Introduction to Internet of Things

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Prof. Dr. Son VuongUniversity of British Columbia

Vancouver, BC CanadaEmail: vuong@cs.ubc.ca or stvuong@gmail.com

VGU20/01/2016

Prof. Dr. Son VuongUniversity of British Columbia

Vancouver, BC CanadaEmail: vuong@cs.ubc.ca or stvuong@gmail.com

VGU20/01/2016

Prof. Dr. Son Vuong’s Bio Sketch BSEE Cal State U, Sacto, MEng CarletonU, PhD, U. Waterloo Lecturer/Assistant Professor, U Waterloo, 1980-82 Joined UBC/CS since 1982 Director of Networks and Internet Computing Lab (NICLab) (Co)Author over 200 papers, supervise 80 MSc/PhD theses Co-edited three books, including “Recent Advances in Distributed

Multimedia Systems” published in 1999 Co-Leader of $30M CAD GISST NCE Proposal (2000) (Co)chair and (Co)organizer of 15 international conferences (CCWC'17,

IEMCON’16, IEMCON’15, AMT’14, iThings’13NCAS’11, Multimedia’08,DMS’08, NOMS’06, DMS'97, ICDCS'95, PSTV'94, FORTE'89, IWPTS'88).

Consultant for the Canadian Government: Department of Communications(DOC), Department of Industry (DOI)

Board of Directors for companies, including Confederal Networks(ConfedNet) and LIVES Mobile Corp.

Professor Emeritus, UBC; Honorary VP, NTTU, Honorary Chair GWS

BSEE Cal State U, Sacto, MEng CarletonU, PhD, U. Waterloo Lecturer/Assistant Professor, U Waterloo, 1980-82 Joined UBC/CS since 1982 Director of Networks and Internet Computing Lab (NICLab) (Co)Author over 200 papers, supervise 80 MSc/PhD theses Co-edited three books, including “Recent Advances in Distributed

Multimedia Systems” published in 1999 Co-Leader of $30M CAD GISST NCE Proposal (2000) (Co)chair and (Co)organizer of 15 international conferences (CCWC'17,

IEMCON’16, IEMCON’15, AMT’14, iThings’13NCAS’11, Multimedia’08,DMS’08, NOMS’06, DMS'97, ICDCS'95, PSTV'94, FORTE'89, IWPTS'88).

Consultant for the Canadian Government: Department of Communications(DOC), Department of Industry (DOI)

Board of Directors for companies, including Confederal Networks(ConfedNet) and LIVES Mobile Corp.

Professor Emeritus, UBC; Honorary VP, NTTU, Honorary Chair GWS

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The University of British Columbia

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The University of British Columbia 108 years old in 2016

A world class university with a spectacular location

Consistently ranked among world’s top 35universities

#1 in CS in Canada, #16 in CS worldwide#33 as global university (US News & World Reporton Education 2015)

Annual budget of $1,600,000,000

Over 50,000 students

12 faculties and 11 schools, 2 campuses in Vancouverand Kelowna

108 years old in 2016

A world class university with a spectacular location

Consistently ranked among world’s top 35universities

#1 in CS in Canada, #16 in CS worldwide#33 as global university (US News & World Reporton Education 2015)

Annual budget of $1,600,000,000

Over 50,000 students

12 faculties and 11 schools, 2 campuses in Vancouverand Kelowna

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The University of British Columbia

World class faculties in medicine, life sciences, law,computer science, engineering and management

One home-grown and one resident Nobel Laureates:

Michael Smith, Nobel Prize in chemistry, 1993

Carl Wieman, Nobel Prize in physics, 2004

David Cheriton: UBC Faculty Alumni, Professor atStanford, a founder of Google. Donnation 2 millionUSD to UBC, 25 million to Waterloo.

World class faculties in medicine, life sciences, law,computer science, engineering and management

One home-grown and one resident Nobel Laureates:

Michael Smith, Nobel Prize in chemistry, 1993

Carl Wieman, Nobel Prize in physics, 2004

David Cheriton: UBC Faculty Alumni, Professor atStanford, a founder of Google. Donnation 2 millionUSD to UBC, 25 million to Waterloo.

