Wireless Sensor Networks COE 499 Introduction to Sensor Networks

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Wireless Sensor Networks COE 499Introduction to
Sensor Networks
Courtesy of Dr. Tarek Sheltami (KFUPM-COE)
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Outline

• WSN Basic Components
• Key Design Challenges

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WSN Basic Components
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WSN Basic Components..

• Low-Power Embedded Processor
• Significantly constrained in terms of
  computational power
• Run specialized component-based embedded
  operating system, such as TinyOS
• May include nodes with greater computational
  power due to heterogeneity
• Nodes incorporate advanced low-power design
  techniques, such as efficient sleep modes and
  dynamic voltage scaling to provide significant
  energy savings

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WSN Basic Components..

• Memory/Storage
• Storage in the form of random access and read
  only memory includes both program memory and data
  memory
• The memory and storage on board are often limited
  but most likely to improve over time
• Radio Transceiver
• Low-rate, short range wireless radio (10-100kbps,
  lt100m), but expected to improve over time
• Radio communication is the most power intensive
  operation and hence must incorporate energy
  efficient sleep and wakeup modes

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WSN Basic Components..

• Sensors
• BW is very limited, so only low data rate
  applications are supported
• Due to multi-model sensing, some devices my have
  several sensors on board
• Sensors used are highly dependant on the
  application

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WSN Basic Components..

• Geopositioning System
• Location is very important for sensor measurement
• The simplest way to obtain positioning is to
  pre-configure sensor location at deployment, but
  this is not the case in many applications
• WSN is mostly deployed in ad hoc fashion for
  outdoor operations, where fraction of the sensor
  nodes may be equipped with GPS
• When some nodes equipped with GPS, other nodes
  must obtain their locations indirectly through
  network localization algorithms

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WSN Basic Components..

• Power Sources
• WSN devices are battery powered for flexibility
• Some fixed nodes may be wired to a continuous
  power source in some applications
• Energy harvesting techniques may provide a degree
  of energy renewal in some cases
• The finite battery energy, which is almost always
  the case in WSN, is the most critical resource
  bottleneck in most WSN applications

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WSN Basic Components..

• In a basic data-gathering applications, there is
  a node referred to as the sink to which all data
  from source sensor nodes are directed
• The simplest logical topology for communication
  of gathered data is a single hop star topology,
  where all nodes send their data directly to the
  sink
• In large area, a multi-hop tree structure may be
  used for data-gathering, in this case some nodes
  must act as routers

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Key Design Challenges

• Energy Efficiency
• Responsiveness
• Robustness
• Synergy
• Scalability
• Heterogeneity
• Self-configuration
• Self-optimization Adaptation
• Systematic Design
• Privacy Security

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Design Key Challenges..

• Extended Lifetime
• WSN devices are severely energy constrained due
  to limitation of batteries
• A typical alkaline battery provides about 50
  watt-hours of energy, which lasts to less than a
  month of continuous operation for each node in
  full active mode
• Replacing batteries for a large scale network is
  very expensive and infeasible
• In many applications, it is necessary to provide
  guarantee that a network of unattended wireless
  sensors can remain operational for several years

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Design Key Challenges..

• Extended Lifetime..
• Hardware improvements in battery design and
  energy harvesting will offer only partial
  solutions
• As a result, most protocols are design explicitly
  with energy efficient as a primary goal
• Responsiveness
• One simple solution to extending network lifetime
  is to coordinate the efforts by switching sleep
  and wakeup modes periodically
• Synchronizing such sleep schedules is challenging
  in itself
• Long sleep periods can reduce the responsiveness
  and effectiveness of the sensor

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Design Key Challenges..

• Robustness
• WSN is supposed to provide large-scale and fine
  grained coverage using large numbers of
  inexpensive devices
• However, inexpensive devices can often be
  unreliable and prone to failures, especially if
  deployed in harsh or hostile environment
• Therefore, protocols designers must have a
  built-in mechanisms to provide robustness
• Performance of the network shouldnt be sensitive
  to individual devices failures

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Design Key Challenges..

• Synergy
• Moores law-type advances in technology have
  ensured that devices capabilities in terms of
  processing power, memory, storage, radio
  transceiver performance and even accuracy of
  sensing improve rapidly (given a fixed cost)
• The challenge is to design synergistic protocols
  with ensure that the system as a whole is more
  capable than sum of the capabilities of its
  individual components
• The protocol must provide as efficient
  collaborative use of storage, computation and
  communication resources

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Design Key Challenges..

• Scalability
• Protocols have to be inherently distributed,
  involving localized communication, and sensor
  network must utilize hierarchical architectures
  in order to provide such scalability
• Heterogeneity
• Can have a number of important design
  consequences
• The presence of a small number of devices of
  higher computational capability along with a
  large number of low-capability devices can
  dictate a two-tier cluster-based network
  architecture

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Design Key Challenges..

