Wireless Sensor Networks Introduction

1
Wireless Sensor NetworksIntroduction

• Instructor Carlos Pomalaza-RáezFall
  2004University of Oulu, Finland

2
What is a Sensor?
Definition A device that produces a measurable
response to a change in a physical or chemical
condition, e.g. temperature, ground composition.
Sensor Networks

• A large number of low-cost, low-power,
  multifunctional, and small sensor nodes
• They benefit from advances in 3 technologies
• digital circuitry
• wireless communication
• silicon micro-machining

3
Wireless Sensor Networks (WSN)
New technologies have reduced the cost, size, and
power of micro-sensors and wireless interfaces
Circulatory Net
EnvironmentalMonitoring
Structural
4
Applications

• Battlefield
• Detection, classification and tracking

• Habitat Monitoring
• Micro-climate and wildlife monitoring
• Examples
• ZebraNet (Princeton)
• Seabird monitoring in Maines Great Duck
  Island(Berkeley Intel)

5
Applications

• Structural, seismic
• Bridges, highways, buildings
• Examples Coronado Bridge San Diego (UCSD),
  Factor Building (UCLA)

• Smart roads
• Traffic monitoring, accident detection, recovery
  assistance
• Examples ATON project (UCSD)

highway
camera
microphone

• Contaminants detection

6
Communication Architecture
Sensing node
Sensor nodes can be data originators and data
routers
Internet
Sink
Manager Node
Sensor nodes
Sensor field
7
Examples of Sensor Nodes
8
Sensor Node Evolution
9
WIRO Platform
WIRO (WIreless Research Object ) is a modular
embedded system developed by the Centre for
Wireless Communications, Oulu, Finland. The
system consists of a set of boards 35 mm x 35 mm
in size. They are

• CPU board - Controls all other WIRO boards and is
  needed in all WIRO stacks. It has an AVR Mega128
  microcontroller running at 7.37 MHz and a 4 Mb
  serial flash memory. The CPU has a 128 kB flash
  memory for programs, 4 kB of SRAM, and 8 ADCs
• RF board It has an RFM model TR3100 radio
  transceiver chip capable of up to 576kbit/s
  speeds. The radio interface on this board is
  configured for 230.4 kbps. Data encoding
  decoding can use the onboard CPLD (Complex
  Programmable Logic Device) or the
  microcontroller on the CPU board. The transceiver
  uses ASK modulation
• Power supply board It has electronics to charge
  a battery pack from the USB bus and to provide
  the other boards with 5V, 3.3V and 1.8V
  voltages
• Sensor board It has 2-axis accelerometer,
  2-axis magnetometer, pressure, temperature and
  humidity sensors
• Prototype board and Test-Pad board

CPU Board
2 Euro coin RF Board
WIRO Box
10
WIRO Power Consumption
RF Board Total Power Consumption
11
WIRO Power Consumption
Sensor Board Total Power Consumption
12
WIRO Power Consumption
13
Typical Features of WSN

• A very large number of nodes, often in the order
  of thousands
• Asymmetric flow of information, from the
  observers or sensor nodes to a command node
• Communications are triggered by queries or events
• At each node there is a limited amount of energy
  which in many applications is impossible to
  replace or recharge
• Almost static topology
• Low cost, size, and weight per node
• Prone to failures
• More use of broadcast communications instead of
  point-to-point
• Nodes do not have a global ID such as an IP
  number
• The security, both physical and at the
  communication level, is more limited than
  conventional wireless networks

14
Design Considerations

• Fault tolerance The failure of nodes should not
  severely degrade the overall performance of the
  network
• Scalability The mechanism employed should be
  able to adapt to a wide range of network sizes
  (number of nodes)
• Cost The cost of a single node should be kept
  very low
• Power consumption Should be kept to a minimum
  to extend the useful life of network.
• Hardware and software constraints Sensors,
  location finding system, antenna, power
  amplifier, modulation, coding, CPU, RAM,
  operating system
• Topology maintenance In particular to cope to
  expected high rate of node failure
• Deployment Pre-deployment mechanisms and plans
  for node replacement and/or maintenance
• Environment At home, in space, in the wild, on
  the roads, etc.
• Transmission media ISM bands, infrared, etc.

