The Internet of Things Prof. Anurag Kumar Department of Electrical - - PowerPoint PPT Presentation

The Internet of Things

• Prof. Anurag Kumar

Department of Electrical Communication Engg. Indian Institute of Science, Bangalore anurag@ece.iisc.ernet.in

Cyber Physical Systems (CPS)

• Engineered systems comprising dense

embedded smart sensors (and even actuators)

– in some physical domain (e.g., the environment, large buildings, farms, public utility systems (water/power), networked health care)

• with distributed computing, signal processing,

and inference,

– thus providing unprecedented visualisation

• and even control and actuation (fine grained),
• all interconnected over a communication

network (with usually a substantial wireless component)

Agriculture Instrumented Cities Motes: Smart Sensor Devices

Application Domains

• Smart and green buildings

– Structure, energy, environment

• Networked healthcare

– Mobile patient management, geriatric care

• Smart Cities

– Transportation, pollution, etc.

• Agriculture
• Smart power grids
• Water monitoring and management
• Forest and wildlife

Wireless Blood Oxymeters Endangered Wildlife Forest Fires

• Core body temperature

– Important health metric for neonates

• Remote embedded

monitoring of neonates in rural homes

Monitoring at the Extreme Ends of Life

• Very old people living alone
• Wirelessly connected sensors

attached to common objects that an elderly person uses

• Analytics algorithms analyse

the data on the cloud

• Change in use pattern could

indicate a problem

Courtesy mylively.com

Smart Buildings

• Sensors and actuators in appliances are wirelessly

connected

• Algorithms analyse usage patterns, grid condition, and

power pricing

– Optimise the use of energy

http://www.digikey.com

Devices Per Person

Devices:

• In automobiles
• Communication devices
• Computer and network peripherals
• Household appliances
• Personal care devices and equipment

Mote

Cisco IBSG, April 2011 Culler and Estrin

The Internet of Things (IoT)

Some have begun to call it “The Internet of Everything” The platform for the emerging Cyber Physical Systems (CPS)

Shelby and Bormann 2009

100 Gbps 100 Mbps 100 Kbps Link speeds Resource Rich Resource Challenged

IoT Technology

Networks in 1988

• LAN and WAN packet

networking were still evolving

Networks Now

• Device to device (D2D) communication
• Ad hoc wireless networks will finally come of age

A Smart Wireless Sensor Node

• A smart sensor node is popularly

called a mote (“speck of dust”)

• Sensing: temperature, chemicals,

light, infrared, biosensors, strain, sound, vibration (often using MEMS technology)

• Processing: e.g., 16-bit, 8 Mhz,

48KB flash, 10 KB RAM with a simple OS

• Digital radio: e.g., ISM band; a few

100 Kbps

• Battery: e.g., 100mAh “button”

batteries to 2000mAh (2 AA batteries)

The Berkeley Mote The TelosB Mote A Mote with a PIR Sensor Array The Vigi’Fall Fall Detector Mote

Getting a Multi-Year Lifetime

• Devices need to alternate through sleep-

wake cycles

• Future devices: active : 0.1mA to 1mA;

sleep : .001mA

• Energy scavenging:

– Nodes can draw power from their environment, – Using appropriate devices or mechanisms – e.g., from ambient light, vibrations, or mechanical use

• Need software and algorithms that

further conserve energy

microstrain.com A self-powered wireless light switch (ESE, IISc)

• Today's devices: active : 5 - 10mA; sleep : .001mA
• 1000mAh battery; multiyear lifetime ⇒ 1% active

A wake-up radio (ESE, IISc)

IoT Communication Technology Evolution

• 1980s and 90s: Wireline industrial automation

networks (CAN bus, HART, Fieldbus)

• 1995 onwards: research in wireless sensor networks

– Predominantly academic research

• 2003: IEEE 802.15.4 PHY/MAC standard (“Zigbee”)
• Industry gets interested; adopts the IEEE 802.15.4

PHY

– 2007: WirelessHART

• Frequency hopping TDMA over the IEEE 802.15.4 PHY

– 2009: ISA 100

• 2007: 6LoWPAN RFC4919 (2007) and RFC4944
• 2008: IETF ROLL (Routing Over Low power Lossy links)

working group formed

• 2009: Zigbee Alliance adopts 6LoWPAN and ROLL

The Network Protocol Stack

• IEEE 802.15.4 PHY at 2.4 GHz
• Mesh support
• UDP over IPv6 with 6LoWPAN adaptation layer

IPv6 6LoWPAN IEEE 802.15.4 MAC IEEE 802.15.4 PHY Application UDP IPv6 6LoWPAN IEEE 802.15.4 MAC IEEE 802.15.4 PHY Ethernet MAC Ethernet PHY

Wireline Local Area Network and the Internet

Sensors Sensors Sensors

PHY and MAC

• IEEE 802.15.4 PHY over 2.4GHz (ISM band)

