EENG 460a / CPSC 436 / ENAS 960Networked Embedded Systems &

Sensor Networks

Andreas Savvidesandreas.savvides@yale.edu

Office: AKW 212Tel 432-1275

Course Websitehttp://www.eng.yale.edu/enalab/courses/eeng460a

Welcome to EENG 460a!

Course Overview• Embedded Systems• Sensor Networks & Applications

Course details• Requirements & Grading• Logistics• Lecture format• Topics covered

Why take this course?

Learn the basics of embedded systems design Learn about sensor networks and emerging

technologies Undergraduates

• Good opportunity to exercise many of the things you learned in your previous classes

• Learn things that will help you with your senior design projects• Get ready for graduate school or industry

Graduate students• Good breadth topic, good chance to jump-start your research project• Get some hands-on experience on tools and platforms to support your

research

Why networked embedded systems?

Technology is reaching a point where it can significantly impact our everyday lives• Low power processors and radios, MEMs and other sensors

Enable “orthogonal spikes of progress” in many other fields• Medical applications, understanding nature & more• Intelligent environments, smart offices, optimized assembly

lines etc• Many opportunities with existing technologies, many things

up to your imagination An interface to other disciplines

Applications in All Aspects of Life

Slide from Intel Presentation

What are Embedded Systems?

More Examples...

Signal processing systems• radar, sonar, real-time video, set-top boxes, DVD players,

medical equipment, residential gateways Mission critical systems

• avionics, space-craft control, nuclear plant control Distributed control

• network routers & switches, mass transit systems, elevators in large buildings

“Small” systems• cellular phones, pagers, home appliances, toys, smart cards,

MP3 players, PDAs, digital cameras and camcorders, sensors, smart badges

Why do we care?Some Market Tidbits...

Specialized devices and information appliances are replacing the generalist PC• variety of forms: set-top boxes, fixed-screen phones, smart mobile

phones, PDAs, NCs, etc.• IDC predicts that by 2002 > 50% of inter access devices will be such

into appliances and not PCso In 1997, 96% of internet access devices sold in the US were PCso By 2004, unit shipments will exceed those of PCs

Traditional systems becoming dependent on computation systems• Modern cars: up to ~100 processors running complex software

o engine & emissions control, stability & traction control, diagnostics, gearless automatic transmission

o http://www.howstuffworks.com/car-computer.htm An indicator: where are the CPUs being used?

Where are the CPUs?

Estimated 98% of 8 Billion CPUs produced in 2000 used for embedded apps

Where Has CS Focused?Where Has CS Focused?Where Has CS Focused?Where Has CS Focused?

InteractiveInteractiveComputersComputersInteractiveInteractiveComputersComputers

Servers,Servers,etc.etc.

Servers,Servers,etc.etc.

200M200Mper Yearper Year

200M200Mper Yearper Year

In VehiclesIn VehiclesEmbeddedEmbeddedIn RobotsIn Robots

Where Are the Processors?Where Are the Processors?Where Are the Processors?Where Are the Processors?

Look for the CPUs…the Opportunities Will Follow!Look for the CPUs…the Opportunities Will Follow!Look for the CPUs…the Opportunities Will Follow!Look for the CPUs…the Opportunities Will Follow!

Embedded ComputersEmbedded Computers80%80%

Embedded ComputersEmbedded Computers80%80%

8.5B Parts 8.5B Parts per Yearper Year

8.5B Parts 8.5B Parts per Yearper Year

RobotsRobots6%6%

VehiclesVehicles12%12%

DirectDirect2%2%

Source: DARPA/Intel (Tennenhouse)Source: DARPA/Intel (Tennenhouse)

Typical Characteristics of Embedded Systems

Part of a larger system• not a “computer with keyboard, display, etc.”

HW & SW do application-specific function – not G.P.• application is known a priori• but definition and development concurrent

Some degree of re-programmability is essential • flexibility in upgrading, bug fixing, product differentiation, product

customization Interact (sense, manipulate, communicate) with the external

world Never terminate (ideally) Operation is time constrained: latency, throughput Other constraints: power, size, weight, heat, reliability etc. Increasingly high-performance (DSP) & networked

Key Recent Trends

Increasing computation demands• e.g. multimedia processing in set-top boxes, HDTV

Increasingly networked• to eliminate host, and remotely monitor/debug• embedded Web servers

o e.g. Mercedes car with web servero e.g web servers on wireless cameras

• embedded Java virtual machineso e.g. Java ring, smart cards, printers

• cameras, disks etc. that sit directly on networks Increasing need for flexibility

• time-to-market under ever changing standards!

