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Wireless Sensor Networks / IoT: An Overview of Wireless Technologies

Alain-Serge Porret

Yverdon, 19.11.2014

Copyright 2014 CSEM | Wireless Sensor Networks / IoT: Overview of Technologies & Trends | Alain-Serge Porret| Page 1

Context: Opportunity (1)

Wireless Sensor Networks are nothing really new BUT:

• Hardware: Main semiconductor players are interested

• Need new driver for growth after smartphone/tablets

• Software: Main information-management companies are excited

• We are transitioning to an information-driven economy

• Shift from industrial (WSN) to consumer (IoT) applications will drive volume

and refresh offering

• Better Integrated Circuit technologies are available

• Efficient, cheap and powerful chips & modules will follow

• Smartphones and Bluetooth Low-Energy allows for easy configuration and

control of pervasive display-less devices

Introduction


Context: Opportunity (2)

Wireless Sensor Networks are nothing really new BUT:

• Hardware: Main semiconductor players are interested

• Need new driver for growth after smartphone/tablets

• Software: Main information-management companies are excited

• We are transitioning to an information-driven economy

• Shift from industrial (WSN) to consumer (IoT) applications will drive volume

and refresh offering

• Better Integrated Circuit technologies are available

• Efficient, cheap and powerful chips & modules will follow

• Smartphones and Bluetooth Low-Energy allows for easy configuration and

control of pervasive display-less devices

Introduction

Better, more advanced semiconductor processes

Cheaper, more versatile RF chips available (Finally use of modern communication techniques)

Standard vs. Proprietary (Interoperability)

Data management solutions available


Context: Some challenges

However, some things, including physics, did not change:

• Markets and use-cases still unclear in biggest segments

• Wireless communication: it’s still complicated (and unpredictable)

• (And it might get worse…)

• Data collection is one thing, smartly acting upon massive amount of data

another

• Managing and configuring distributed sensors: a nightmare?

• Auto-organization, semantics

• Safety, Security, Privacy

• Battery life towards harvesting

Introduction


A cautionary tale: IoT = WSN v2.0

Introduction


Focus of this presentation

Introduction

Sensors Local Processing

Wireless Modem

Wireless Protocol

Gateways, Concentrators,

& Repeaters

Server Database

Application / User interface

Energy Propagation Environment

Communication

Hardware Communication

Software

Embedded System /

Remote Wireless node


Standard communication model

• Communication hardware (radio) • Frequency bands / Regulations • Modulation • Antenna • Propagation / Interferences

Introduction

• Automatic repetition • Frame management • Packet synchronization • Error checking • Physical addresses management

• Quality of service • Routing / Network Topologies • Adaptation / Translation

• Encryption

Me

dia

La

ye

rs

Ho

st

La

ye

rs


• Propagation & Antennas

• Wireless transceiver and modem

• Analog Pre-Processing, Sensor interfaces & Vision sensors

• Digital signal processing

• Key service blocks (Power management, Wake-up RTC…)

• Platform integration (sensors, harvesters, batteries…)

• Real-Time embedded software

• Transmission protocol

Wireless Sensor Networks / IoT & Related Competencies

Introduction


Optimized design, e.g. for wake-up listening

Energy

time

standard transceiver

WiseNet-SoC

Up to 30x

less energy

Hardware matters…

Wireless Sensors

• Expected battery lifetime: 1 – 10 years

depending on project, possibly

harvesting

• Choice of hardware (chip/component)

options, from generic to fully custom,

will define performances


sources of energy waste at the MAC layer:

idle listening listening when no data is available

overhearing listening to data dedicated to others

oversending emitting while there is no receiver

protocol overhead data that is not directly used for the application

collisions two parties are sending at the same time

Software/Protocols matters…

Wireless Sensors

Wireless communications: It’s complicated… (more than it looks)


(Some) Specific challenges of WSN nodes

• Pervasive, unattended Minimum maintenance, high MTBF or redundancy

• Adaptability to changing conditions

• Energy-constrained Battery-powered or battery-less

• Battery life measured in years, energy-aware behavior

• Low complexity Limited resources: Computing power & memory space

• Optimized embedded code / simple but smart protocols

• Limited information about surroundings locally stored

• Support large number of nodes Self-organization, self-configuration

• Carries important data without supervision Privacy, Security, Encryption

• Coexistence, jamming, reflections (self-jamming)