– The most popular PHY standard

• 16 channels over 80MHz

– Each channel of 2MHz, spaced 5MHz apart

• 250Kbps bit rate

– Achieved by a spread spectrum modulation – 2000 chips per second – 62.5 symbols per sec., 32 chips per symbol – 16 PN sequences code 4 bits/symbol

• Thus yielding 62.5 x 4 = 250Kbps
• Medium Access Control (MAC):

– CSMA/CA – TDMA for time critical applications

TI’s Single Chip PHY/MAC for IEEE 802.15.4

Packet Error Rate vs. Received Signal Strength

• CC 2420: receiver sensitivity of -88 dBm achieved

– Noise floor -110 dBm; processing and coding gain: 10 to 11 dB – Link lengths of 10 meters indoors and 30 meters outdoors

• CC 2520: receiver sensitivity of -98 dBm

– Also higher transmit power (5 dBm) – Link lengths of 100 meters outdoors are achievable

103 Bytes over the air (13 B header, 90 B payload)

• Example: 70B packets

– Packet error rate 1%

• Can support a few packets

per second per source

• Non-negligible packet loss

probability

– There is no TCP

• Application level resilience

needed

• Not for applications with

tight delay/loss requirements

IEEE 802.15.4 CSMA-CA MAC Performance

Layer 3: IPv6 and 6LowPAN

• IPv6 can support a large number of uniquely

addressable devices

• 6LoWPAN: an adaptation layer

– Fragmentation and reassembly – Header compression – Mesh routing

IPv6 6LoWPAN IEEE 802.15.4 MAC IEEE 802.15.4 PHY Application UDP IPv6 6LoWPAN IEEE 802.15.4 MAC IEEE 802.15.4 PHY Ethernet MAC Ethernet PHY

Wireline Local Area Network and the Internet

Sensors Sensors Sensors

Routing over Low Power and Lossy Links

• Why can’t MANET protocols be used?
• Link state protocols (e.g., OLSR)

– Very high in overheads; hence not energy conscious – Specially when link states change frequently

• On-demand protocols (AODV, DSR) also not found suitable
• IETF’s ROLL working group

– Routing Over Low-power Lossy-links

• Unreliable and time varying links

– Short term variations

• (coherence time)

– Long term variations

• (e.g., seasonal variations)
• Need to find routes in this resource

challenged setting

RPL: Routing Protocol for Low power lossy links

• Flexible notion of link cost

– E.g., average number of attempts needed to send a packet over that link

• Nodes are dynamically “ranked” in terms of their relative

costs to the sink

• This partial order yields a directed acyclic graph
• On which RPL finds a routing tree
• The cost of each link is constantly updated
• The tree, thus, changes over time as link qualities change
• Based on dynamic shortest

path

• Bellman-Ford type algorithm

Some Experience with RPL

• Network was designed with two

guaranteed paths

– Delivery probability within a delay bound

• Static path routing does not exploit other

paths that appear over time

– 70% delivery (was the target))

• RPL is very dynamic

– Link metric: packet loss rate – Exploits all available paths – Can have large convergence times SmartConnect

100 pkts per source in 25 minutes 5 days of continuous data

Network Computing 𝑦1 𝑦2 𝑦3 𝑦𝑜

BS

• Signal processing requires computing functions of the data

– Say 𝑔(𝑦1, 𝑦2, 𝑦3, ⋯ , 𝑦𝑜); e.g., average, max, etc.

• Send all the values to the base station (BS)

– Communication complexity 𝑃 𝑜2 – A common approach in simple low duty cycle applications

• In-network computation of, say, max

– E.g., max( ( 𝑦1, 𝑦2 , 𝑦3 , ⋯ , 𝑦𝑜)) – Communication complexity 𝑃(𝑜)

• Need simple distributed algorithms
• Resource challenged nodes; lossy and intermittent links
• Distributed clock synchronisation, function computation,
• ptimisation, signal processing, tracking, etc.

Wireline Local Area Network and the Internet

Complete Application Architecture

• Databases

– E.g., patient records

• Analytics and inference

– Is the patient experiencing an episode

• Actuation

– Send the doctor an alert – Activate some embedded actuator

Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Sensor Mote Relay Relay Relay Relay Relay Relay

Analytics in the Cloud

Sensor Mote Sensor Mote

Application Dashboard

Challenges for IoT Applications

• This talk has focused on communications technology for

IoT

• There are many other challenges
• Building provably correct and reliable systems from a

large number of resource challenged embedded sensing/computing devices

• Designing such systems to meet real-time performance
• bjectives (difficult with wireless interconnections)
• Control over resource challenged networks
• Security and anonymity
• Development of common middleware that can be reused

across application domains

Whither IoT?

Major Business Expectations

• 9 May, 2012: “The 'internet of things' (IoT) is a major theme at this

week's CTIA event in New Orleans, as operators and chipmakers race to develop a promising new revenue stream and influence the evolving IP- based ecosystem.”