Tools/Systems Developed within NICLab

BlueCTBlueCT: A Class Response System (“Clicker”) forinteractive e-learning via laptops and cell phones NEMO: Mobile Intelligent Agent System COOL-BitVampireBitVampire: The first P2P on-demand media

streaming system LePlazaLePlaza: A novel location-aware social network - Web-

based and via cell phones LIVESLIVES (Learning through Interactive Voice Educational

System): A voice-based mobile platform for e-learning.Also LIVESMOBILE and LIVESGEO The GThe G--SystemSystem: uses the Internet of Things and social

networking for advanced society

BlueCTBlueCT: A Class Response System (“Clicker”) forinteractive e-learning via laptops and cell phones NEMO: Mobile Intelligent Agent System COOL-BitVampireBitVampire: The first P2P on-demand media

streaming system LePlazaLePlaza: A novel location-aware social network - Web-

based and via cell phones LIVESLIVES (Learning through Interactive Voice Educational

System): A voice-based mobile platform for e-learning.Also LIVESMOBILE and LIVESGEO The GThe G--SystemSystem: uses the Internet of Things and social

networking for advanced society

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Sensor devices becoming widely available- Programmable devices- Off-the-shelf gadgets/tools

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What does IOT Mean ?Kevin Ashton coined "Internet of Things" phrase todescribe a system where the Internet is connected tothe physical world via ubiquitous sensors

How Ubiquitous?Gartner: “IoT Installed Base Will Grow to 26 Billion Units By2020.” That number might be too low.

Every mobile Every auto

Every door Every room

Every sensor inevery device …in every bed,chair or bracelet... in everyhome, office,building orhospital room …in every city andvillage ... onEarth ...

Every part, onevery parts list

Every sensor inevery device …in every bed,chair or bracelet... in everyhome, office,building orhospital room …in every city andvillage ... onEarth ...

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More “Things” are being connectedHome/daily-life devicesBusiness andPublic infrastructureHealth-care…

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More “Things” are being connected

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Image Courtesy: : CISCO

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SiliconValley10 km

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Smart Shopping

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Personal Computer Ring

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Smart Trash Bucket

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Prosthetic Eye with Camera

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Sign Translation within Video

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NEST Thermostat (3rd Gen)Smart auto-adjustment and remote setting

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A World of IoT …

5G5GNetworkNetwork

Big DataBig DataBody Area NetworkBody Area Network HealthcareHealthcare

5G5GNetworkNetwork

M2MM2M

ObserveandSensing

Gather Learn,Understand,Hypothesize,Optimize &Predict

Change

IoT is a Four Part JourneyNetworks

Sensors,Monitors,Devices,Machines

Cloud, Big Data, Machine Learning,Analytics and Decision Systems, AI

Machine& People

ObserveandSensing Analyze

Learn,Understand,Hypothesize,Optimize &Predict

Interactions among IoT components

The G-System The G-System applies The Internet of Things (IoT) beyond

the Smart City towards an Advanced Society. Aims at enhancing people’s quality of life and achieving a

harmonized society Has built-in Principle of Cause and Effect Collects visible and invisible information from the

environment (all Things) Dynamical update: G-Score (a diachronic metric) Detects opportunities from collected information and

hidden patterns behind the data Connects/disconnects people/G-Nodes and environment

in a “mysterious” (“karmic”) fashion; and suggestsactions/reactions

The G-System applies The Internet of Things (IoT) beyondthe Smart City towards an Advanced Society. Aims at enhancing people’s quality of life and achieving a

harmonized society Has built-in Principle of Cause and Effect Collects visible and invisible information from the

environment (all Things) Dynamical update: G-Score (a diachronic metric) Detects opportunities from collected information and

hidden patterns behind the data Connects/disconnects people/G-Nodes and environment

in a “mysterious” (“karmic”) fashion; and suggestsactions/reactions

G-System vs Ecosystem

G-Systemtransformed

EcoSystem G-SystemGreen, Good, Global, Glory, God

G-Network - High Level Architecture

G gateway

G gateway

G-Network: towards LTE-Beyond (5G)

G gateway

3G base station

Wi-Fi hotspot

Internet

G gateway

G gateway

Cloud Computing

Internet

G-Infrastructure

Logical connection

Context-awareP2P Overlay andG Middleware

Context-awareP2P Overlay andG Middleware

Internet

WifiSensor

RFIDBluetooth

G-Node(Node with G-Power)

Things – Passive Nodes

MANET

A network infrastructure of the G-System

Other Ad HocNetworks

CloudComputing

Context-awareP2P Overlay andG Middleware

Context-awareP2P Overlay andG Middleware

G-Node(Node with G-Power)Nodes fully

connected andgrouped across thenetworks by contexts

G-Node

G-Network Middleware System Architecture

P2P G-Network Middleware APIP2P G-Network Middleware API

G-Network Engine Run-time ModelG-Network Engine Run-time Model

P2P Service LayerP2P Service Layer

Topology-aware and Location-aware DHT-based Routing OverlayTopology-aware and Location-aware DHT-based Routing Overlay