• Many HW/SW tradeoffs Cost, bulk, range, data rate, energy/bit, latency, …

Wireless communication: It’s complicated…


Wave propagate in circles, or “The world is flat”

• Radio coverage is not at all circular

• Obstacles, topography, fading, …

• Signal strength is only loosely related with

distance


source: D. Kotz et al., 2003

so

urc

e: Kri

s P

iste

r, 2

00

9

1/R2?

1/R4?


Surely, link quality won’t change over time...

• Links fall into 3 categories

• Connected, transitional, disconnected

• Transitional links are often unreliable and

asymmetric (even for static nodes)

Wireless communication: It’s complicated


The only source of packet loss is collisions in the network

• Packet error does not mean packet

collision

• Coexistence: What if there were

other people on earth ????

• Link quality changes

• Often counterproductive

to retry immediately

• At least on same channel

• There are other techniques

than retry to correct errors

• Hidden / exposed terminal

Wireless communication: It’s complicated...

Sources: V. Turau et al., INSS 2006


Only the direct path matters…


source: Kris Pister, 2009


All channels are equivalent…


source: Werb et al., 2005

And it changes

over time!


Some common mitigation techniques

• Boost link budget margins

Higher transmit power (limited by regulations, energy sources)

Better receiver noise figure (limited by physics)

Added redundancy longer packet duration (limited to low data rates)

• Smarter modulations & error correction Complexity

Synchronous demodulation, channel estimation (OFDM)

Forward Error Correction (FEC), Vitterbi, Reed-Solomon, LDPC, BCH

• Diversity Complexity

Repeat information (time diversity)

Multiple antennas ( MIMO)

Change channel (frequency hopping, frequency spreading, multi-mode radio)

Alternate routing path (multi-hop)

Wireless communication: It’s complicated... R

educe e

ntr

opy:

Still

limite

d b

y S

hannon!

A tentative overview of IoT technologies


Long Range

Standards per application type (Only RF, not light or inductive)

IoT Technical Overview

Body Area Networks

Buildings

Industrial

Smart Meters

Automotive

ANT

ANT+

ZigBee BTLE

WiFi

802.11p

UWB

Wireless

M-BUS

802.11ah

LoRa™ SigFox

WeightLess

ISA100

WirelessHART

W1A-PA

Z-Wave

Thread

802.15.4g

802.15.4e/k

KNX

802.15.6 802.15.4j


• Unallocated TV spectrum (white spaces)

• ~ 470 – 800 MHz

• ISM bands

• 315 MHz (US)

• 433 MHz (EU)

• 868 MHz (EU)

• 915 MHz (US)

• 2.4 GHz

• 5.8 GHz

• Ultra-wide band (UWB)

• 3 – 10 GHz

Frequency bands


IEEE

80

2.1

5.4

+ a

… k

BT

Weightless

DASH7

W M-Bus

802.11 / WiFi

802.11ah

ZigBee ANT

Z-Wave LoRa™

ISA100

World

wid

e

Data

Rate

C

overa

ge

Congestion

Penetr

ation o

f

Concre

te/W

ate

r R

angin

g

Ma

x.

Pow

er


Range & data rate (1)


Lon

g R

ange


Range & data rate (2)


Lon

g R

ange


Network types

• Star (WiFi, Bluetooth, LoRa™)

• Tree

Multi-hops, routing

• Cluster-Tree (ZigBee)

Multi-hops, routing

• Peer-to-peer Mesh (WirelessHART, WiseMAC)

Multi-Hops, path diversity support, routing


Cluster-Tree


A word about modulations

• Basic – Frequency and phase modulations (GFSK, BPSK, OQPSK, etc…)

• BTLE, IEEE 802.15.4 (ZigBee)

• OFDM

• WiFi (IEEE 802.11), IEEE 802.15.4g (metering)

• Frequency-Chirp, CSS modulation (chirp spread spectrum)