Need careful co-design of h/w & s/w!

“Traditional” Software Embedded Systems = CPU + RTOS

“Traditional” Hardware Embedded Systems = ASIC

A direct sequence spread spectrum (DSSS) receiver ASIC (UCLA)

ASIC FeaturesArea: 4.6 mm x 5.1 mm

Speed: 20 MHz @ 10 Mcps

Technology: HP 0.5 m

Power: 16 mW - 120 mW (mode dependent) @ 20 MHz, 3.3 V

Avg. Acquisition Time: 10 s to 300 s

Modern Embedded Systems?

Embedded systems employ a combination of• application-specific h/w (boards, ASICs, FPGAs etc.)

o performance, low power

• s/w on prog. processors: DSPs, controllers etc.o flexibility, complexity

• mechanical transducers and actuators

Application Specific Gates

Processor Cores

Analog I/O

Memory

DSP Code

Course Goals

Learn the basics of embedded systems• Learn how to program an embedded processor• Learn the basics of embedded OS• Find out about new technologies that are out there• Apply this knowledge in the context of sensor networks

This knowledge allow you• Complete projects from beginning to end in shorter time• Design and implement complex systems to support your

research or industry career• An opportunity to utilize the knowledge you acquired from

previous engineering courses

What about Sensor Networks?

Networks of small devices equipped with sensors Embedded systems become more powerful when

they are networked! From a networking and computing perspective:

• Device-to-device communication instead of person-to-device

Want to have massive distributed systems of low-cost collaborative devices to achieve large tasks• Such as?

Large Diversity in PlatformsC

apabili

tie

s

Size, Power Consumption, Cost

MICA Mote

iBadge

MK - II

StarGate

Design Lineage of Motes

COTS dust prototypes (Kris Pister et al.)

weC Mote (~30 produced) Rene Mote (850+ produced) Dot (1000 produced) Mica node ( 5000+ produced) Mica2 (Current) Spec (Prototype)

Ack: Jason Hill, UC Berkeley

Sensor Node Energy Roadmap

20002000 20022002 20042004

10,0010,0000

1,0001,000

100100

1010

11

.1.1

Ave

rag

e P

ow

er

(mW

)

• Deployed (5W)

• PAC/C Baseline (.5W)

• (50 mW)

(1mW)

Rehosting to Rehosting to Low Power Low Power COTSCOTS (10x)(10x)

-System-On-Chip-System-On-Chip-Adv Power -Adv Power ManagementManagementAlgorithms (50x)Algorithms (50x)

Source: ISI & DARPA PAC/C Program

Traffic/Load/Event Models: Dimensions

Frequency (spatial, temporal)• Commonality of events in time and space

Locality (spatial, temporal)• Dispersed vs. clustered/patterned

Mobility• Rate and pattern• Diversity

Example early adopter applications: CENS Systems under design/construction

Biology/Ecosystems• Microclimate monitoring• Triggered image capture• Canopy-net (Wind River

Canopy Crane Site)

Contaminant Transport• County of Los Angeles

Sanitation Districts (CLASD) wastewater recycling project, Palmdale, CA

Seismic monitoring• 50 node ad hoc, wireless,

multi-hop seismic network• Structure response in USGS-

instrumented Factor Building w/ augmented wireless sensors

Event Detection

Localization &Time Synchronization Calibration

Programming Model

In Network Processing

Systems: Challenges and Services

Resource constrained nodes (energy, comm, storage, cpu)

Irregular deployment and environment

Dynamic network topology Hand configuration will fail

• Scale, variability, maintenance

Routing and transport in a Tiered architecture Channel/connectivity characterization Time synchronization and Localization

services In Network Processing Programming model

Tiered Architecture for scalability, longevity

One size does not fit all….Combine heterogeneous devices as in memory hierarchies• Small battery powered Motes (Mica2 8 bit microcontrollers, TOS,

10s of Kbps, ~600kbytes storage) hosting in situ sensors

• Larger solar powered Microservers (32-bit processors, linux OS, 10s of Mbps, ~100 Mbytes storage)

• Data centric routing/transport at both levels• Pub/sub bus over 802.11 to Databases, visualization, analysis• Tinydiffusion: multihop transport, tasking over duty-cycling MAC

Network Architecture: Can we adapt Internet protocols and “end to end” architecture?