15
Node Energy Consumption Projections
10,000 1,000 100 10 1 .1

• Deployed (5W)

Average Power (mW)

• (50 mW)

• (1mW)

2000 2002 2004
16
Node Hardware
In-node processing
Wireless communication with neighboring nodes
Event detection
Acoustic, seismic, magnetic, etc. interface
Electro-magnetic interface
sensors
radio
CPU
battery
Limited battery supply
17
Energy Limitations

• Each sensor node has limited energy supply
• Nodes may not be rechargeable
• Energy consumption in
• Sensing
• Data processing
• Communication (most energy intensive)

20
15
Power (mW)
10
5
0
Sensing
CPU
TX
RX
IDLE
SLEEP
Power consumption of node subsystems
18
TR 1000 Parameters
19
Medusa II Sensor Node (UCLA)
20
Sensor Network Protocol Stack
Power Management How the sensor uses its power,
e.g. turns off its circuitry after receiving a
message.
Application
Mobility Management Detects and register the
movements of the sensor nodes
Task Management
Mobility Management
Transport
Power Management
Network
Task Management Balances and schedules the
sensing tasks given to a specific region
Data Link
Physical
21
Physical Layer

• Frequency selection The use of the industrial,
  scientific, and medical (ISM) bands has been
  often proposed
• Carrier frequency generation and Signal detection
  Depend on the transceiver and hardware design
  constraints which aim for simplicity, low power
  consumption, and low cost per unit
• Modulation
• Binary and M-ary modulation schemes can transmit
  multiple bits per symbol at the expense of
  complex circuitry
• Binary modulation schemes are simpler to
  implement and thus deemed to be more
  energy-efficient for WSN applications
• Low transmission power and simple transceiver
  circuitry make Ultra Wideband (UWB) an attractive
  candidate
• Baseband transmission, i.e. no intermediate or
  carrier frequencies
• Generally uses pulse position modulation
• Resilient to multipath
• Low transmission power and simple transceiver
  circuitry

Application
Transport
Network
Data Link
Physical
22
Physical Layer
Energy consumption minimization is of paramount
importance when designing the physical layer for
WSN in addition to the usual effects such as
scattering, shadowing, reflection, diffraction,
multipath, and fading.
Radio Model Energy Consumption
ETC energy used by the transmitter
circuitry ETA energy required by the
transmitter amplifier to achieve an acceptable
signal to noise ratio or at the receiver
23
Physical Layer
Assuming a linear relationship for the energy
spent per bit by the transmitter and receiver
circuitry
eTC, eTA, and eRC are hardware dependent
parameters
An explicit expression for can be derived as,
24
Physical Layer
(S/N)r minimum required signal to noise ratio
at the receivers demodulator for an acceptable
Eb/N0 NFrx receiver noise figure N0
thermal noise floor in a 1 Hertz bandwidth
(Watts/Hz) BW channel noise bandwidth ?
wavelength in meters a path loss exponent
whose value varies from 2 (for free space) to 4
(for multipath channel models) Gant antenna
gain ?amp transmitter power efficiency Rbit
raw bit rate in bits per second
25
Data Link Layer
The data link layer is responsible for the
multiplexing of data stream, data frame
detection, medium access and error control.
Ensures reliable point-to-point and
point-to-multipoint connections in a
communication network
Application
Transport
Network
Data Link
Physical

• Medium Access Control (MAC) Let multiple
  radios share the same communication media
• Functions
• Local Topology Discovery and Management
• Media Partition By Allocation or Contention
• Provide Logical Channels to Upper Layers

MAC protocol for sensor network must have
built-in power conservation mechanisms, and
strategies for the proper management of node
mobility or failure
26
Wireless MAC Protocols
Wireless MAC protocols can be classified into two
categories, distributed and centralized,
according of the type of network architecture for
which they have been designed. Protocols can be
further classified, based on the mode of
operation, into random access protocols,
guaranteed access protocols, and hybrid access
protocols
Wireless MAC protocols
DistributedMAC protocols
CentralizedMAC protocols
Randomaccess
Randomaccess
Guaranteedaccess
Hybridaccess
Since it is desirable to turn off the radio as
much as possible in order to conserve energy some
type of TDMA mechanism is often suggested for WSN
applications. Constant listening times and
adaptive rate control schemes have also been
proposed.
27
Power Saving Mechanisms

• The amount of time and power needed to wake-up
  (start-up) a radio is not negligible and thus
  just turning off the radio whenever is not being
  used is not necessarily efficient
• The energy characteristics of the start-up time
  should also be taken into account when designing
  the size of the data link packets. The values
  shown in the figure below clearly indicate that
  when the start-up energy consumption is taken
  into account the energy per bit requirements can
  be significantly higher for the transmission of
  short packets than for longer ones

28
Power Saving Mechanisms

• Based on using an ultra low power radio to
  wake-up the neighbors.
• This second radio uses much less power via either
  a low duty cycle or hardware design
• Usually this second radio can only transmit a
  busy tone
• This broadcast tone should not disrupt any
  on-going data transmission, e.g. use a different
  channel

Wake up!
Sleeping nodes
Communicating nodes
29
Error Control
Error control is an important issue in any radio
link. There are two important modes of error
control

• Forward Error Correction (FEC) There is a
  direct tradeoff between the overhead added to the
  code and the number of errors that can be
  corrected. The number of bits in the code word
  impacts the complexity of the receiver and
  transmitter. If the associated processing power
  is greater than the coding gain, then the whole
  process in energy inefficiency.
• Automatic Repeat Request (ARQ) Based on the
  retransmission of packets that have been detected
  to be in error. Packets carry a checksum which is
  used by the receiver to detect errors. Requires a
  feedback channel.