• Self-configuration
• By design, WSN are unattended distributed systems
• Nodes must have the ability to
• Configure their own network topology
• Localize
• Synchronize
• Calibrate themselves
• Coordinate inter-node communication
• Determine other operating parameters

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Design Key Challenges..

• Self-optimization Adaptation
• Significant uncertainty about operating
  conditions prior to deployment
• Cant optimize network a priori !!
• Nodes must autonomously learn from sensor and
  network measurements over time and use this
  knowledge to improve performance
• Nodes must be able to adapt to dynamic changes in
  the surrounding environment

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Design Key Challenges..

• Systematic Design
• There is a challenging tradeoff between ad hoc
  and more flexible, easy-to-organize design
  methodologies that sacrifice some performance
• Given severe resources constraints in WSN,
  systematic design methodologies are necessitated
  by practical considerations
• Privacy and Security
• The large scale, prevalence and sensitivity of
  information collected by WSN give rise to both
  privacy and security

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Sensor Network Challenges

• Low computational power
• Current mote processors run at lt 10 MIPS (Million
  Instructions Per Second)
• Not enough horsepower to do real signal
  processing
• Memory not enough to store significant data
• Poor communication bandwidth, current radios
  achieve about 10 Kbps per mote
• Note that raw channel capacity is much greater
  Overhead due to CSMA backoff, noise floor
  detection, start symbol, etc.
• 802.15.4 (Zigbee) radios now available at 250
  Kbps
• But with small packets one node can only transmit
  around 25 kbps

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Sensor Network Challenges..

• Limited energy budget
• 2 AA motes provide about 2850 mAh
• Coin-cell Li-Ion batteries provide around 800 mAh
• Solar cells can generate around 5 mA/cm2 in
  direct sunlight
• Must use low duty cycle operation to extend
  lifetime beyond a few days

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Sensor Network Challenges..

• Portable, energy-efficient devices
• End-to-end quality of service
• Seamless operation under context changes
• Context-aware operation
• Secure operation
• Sophisticated services for simple clients

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Unique Aspects

• Number of sensor nodes can be many orders of
  magnitude larger than number of nodes in an ad
  hoc network
• Tens of thousands.
• But individual ID might not be needed.
• Sensors might be very small, cheap, and prone to
  failure.
• Therefore, we need redundancy.
• Extremely limited in power, and must stay
  operative for long time
• Energy harvesting might be considered.
• Sensors might be densely deployed.
• Opportunity for using redundancy to improve the
  robustness of the system

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Unique Aspects..

• Very limited mobility
• Helps with the design of the protocols
• Measurements might be correlated.
• Example measurements of temperature, pressure,
  humidity, etc.
• Volume of transmitted data might be greatly
  reduced.
• For many applications, nodes are randomly
  deployed.
• Thrown by a plane, carried by wind, etc.

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Location-dependent Information

• Changing context
• small movements may cause large changes
• caching may become ineffective
• dynamic transfer to nearest server for a service

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Portability

• Power is key
• long mean-time-to-recharge, small weight, volume
• Risk to data due to easier privacy breach
• network integrated terminals with no local
  storage
• Small user interfaces
• small displays, analog inputs (speech,
  handwriting) instead of buttons and keyboards
• Small storage capacity
• data compression, network storage, compressed
  virtual memory, compact scripts vs. compiled code

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Low Power Energy-awareness

• Battery technology is a hurdle
• Typical laptop 33 display, 33 CPU, 34 rest
• wireless communication and multimedia processing
  incur significant power overhead
• Low power
• circuits, architectures, protocols
• Power management
• Right power at the right place at the right time
• Battery model

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Low Power Energy-awareness..

• There are many means for powering nodes, although
  the reality is that various electrical sources
  are by far the most convenient.
• Technology trends indicate that within the
  lifetime of Embedded Networked Sensors (ENS),
  nodes will likely be available that could live
  off ambient light.
• However, this cannot be accomplished without
  aggressive energy management at many levels
  continuous communications alone would exceed the
  typical energy budgets.

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Sensor Node Energy Roadmap
Source ISI DARPA PAC/C Program
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)

2002 2004 2000
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Battery Technology

• Battery technology has historically improved at a
  very slow pace
• NiCd improved by x2 over 30 years!
• require breakthroughs in chemistry

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Comparison of Energy Sources
Source UC Berkeley
With aggressive energy management, ENS might live
off the environment
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Computation Communication
Energy breakdown for MPEG
Energy breakdown for voice
Decode
Transmit
Decode
Encode
Encode
Receive
Receive
Transmit
Radio Lucent WaveLAN at 2 Mbps
Processor StrongARM SA-1100 at 150 MIPS

• Radios benefit less from technology improvements
  than processors
• The relative impact of the communication
  subsystem on the system energy consumption will
  grow

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Key Issue Resource Awareness
Inherent unpredictability
Solution adaptation
Resource awareness
right resource at the right time and the right
place

• Wireless Backbone Networks
• High traffic load
• Limited available spectrum
• Focus on transmission resources

• Wireless Ad-Hoc Networks
• Unattended operation
• Limited available battery
• Focus on energy resources