Internet routes data using IP Addresses in Packets and Lookup tables in routers• Humans get data by “naming data” to a search engine• Many levels of indirection between name and IP

address• Works well for the Internet, and for support of Person-

to-Person communication

Embedded, energy-constrained (un-tethered, small-form-factor), unattended systems cant tolerate communication overhead of indirection

Sensors

• Passive elements: seismic, acoustic, infrared, strain,

salinity, humidity, temperature, etc.

• Passive Arrays: imagers (visible, IR), biochemical

• Active sensors: radar, sonar

– High energy, in contrast to passive elements

• Technology trend: use of IC technology for increased

robustness, lower cost, smaller size

– COTS adequate in many of these domains; work remains to be

done in biochemical

What are the challenges?

Sensors are not perfect Sensor measurements are affected by changes in

surrounding conditions and obstacles affect propagation characteristics

Need to understand and combine multipoint measurements

Power consumption always an issue Numerous issues associated with the

programmability and management of sensor devices

Two Main Components

Understanding sensormeasurements and emerging behaviors

Architectural optimizations,

Small form factors, low power

Tiered/Heterogenous/Integrated Sensor Networks

Dependencies on both new algorithms and technological components

How can networked embedded systems scale?

Make them self-configuring• Position and time• Calibrate sensors to a common base

New ways of addressing and administering• Not interested in the temperature reading of sensor X, we

are interested in the temperature of a specific place or room Nodes should autonomously organize themselves into

groups, understand their environments and respond to changes in the environment

Programmability requirements change

In Network Processing:Distributed Representation, Storage, Processing

In network interpretation of spatially distributed data• Statistical or model based filtering

• In network “event” detection and reporting

• Direct queries towards nodes with relevant data

• Trigger autonomous behavior based on eventso Expensive operations: high end sensors or sampling

o Robotic sensing, sampling

Support for Pattern-Triggered Data Collection• Multi-resolution data storage and retrieval

o Index data for easy temporal and spatial searching

• Spatial and temporal pattern matchingo Trigger in terms of global statistics (e.g., distribution)

• Exploit tiered architectures

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Multidisciplinary Nature

Networked embedded systems create opportunities to utilize, blend and create knowledge from other disciplines• Statistical Signal Processing• Information Theory• Communication Theory• Operating Systems and Languages• Databases• VLSI systems and MEMS • Many more…

Sample Layered Architecture

Resource constraints call for more tightly integrated layers

Open Question:

Can we define anInternet-like architecture for such application-specific systems??

In-network: Application processing, Data aggregation, Query processing

Adaptive topology, Geo-Routing

MAC, Time, Location

Phy: comm, sensing, actuation, SP

User Queries, External Database

Data dissemination, storage, caching

NIMS Architecture: Robotic, aerial access to full 3-D environment Enable sample acquisition

Coordinated Mobility Enables self-awareness of

Sensing Uncertainty Sensor Diversity

Diversity in sensing resources, locations, perspectives, topologies

Enable reconfiguration to reduce uncertainty and calibrate

NIMS Infrastructure Enables speed, efficiency Low-uncertainty mobility Provides resource transport for

sustainable presence* (Kaiser, Pottie, Estrin, Srivastava,

Sukhatme, Villasenor)

Networked Info Mechanical Systems (NIMS)*

XYZ Sensor Node

Sensor node created for experimentation

• Low cost, low power, many peripherals

• Integrated accelerometer, light and temperature sensor

Uses an IEEE 802.15.4 protocol• Chipcon 2420 radio

OKI ARM Thumb Processor• 256KB FLASH, 32KB RAM• Max clock speed 58MHz, scales

down to 2MHz• Multiple power management

functions Powered with 3AA batteries & has

external connectors for attaching peripheral boards

Designed at Yale Enalab and Cogent computer systems, will be used as the main platform for the course

Em*: Software environment for developing and deploying wireless sensor networks

Radio

Topology Discovery

Collaborative SensorProcessing Application

NeighborDiscovery

ReliableUnicast

Sensors

LeaderElection

3d Multi-Lateration

Audio

TimeSync

AcousticRanging

StateSync

Domain Knowledge

Reusable Software

Hardware

(Flexible Interconnects;not a strict “stack”)