Wi-Fi Direct AdapterWi-Fi Direct Adapter

DHT ServicesPartition Manager

P2P Service LayerP2P Service Layer

Semantic-basedResource Manager

Quality of Services

Multi-hopRouting

G-System Technical Challenges Explosion of data in G-Nodes tracking/monitoring Mobile AdHoc network (MANET) algorithms A context-aware epidemic routing algorithm supporting

various hardware, such as RFID, sensors A content distribution algorithm to exchange/share

content and contexts in a transparent fashion G-Middleware/Framework integrates a MANET and the Internet transparently Running services remotely through migratory agents

G-System engine: rule-based, definition of G-Score, etc. Other challenges: security, fault tolerance, consistency.

Explosion of data in G-Nodes tracking/monitoring Mobile AdHoc network (MANET) algorithms A context-aware epidemic routing algorithm supporting

various hardware, such as RFID, sensors A content distribution algorithm to exchange/share

content and contexts in a transparent fashion G-Middleware/Framework integrates a MANET and the Internet transparently Running services remotely through migratory agents

G-System engine: rule-based, definition of G-Score, etc. Other challenges: security, fault tolerance, consistency.

Our Approach to the IoTTo approach this ultimate goal of ubiquitous

networking, we propose to develop the G-Systemthat integrates numerous novel methods,paradigms and technologies including: The nextThe next--generation RFID (generation RFID (RFIDRFID--G2G2),), Mobile intelligent agents (NEMO, WISEMAN) Context (location)-aware social networking (LePlaza) P2P Interest management and computing (MOPAR) P2P adaptive video streaming (BitVampire) G-Services (LIVES for mobile learning) Security (access, privacy, botnet protection, etc.)

To approach this ultimate goal of ubiquitousnetworking, we propose to develop the G-Systemthat integrates numerous novel methods,paradigms and technologies including: The nextThe next--generation RFID (generation RFID (RFIDRFID--G2G2),), Mobile intelligent agents (NEMO, WISEMAN) Context (location)-aware social networking (LePlaza) P2P Interest management and computing (MOPAR) P2P adaptive video streaming (BitVampire) G-Services (LIVES for mobile learning) Security (access, privacy, botnet protection, etc.)

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Functional Components of an RFID-G2 System

Dr. Min Chen: RA, UBC/CS; Professor, HUST

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Randy H. KatzUC Berkeley

IEMCON 2015: 6th InternationalConference and Workshop onComputing and CommunicationVancouver, Canada15 October 2015

Greener BuildingsHumansHumans BuildingBuilding

PredictiveControllerPredictiveController

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EnvironmentEnvironment

PredictiveController

Predictions based onBuilding Dynamics, Weather, Occupancy, Comfort

Inst

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enta

tion

Inst

rum

enta

tion

Mod

els

Mod

els

Plug LoadsPlug LoadsLightingLightingFacilitiesFacilities

Building

Facility-to-

Building

Facility-to-

Building

Facility-to-

Building

Facility-to-

Building

Facility-to-

Building

Facility-to-

Building

Gen-to-BuildingGen-to-Building

Gen-to-Grid

Gen-to-Grid

uGrid-to-GriduGrid-to-Grid

Building-to-Grid

Building-to-Grid Building-

to-GridBuilding-to-Grid

Energy Networks

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Inst

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enta

tion

Inst

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Mod

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Mod

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ControlsControls

Building OSBuilding OS

FacilitiesFacilities

Inst

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Inst

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enta

tion

Mod

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Mod

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Routing/ControlRouting/Control

Grid OSGrid OS

DemandResponseDemandResponse

Load FollowingLoad FollowingSupply FollowingSupply Following

Grid

Facility-to-

Building

Facility-to-

Building

Facility-to-

Building

Facility-to-

Building

Inst

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tion

Inst

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Mod

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Mod

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ControlControl

CompressorSchedulingCompressorScheduling

TemperatureMaintenanceTemperatureMaintenance

Supply-FollowingLoads

Storage-to-

Building

Storage-to-

Building

Inst

rum

enta

tion

Inst

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enta

tion

Mod

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Mod

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Power-AwareCluster Manager

Power-AwareCluster Manager

Load Balancer/Scheduler

Load Balancer/Scheduler

Web ServerWeb ServerWeb App LogicWeb App Logic

DB/StorageDB/Storage

Machine RoomMR-to-

BuildingMR-to-

Building

uGrid-to-GriduGrid-to-Grid

Software-Defined Building (SDB)

