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

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EENG 460a / CPSC 436 / ENAS 960Networked
Embedded Systems Sensor Networks

• Andreas Savvides
• andreas.savvides_at_yale.edu
• Office AKW 212
• Tel [phone]
• Course Website
• http//www.eng.yale.edu/enalab/courses/eeng460a

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Welcome to EENG 460a!

• Course Overview
• Embedded Systems
• Sensor Networks Applications
• Course details
• Requirements Grading
• Logistics
• Lecture format
• Topics covered

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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

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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

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Applications in All Aspects of Life
Slide from Intel Presentation
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What are Embedded Systems?
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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

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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 gt 50 of inter access
  devices will be such into appliances and not PCs
• In 1997, 96 of internet access devices sold in
  the US were PCs
• 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
• engine emissions control, stability traction
  control, diagnostics, gearless automatic
  transmission
• http//www.howstuffworks.com/car-computer.htm
• An indicator where are the CPUs being used?

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Where are the CPUs?

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

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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

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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
• e.g. Mercedes car with web server
• e.g web servers on wireless cameras
• embedded Java virtual machines
• 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!

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Traditional Software Embedded Systems CPU
RTOS
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Traditional Hardware Embedded Systems ASIC

• ASIC Features
• Area 4.6 mm x 5.1 mm
• Speed 20 MHz _at_ 10 Mcps
• Technology HP 0.5 mm
• Power 16 mW - 120 mW (mode dependent) _at_ 20 MHz,
  3.3 V
• Avg. Acquisition Time 10 ms to 300 ms

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

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Modern Embedded Systems?

• Embedded systems employ a combination of
• application-specific h/w (boards, ASICs, FPGAs
  etc.)
• performance, low power
• s/w on prog. processors DSPs, ?controllers etc.
• flexibility, complexity
• mechanical transducers and actuators

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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

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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?

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Large Diversity in Platforms
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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
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Sensor Node Energy Roadmap
10,000 1,000 100 10 1 .1
Rehosting to Low Power COTS (10x)

• Deployed (5W)

• PAC/C Baseline (.5W)

Average Power (mW)

• (50 mW)

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

• (1mW)

2000 2002 2004
Source ISI DARPA PAC/C Program
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Comparison of Energy Sources
With aggressive energy management, ENS might live
off the environment.
Source UC Berkeley
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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

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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

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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

Localization Time Synchronization
Calibration

• Routing and transport in a Tiered architecture
• Channel/connectivity characterization
• Time synchronization and Localization services
• In Network Processing
• Programming model

In Network Processing
Programming Model
Event Detection
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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

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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

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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

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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

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Two Main Components
Understanding sensor measurements and emerging
behaviors
Architectural optimizations, Small form factors,
low power
Tiered/Heterogenous/Integrated Sensor
Networks Dependencies on both new algorithms and
technological components
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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

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In Network ProcessingDistributed
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 events
• Expensive operations high end sensors or
  sampling
• Robotic sensing, sampling
• Support for Pattern-Triggered Data Collection
• Multi-resolution data storage and retrieval
• Index data for easy temporal and spatial
  searching
• Spatial and temporal pattern matching
• 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

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Sample Layered Architecture
User Queries, External Database
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
Data dissemination, storage, caching
Adaptive topology, Geo-Routing
MAC, Time, Location
Phy comm, sensing, actuation, SP
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Networked Info Mechanical Systems (NIMS)

• 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)

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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

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Em Software environment for developing and
deploying wireless sensor networks
Collaborative Sensor Processing Application
Domain Knowledge
3d Multi- Lateration
State Sync
Reusable Software
(Flexible Interconnects not a strict stack)
Topology Discovery
Acoustic Ranging
Neighbor Discovery
Reliable Unicast
Leader Election
Time Sync
Radio
Sensors
Audio
Hardware
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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

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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

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Course Logistics

• Text
• Principles of Embedded Network Design by
  Kaiser and Pottie Available at TYCO on Broadway
  St
• Wireless 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 1100am 1200pm by
  appointment
• TA Dimitrios Lymberopoulos (dimitrios.lymberopoul
  os_at_yale.edu)

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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

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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

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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

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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

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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

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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

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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 following
• Follow-up discussions on embedded system problems
• Topic presentations
• Guest lecture presentation (e.g Prof.
  Cullurciello sensors, Prof. Koser MEMS, Prof.
  Ganesan Emstar, query processing)

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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

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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/WAMES20200420-20Progr
  am.htm

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Reading for this week

• D. Tennenhouse, Proactive Computing
• Kaiser Pottie, Wireless Sensor Networks
• Articles posted on the course website
• http//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