With FEC one pays an a priori battery power
consumption overhead and packet delay by
computing the FEC code and transmitting the extra
code bits. In return one gets a reduced
probability of packet loss. With ARQ one gambles
that the packet will get through and if it does
not one has to pay battery energy and delay due
to the retransmission process. Whether FEC or ARQ
or a hybrid error control system is most energy
efficient will depend of the channel conditions
and the network requirements such as throughput,
delay.
30
Network Layer
Basic issues to take into account when designing
the network layer for a WSN are
Application
Transport
Network

• Power efficiency
• Data centric The nature of the data (interest
  requests and advertisement of sensed data)
  determines the traffic flow
• Data aggregation is useful to manage the
  potential implosion of traffic because of the
  data centric routing
• Rather than conventional node addresses an ideal
  sensor network uses attribute-based addressing,
  e.g. region where humidity is below 5
• Locationing systems, i.e. ability for the nodes
  to establish position information
• Internetworking with external networks via
  gateway or proxy nodes

Data Link
Physical
31
Routing
Phenomenonbeing sensed
Data aggregation takes place here
Sink
Multihop routing common due to limited
transmission range

• Low node mobility
• Power aware
• Irregular topology
• MAC aware
• Limited buffer space

Some routing issues in WSNs
32
Data Aggregation
It is a technique used to solve the problem of
implosion in WSNs. This problem arises when
packets carrying the same information arrive a
node. This situation can happen when more than
one node sense the same phenomenon. This is
different than the problem of duplicate
packets in conventional ad hoc networks. Here it
is the high level interpretation of the data in
the packets is what determines if the packets are
the same. Even for the case when the packets
are deemed to be different they could still be
aggregated into a single packet before the
relaying process continues. In this regard data
aggregation can be considered as data fusion.
Data coming from multiple sensor nodes are
aggregated, if they have about the same
attributes of the phenomenon being sensed, when
they reach a common routing or relaying node on
their way to the sink. In this view the routing
mechanism in a sensor network can be considered
as a form of reverse multicast tree.
Phenomenon being sensed
33
Data Centrality
In data-centric routing, an interest
dissemination is performed in order to assign the
sensing tasks to the sensor nodes. This
dissemination can take different forms such as

• The sink or controlling nodes broadcast the
  nature of the interest, e.g. four legged animals
  of at least 50 Kg in weight

Four-legged animal of at least 50 Kg
Sink
Flow of the request
34
Data Centrality

• Sensor nodes broadcast an advertisement of
  available sensed data and wait for a request from
  the interested sinks

Tiger, tiger, burning bright,In the forest of
the night,What immortal hand or eyeCould frame
thy fearful symmetry?
Flow of the advertisement
Sink
35
Flooding Gossiping
Flooding is a well known technique used to
disseminate information across a network. It is a
simple, easy to implement reactive mechanism that
could be used for routing in WSNs but it has
severe drawbacks such as,

• Implosion When duplicated messages are sent to
  the same node
• Overlap When two or more nodes share the same
  observing region, they may sense the same stimuli
  at the same time. As a result, neighbor nodes
  receive duplicated messages
• Resource blindness Does not take into account
  the available energy resources. Control of the
  energy consumption is of paramount importance in
  WSNs, a promiscuous routing technique such as
  flooding wastes energy unnecessarily

Gossiping is a variation of flooding attempting
to correct some of its drawbacks. Nodes do not
indiscriminately broadcast but instead send a
packet to a randomly selected neighbor who once
it receives the packet it repeats the process. It
is not as simple to implement as the flooding
mechanism and it takes longer for the propagation
of messages across the network.
36
Proposed Routing Techniques
SPIN Sensor Protocols for Information via
Negotiation Attempts to correct the major
deficiencies of classical flooding in particular
the indiscriminate flow of packets with the
related energy waste. The sensor nodes minimize
the amount of traffic and transmissions by first
sending and advertisement of the nature of the
sensed data in a concise manner followed by the
transmission of the actual data to only those
nodes that are interested in receiving it.
ADV