PlanningVisualization

OccupantSatisfaction

Control /Schedule

External

Energy Environment Outdoor EnvironmentPersonal Environment

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BMS

Cyber Physical BuildingTr

ansp

ort

ProcessLoads

OccupantDemand

LegacyInstrumentation &Control Interfaces

PervasiveSensing

Activity/UsageStreams

Local Controllers

OccupantSatisfaction

Multi-ObjectiveModel-Driven

Control

Building Operating Systemand Service

HVA

C

Ele

ctric

al

Sec

urity

, Fau

lt,A

nom

aly

Det

ect &

Man

agem

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Control /Schedule

BIM proxydrvrs

Mapping

SoftZones

Physical Info Bus

privacy-pres. query

PhysicalModels

EmpiricalModels

App

sandbox

Ligh

t

DataBroke

r

SDB a Kind of IoT Platform

Presentation and Analysis InterfacesPresentation and Analysis Interfaces

Analysis, Visualization

DataStoreDataStore

EventDistribu-

tionDiscovery

Localiz-ation

ControllersControllersSchedulerScheduler

Subsampled,Materialized

DataBroke

r

DataBroke

r

1/20/2016 IEMCON 2015 49Sensors, Actuators, Event Streams

DataStoreDataStore

AdaptationAdaptation

DataStoreDataStore

DataStoreDataStore

EventDistribu-

tion

EventDistribu-

tionDiscoveryDiscovery

Localiz-ation

Localiz-ation

ControllersControllers

Data, MetadataLegacy, Archive

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Smart Buildings and the Cloud

LocalControls

LocalControls

SupervisoryControls

SupervisoryControls

ArchiveArchive

LearningAlgorithmsLearning

Algorithms

SpooledInstrumentation

High-levelControls

“Unlimited” storageand processing Global perspective,

integration acrossinstrumentation sources But latency, bandwidth,

connectivity issues

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LocalControls

Human-Centered BeyondInternet-of-(Non-Human)Things

Processing/Analysis

Output

Uncertainty! In

Out

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Sensors Actuators

Input

Uncertainty!Under

actuated!

TheReal

World

Humans

In

Out

IOT: The ChallengesEvery one of those sensors and control points is generatingdata. Often, it's very informative and very private data.Systems are needed to help those devices talk to each other,manage all that data, and enforce proper access control.

Big Data means BIG ChallengesAll of the messaging, management,and access control technologies usedin these large-scale device networksmust be massively scalable.

Open ProtocolsCurrent Internet and software methods are highly modular(APIs), highly distributed (Cloud) and "loosely coupled"(SOA). In today's systems, every LEGO brick comes from adifferent source – and they all still must snap together.This requires open, rapid and safeopen, rapid and safe development methods.

Current Internet and software methods are highly modular(APIs), highly distributed (Cloud) and "loosely coupled"(SOA). In today's systems, every LEGO brick comes from adifferent source – and they all still must snap together.This requires open, rapid and safeopen, rapid and safe development methods.

Open, Rapid and Safe:Open Source and Open StandardsOpen Source and Open Standards

OPEN: Both work well. Easy to join, transparent to review.FAST: Open source methods work well. Rapid iterations andease of contributions promote rapid development. (1)

SAFE: Open standards methods work well. Strong IPR rules,balanced participation, neutral governance = usable work. (2)

OPEN: Both work well. Easy to join, transparent to review.FAST: Open source methods work well. Rapid iterations andease of contributions promote rapid development. (1)

SAFE: Open standards methods work well. Strong IPR rules,balanced participation, neutral governance = usable work. (2)

Key Challengesfor an Open Internet of Things

Lightweight protocols fordevices to work together,communicateUnique and extensibleidentifiers for all thosebillions of devices

Unique and extensibleidentifiers for all thosebillions of devices

Demand for API access andinteroperability

Cybersecurity

Privacy and Policy

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Unintended Consequencesand Security Issues in IOT

Shodan search engine TV camera is watching youHackable home: Lamp (unit with no sec control) Web Camera Baby Monitor Fridge Car in garage Electronic pill reminder (Vitality Pill reminder)

Shodan search engine TV camera is watching youHackable home: Lamp (unit with no sec control) Web Camera Baby Monitor Fridge Car in garage Electronic pill reminder (Vitality Pill reminder)

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(...)

Sky Computing

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The best way to predict thefuture is to invest it

The best way to predict thefuture is to invest it

Q/AQ/A

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