• Nanotron

• LoRa™ (combined with other technologies)

• UNB (Ultra-narrow band)

• SigFox

• UWB (Ultra-wide band)

• IEEE 802.15.4a



Example of miniature antenna

• Micro SD + 7 mm extension

• Smart phone integration

• Efficiency ≈ 70%


Micro SD

Alumina ε=9.4


Example of modern hardware: Miniature Ultra-Low-Power 2.4GHz Radio IC

Low Power

Low Voltage

Small footprint

Highly integrated

Available under license :

• BLE

• IEEE 802.15.4

• Proprietary

modulations

icyTrx 65/55nm 65 nm CMOS

1.0 V, 5 mA in Rx

-97 dBm @ 1Mb/s

2 dBm output power

0 ext. RF components

IP Area < 2 mm2



Example of state-of-the-art power budget: icycom with WiseMAC

• With Lithium Thionyl Chloride AA (50.5 mm, diameter 14.5 mm, 3.50 USD)

2.3 Ah,

1% per year self discharge,

2.7 ~ 3.6V

• Sleep mode with precise RTC : 4 µA

• 865-928 MHz Rx channel sampling every 250 ms: 4 µA

• 865-928 MHz Rx continuous for 100 kBytes/day : 1 µA

• 865-928 MHz Tx 10 kBytes/day at 25 kbit/s: 1 µA

• Sensors and associated processing: 5 µA

Autonomy of 16.4 years



Trend: Energy Harvesting


Source Source power Harvested power Ambient light

Indoor

Outdoor

0.1 mW/cm²

100 mW/cm²

10 – 20 µW/cm²

10 mW/cm² Vibration/motion

Human

Industrial

0.5 mW @ 1 Hz 1 m/s2 @ 50Hz

1 mW @ 5 Hz 10 m/s2 @ 1 kHz

4 µW/cm²

100 µW/cm² Thermal energy

Human

Industrial

20 mW/cm²

100 mW/cm²

30 µW/cm²

1–10 mW/cm² RF Cell phone 0.3 µW/cm² 0.1 µW/cm²

Generated power by

harvester type

[Vullers 08]

Energy Source Power Density & Performance Source of Information

Acoustic Noise 0.003 μW/cm3 @ 75dB 0.96 μW/cm3 @ 100dB

(Rabaey, Ammer, Da Silva Jr, Patel, & Roundy, 2000)

Temperature Variation 10 μW/cm3 (Roundy, Steingart, Fréchette, Wright, Rabaey, 2004)

Ambient Radio Frequency 1 μW/cm² (Yeatman, 2004) Ambient Light 100 mW/cm² (direct sun)

100 µW/cm² (illuminated office) Available

Thermoelectric 60 µW/cm² (Stevens, 1999) Vibration (micro generator) 4 µW/cm3 (human motion—Hz)

800 µW/cm3 (machines—kHz) (Mitcheson, Green, Yeatman, & Holmes, 2004)

Vibrations (Piezoelectric) 200 μW/cm3 (Roundy, Wright, & Pister, 2002)

Energy density of

energy harvesters, by

source type [Yildiz 09]


Trend: Localization

• Potentially, a dense enough network of sensors

(or gateways) is a way to get information on the

distance between nodes

• Using signal strength

• Or “time-of-flight” information

• And therefore an information on position

• No GPS required (power consumption)

• Potentially works also indoors

• Many applications allowing the tracking of people, goods, devices,…

• Opportunities to improve accuracy with data fusion

• Accelerometers, gyro, compass, altimeter, signal strength/proximity from other

networks…


A few words on some key standards


IEEE 802.15.4 (Low Data-Rate Wireless Personal Area Network)

IEEE 802.15.4 describes only the PHY and MAC layers

Bands: 868 MHz (EU), 915 MHz (US), 2.4 GHz (WW)

Data rate: 20 – 250 kb/s

Modulations: BPSK, OQPSK

Uses direct-sequence Spread Spectrum (DSSS)

Typical sensitivity: -90 .. -100dBm

Frame: Up to 127 bytes, 64-bit MAC addresses

Defines full-function devices (FFD) and or reduced-function devices (RFD)