• 20 Mar, 2012: “Qualcomm Atheros calls its line-up of products for the

segment its `Internet of Everything portfolio’ and expects it to find buyers among smart energy providers, those creating products for the intelligent home, in security and building automation, for remote health and wellness monitoring, and more.”

• 25 Aug, 2011: “Enterprise networking giant Cisco has unveiled a new

compact router in an attempt to bring internet to devices which are normally not connected to the web, like refrigerators and ATMs. The Cisco 819 Integrated Services Router (ISR) Machine-to-Machine Gateway has been designed to bring networking capabilities to non-traditional IP devices, in-line with Cisco’s vision for ‘Internet of Things’.”

A New Job Designation

Job Title Internet of Things Researcher (Qualcomm Research San Diego) Post Date 11/01/2012 (that’s November 1, 2012) Company - Division Qualcomm Technologies, Inc. - Corporate Research & Development Job Area Engineering - Systems Location California - San Diego Job Function Imagine a world in which the most mundane of objects can communicate. Potentially trillions of things can form new networks and operate without direct human input. Join Qualcomm's Research organization, based in San Diego, California to help make this happen. Work on early applications such as Smart Grid, Wireless Health, and Industrial Machine to Machine. (M2M) Design optimizations to enable applications to use WWAN network efficiently in terms of signalling and power constraints. Responsibilities Skills/Experience Internet suite of protocols, such as TCP/IP, IPv4/v6, IP mobility, Ipsec. Solid understanding of wireless protocols and applications. Experience in system and protocol design. Experience in M2M and any of M2M verticals. Understanding of wireless modules. Application performance optimization with intermittent

• connectivity. Protocol design and optimization for low-power devices with limited

processing capabilities. Authentication/authorization, Internet security protocols. Requirements A Master's degree in Electrical Engineering or Computer Science is required; a Doctorate degree is preferred. Work experience is desirable.

While Research Support Continues

• US National Science Foundation (NSF) (in their call for CPS

proposals: 2012-13)

– “CPS will transform the way people interact with engineered systems, just as the Internet transformed the way people interact with information. However, these goals cannot be achieved without rigorous systems engineering. The CPS of tomorrow will need to far exceed the systems of today in capability, adaptability, resiliency, safety, security, and usability.”

• 11 Apr, 2012: Announced at the Intel Developer Forum in China

today, the deal will see around £20 million invested in research and development of the core technologies for powering the Internet of

• Things. It's an obvious move for Intel: as one of the biggest chip

makers around, it can't afford to be caught on the hop if a lucrative new market emerges

IoT Research at IISc

Intrusion Detection for Secure Spaces

• Multidisciplinary, multifaculty R & D project

– ECE, DESE, CSA, and Mech. Engg. Departments

• The project objectives included

– Sensors – Low power electronics – Networking and signal processing algorithms – System software – Security

MEMS Accelerometer Relay Network and Base Station Passive IR Sensor Platform The PIR Virtual Fence

EnviroBats at 7 locations on campus

CPU + GSM Electrochemical Gas sensors (CO2, CO,NOx, SO2)

CNR Rao Circle

ECE

Real time monitoring at fine spatio-temporal scales

• pollution model for the city
• model can be used for

what-if policy experiments

• enables study of impact on

public health (St. Johns Research Institute)

Embedded Pollution Monitoring

IISc’s Robert Bosch Centre for Cyber Physical Systems

 Robert Bosch Foundation in its 125th year set up a 40

million Euro philanthropic fund for education & research

 Of this, half was earmarked for developing a Centre

for Cyber Physical Systems at IISc, over a 10 year period

 Inaugurated by Dr. A. P. J. Abdul Kalam on 8/11/2011  An interdisciplinary centre with a focus on research

(basic and translational), and IP generation, in cyber physical systems, with application domains such as mobility solutions, renewable energy, healthcare, etc.

Linkages and Expectations

Robert Bosch Centre for Cyber Physical Systems

Industry Government Society IISc’s Academic Resources

Problems, Impact

IISc

Robert Bosch Foundation

 Conduct cutting edge scientific work, published in the top venues  Create IP and generate revenue (as per milestones) leading to self- sufficiency  Emerge as one of the top three centres in CPS in the world

First Round Projects: Domains and Laterals

Buildings Water Mobility Healthcare Agriculture Domain Models, Data Processing, Inference, and Control Distributed Algorithms for Inference and Control System Security, Integrity, Resilience to Intrusion Communication Networks (predominantly, Wireless Networks) Interaction with the Physical World: Sensors, Actuators, Energy Harvesting Development Tools: Specification and Verification, Visualisation, etc.

Final Remarks

• Advances in sensors, low power electronics,

wireless communication techniques, low power embedded processing, computing, signal processing, and networking algorithms

– Unprecedented capabilities for embedded sensing, distributed inference, and even control – The basis for IOT and CPS

• Appears essential for upcoming challenges

– Aging populations – Water, energy, and environment management

• Will CPS and IoT technologies mature and get

widely adopted?