The Internet of Things - National Knowledge...

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The Internet of Things Prof. Anurag Kumar Department of Electrical Communication Engg. Indian Institute of Science, Bangalore [email protected]

Transcript of The Internet of Things - National Knowledge...

Page 1: The Internet of Things - National Knowledge Networkworkshop.nkn.in/2013/images/presentation/internet-of... · 2013-10-24 · • 9 May, : The 'internet of things' (IoT) is a major

The Internet of Things

Prof. Anurag Kumar Department of Electrical Communication Engg.

Indian Institute of Science, Bangalore [email protected]

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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

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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

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• 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

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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

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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

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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

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IoT Technology

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Networks in 1988

• LAN and WAN packet networking were still evolving

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Networks Now

• Device to device (D2D) communication

• Ad hoc wireless networks will finally come of age

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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

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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)

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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

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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

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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

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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)

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• 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

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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

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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

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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

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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

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Network Computing 𝑥1 𝑥2 𝑥3 𝑥𝑛

BS

• Signal processing requires computing functions of the data – Say 𝑓(𝑥1, 𝑥2, 𝑥3, ⋯ , 𝑥𝑛); e.g., average, max, etc.

• Send all the values to the base station (BS) – Communication complexity 𝑂 𝑛2

– A common approach in simple low duty cycle applications

• In-network computation of, say, max – E.g., max( ( 𝑥1, 𝑥2 , 𝑥3 , ⋯ , 𝑥𝑛))

– Communication complexity 𝑂(𝑛)

• Need simple distributed algorithms • Resource challenged nodes; lossy and intermittent links

• Distributed clock synchronisation, function computation, optimisation, signal processing, tracking, etc.

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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

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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 objectives (difficult with wireless interconnections)

• Control over resource challenged networks

• Security and anonymity

• Development of common middleware that can be reused across application domains

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Whither IoT?

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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’.”

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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.

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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

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IoT Research at IISc

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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

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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

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IISc’s Robert Bosch Centre for Cyber Physical Systems

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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.

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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

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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.

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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?