Em* Supports A Slow Descent into Reality

EmStar allows the same Linux code to be used• In a pure (low-fidelity) simulation• Mostly simulated, but using a real wireless channel• In a real testbed, small-scale but high-visibility• Deployed, in-situ, at scale -- but low visibility

Advantage over traditional simulators: the debugged code itself, not just the high-level concepts, flow from simulation into the real world

To maintain high visibility, we trade scale for reality

Systems Taxonomy: Dimensions

Spatial and Temporal Scale• Sampling interval• Extent• Density (of sensors relative to stimulus)

Variability• Ad hoc vs. engineered system structure• System task variability• Mobility (variability in space)

Autonomy• Multiple sensor modalities• Computational model complexity

Resource constrained• Energy, BW• Storage, Computation

Course Logistics

Text Principles of Embedded Network Design by Kaiser and Pottie –

Available at TYCO on Broadway StWireless Sensor Networks, an Information Processing Approach by Zhao and Guibas – order online

Both texts are on reserve at the Engineering Library Lab: lab and software used for the course available in CO-

40. My office hours Wed 11:00am – 12:00pm & by appointment TA: Dimitrios Lymberopoulos

(dimitrios.lymberopoulos@yale.edu)

Who should take this course?

Senior students • Combine with senior design project• Get some hands-on experience before entering industry or

graduate school• Start early so that you have something to show for when you

start with your applications Graduate students

• Build up background in wireless embedded systems• Use the course to jump-start or support your research

Graduate students will be graded on a different curve and would have slightly different requirements

Requirements and Grading

Class requirements• Attendance is mandatory • Class Discussion & Participation 5%• Homeworks 25%• 2 Midterms 30%• Final Project 40%

Students must have taken EENG 350 or CS 323 or operating systems

Senior or graduate standing Be motivated and be willing to work independently

Course Policies

You cannot reuse the same material from other courses, projects or independent studies for this course

You must turn in the homework at the deadline

Cheating and Plagiarism will not be tolerated

Homeworks and Programming Assignments

Three “basic” programming exercises to get you going with embedded processors

3 homework problems 1 in class presentation in class 2 midterm exams

Course Projects

Opportunity to go deeper in a specific area on your own• Lectures and homework will give you broader coverage, the project will

be more focused Project should have a novelty component

• Does not have to be nobel price but you should add your own flavor to the project

Project proposal due by• Topic suggestions will be online at the end of Week 2 but I also

encourage you to pick your own topic• Come and talk to me about projects

Project goal• Pick something that you can realistically do in a semester• Keep focused and aim for high quality

More about Projects

Project may have one or more components:• A theoretical or evaluation project• Detailed simulation or optimization of a

specific algorithm or protocol• Evaluation or building of new hardware• Data collection and analysis of sensor

measurements• Design new sensor interfaces

Lecture Organization

At the beginning full lecture will cover new material by me

Later on, some of the lectures will be split in 2• First half will cover new material

• Second half will be one of the followingo Follow-up discussions on embedded system problems

o Topic presentations

o Guest lecture presentation (e.g Prof. Cullurciello – sensors, Prof. Koser MEMS, Prof. Ganesan – Emstar, query processing)

Topics and Tentative Lecture Schedule

Week 1: Intro

Week 2: Motivating applications and embedded systems intro

Week 3: Embedded Programming

Weeks 4 –5: Study case: Location Discovery

Week 6: Sensor and Radio Technologies

Week 7: MAC and Routing Protocols

Week 8: Data Aggregation, Storage and Clustering

Week 9: Mobility and Collaborative Control

Week 10: Learning in Sensor Networks

Week 11: Collaborative Signal Processing

Week 12: Security and Data Integrity

Week 13: Misc Topics

Some “neat” Applications

CodeBlue Project at Harvard Networked Cows at Dartmouth & MIT Great Duck Island Habitat Monitoring (initiated by UC

Berkeley) Boundary Estimation at Yale Elder Home Monitoring by Intel

For more details take a look at the WAMES2005 Program at:http://lcawww.epfl.ch/luo/WAMES%202004%20-%20Program.htm

Reading for this week

• D. Tennenhouse, “Proactive Computing”• Kaiser & Pottie, “Wireless Sensor Networks”

Articles posted on the course websitehttp://www.eng.yale.edu/enalab/courses/eeng460a/

To order the book: Go to TYCO and place your order. Ask for EENG460a text, Prof. Savvides

The book will be ready for you to pick up on the next day