Network topology: Star (beaconing) or peer-to-peer, no direct mesh support,

synchronization not defined in standard

Supports Carrier Sense Multiple Access/Collision Avoidance

Main standards


IEEE 802.15.4 extensions

Several IoT (home automation/Industrial) protocols are built on IEEE 802.15.4 PHY

• ZigBee: Building automation, industrial (?), remote controllers (RF4CE)

• WirelessHART (IEC 62591) IEEE 802.15.4e: Industrial

• ISA-100 (ANSI/ISA100.11a): Industrial

IEEE 802.15.4a

• Additional PHYs for UWB

• Additional support for chirp spread spectrum (CSS) in 2.4 GHz band

IEEE 802.15.4e Industrial applications (WirelessHART)

IEEE 802.15.4f Active RFID (bi-directional, localization)

IEEE 802.15.4g Smart grid / metering applications

IEEE 802.15.4j Medical Body Area Network (MBAN)

IEEE 802.15.4k Critical Infrastructures Monitoring

Main standards


Integration of WSN over TCP/IP: 6LoWPAN IPv6 over Low power Wireless Personal Area Networks

6LoWPAN is a translation layer that allows IP networking for IEEE 802.15.4 low-power

radio, and therefore direct internet access to wireless sensors with limited resources.

• Compress IPv6 headers to be compatible with IEEE 802.15.4

• Adaptation of packet size

• Address resolution

• Two-phase routing:

• Mesh in PAN space

• Traditional IP above

edge router

• 6LoWPAN achieves

translation

Main standards


Possible future of mesh networks: RPL/RoLL IPv6 Routing Protocol over Low Power and Lossy Network

RPL is a new efficient routing layer that provides mesh networking for IEEE 802.15.4e

low-power radio.

• End-to-end IP based (no translation)

• Promising new alternative to centralized

wirelessHART router and similar

• Compatible with limited-resource nodes

• No need for computation-heavy

coordinator node / self-configuration

• Supports several “sinks”/roots

• Self-repairing

Main standards


ZigBee vs. Bluetooth Low Energy

ZigBee

LAN (scale of a building) with mesh

capability

Low data rate (<= 250 kb/s)

Support sub-GHz bands

Large number of nodes

o “Polite” – Easily jammed

o No clear advantage left today

vs. other technologies

o Higher power consumption

Main standards

BLE (4.0, 4.1)

Today limited to PAN (coverage of

a few meters)

Higher data rate (1 Mb/s)

2.4 GHz

Available in all portable devices

In development (4.2, 5.0)

• Support for mesh networks

• Support for long range

• Audio streaming

• Higher data rates


New health BAN applications


Strong growth expected, not only measurements, but increasingly continuous data

updates for tracking performance, conditions and better diagnosis


BAN standards condidates: Still no clear winner


IETF RFC4944

6LoWPAN

Bluetooth SIG

(BT LE)

ECMA

TC32-PNF

ANT

Continua

Alliance

TC

SmartBAN

TC ERM

e.g. TG30

TC M2M

EP eHealth

…and more

Bluetooth

IEEE 802.15.1

WPAN

IEEE 802.15.4

MBAN

IEEE 802.15.4j

UWB

IEEE 802.15.4a

IEEE 11073 Health informatics

BAN

IEEE 802.15.6

Conclusions


In guise of conclusions… Some thoughts

• Times ripe for major progresses: Both in technological and market terms

• Some hurdle are not (yet) really solved

• Reliability

• Ease of deployment (auto-configuration, smart routing, self-healing network)

• Security, privacy

• Many competing standards CE to provide “tower of Babel” solutions ?

• Some probable winners

• BTLE here to stay (BAN/PAN, gateway for control and configuration)

• Transparent bridge to IP network

• Google! Apple! IBM! Cisco! – Cloud model the only option?

• Some form of Long-Range (urban networks)

• Localization (indoors/outdoors) a significant feature

• No winner-take-all: Co-existence for a long time (i.e. industrial vs. consumer)

Thank you for your attention!

Contact: Alain-Serge Porret [email protected] T +41 32 720 5218 M +41 79 198 6576 F +41 32 720 5768

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