute, memory, storage, I/O), the physical network

Open Source dominates development environments, applications: Mobility, Data, Big Data, Analytics, Security, …

Fog as an extension of the cloud is no exception From gateways, to smart devices, do any device, to sensors Though more work and collaboration is needed

•  And where is Open Source already in the Internet of Things?


@michaelenescu

Everywhere! Thank You

Technology

Michael Enescu - Cloud + IoT at IEEE