• SPIN messages
• ADV- advertise data
• REQ- request specific data
• DATA- requested data
• Resource management
• Nodes decide their capability of participation in
  data transmissions

A
B
REQ
A
B
DATA
A
B
37
Proposed Routing Techniques
Data Funneling Attempts to minimize the amount
of communication from the sensors to the
information consumer node (sink). It facilitates
data aggregation and tries to concentrate, e.g.
funnel, the packet flow into a single stream from
the group of sensors to the sink. It also
attempts to reduce (compress) the data by taking
advantage that the destination is not that
interested in a particular order of how the data
packets arrive.
Setup phase

• Controller divides the sensing area into regions
• Controller performs a directional flood towards
  each region
• When the packet reaches the region the first
  receiving node becomes a border node and modifies
  the packet (add fields) for route cost
  estimations within the region
• Border node flood the region with modified packet
• Sensor nodes in the region use cost information
  to schedule which border nodes to use

38
Proposed Routing Techniques
Data Funneling Data Communication Phase

• When a sensor has data it uses the schedule to
  choose the border node that is to be used
• It then waits for time inversely proportional to
  the number of hops from the border
• Along the way to the border node, the data
  packets joined together until they reach the
  border node
• The border node collects all packets and then
  sends one packet with all the data back to the
  controller

39
Transport Layer
TCP variants developed for the traditional
wireless networks are not suitable for WSNs where
the notion of end-to-end reliability has to be
reinterpreted due to the sensor nature of the
network which comes with features such as
Application
Transport
Network
Data Link

• Multiple senders, the sensors, and one
  destination, the sink, which creates a reverse
  multicast type of data flow

Physical

• For the same event there is high level of the
  redundancy or correlation in the data collected
  by the sensors and thus there is no need for
  end-to-end reliability between individual sensors
  and the sink but instead between the event and
  the sink
• On the other hand there is need of end-to-end
  reliability between the sink and individual nodes
  for situations such as re-tasking or
  reprogramming
• The protocols developed should be energy aware
  and simple enough to be implemented in the
  low-end type of hardware and software of many WSN
  applications

40
Proposed Transport Layer Techniques
Pump Slowly, Fetch Quickly (PFSQ) Designed to
distribute data from a source node by pacing the
injection of packets into the network at
relatively low speed (pump slowly) which allows
nodes that experience data loss to aggressively
recover missing data from their neighbors (fetch
quickly). Goals of this protocols are

• Ensure that all data segments are delivered to
  the intended destinations with minimum especial
  requirements on the nature of the lower layers
• Minimize number of transmissions to recover lost
  information
• Operate correctly even in situations where the
  quality of the wireless links is very poor
• Provide loose delay bounds for data delivery to
  all intended receivers

PFSQ) has been designed to guarantee
sensor-to-sensor delivery and to provide
end-to-end reliability for control management
distribution from the control node (sink) to the
sensors. It does not address congestion control
41
Proposed Transport Layer Techniques
Event-to-Sink Reliable Transport (ESRT)
Designed to achieve reliable event detection (at
the sink node) with a protocol that is energy
aware and has congestion control mechanisms.
Salient features are

• Self-configuration even in the case of a
  dynamic topology
• Energy awareness sensor nodes are notified to
  decrease their frequency of reporting if the
  reliability level at the sink node are above the
  minimum
• Congestion control takes advantage of the high
  level of correlation between the data flows
  corresponding to the same event
• Collective identification sink only interested
  in the collective information from a group of
  sensors not in their individual reports
• Biased implementation most of the complexity of
  the protocol falls on the sink node minimizing
  the requirements on the sensor nodes

42
Application Layer
There has not been a lot of development on this
layer for WSNs. Some potential applications have
been suggested as listed below but little work of
substance has been reported on any particular
area.
Application
Transport
Network
Data Link

• Sensor Management Protocol (SMP) Carries out
  tasks such as
• Turning sensors on and off
• Exchanging data related to the location finding
  algorithms

Physical

• Authentication, key distribution, and other
  security tasks
• Sensor movement management

• Interest Dissemination Interest is send to a
  sensor or a group of sensors. The interest is
  expressed in terms of an attribute or a
  triggering event.

• Advertisement of Sensed Data Sensor nodes
  advertise sensed data in a concise and
  descriptive way and users reply with requests of
  data they are interested in receiving

43
Distributed Source Coding (DSC)
Aims to take advantage of the high level of
correlation of the data collected by spatially
close sensor nodes in response to an event.
Application Layer
The goal is to remove this redundancy in a
distributed manner. There is the need to be able
to make reliable decisions from the contribution
of a large number of individual unreliable
components with a considerable amount of system
redundancy. Any method that can strip this
redundancy in a distributed manner, e.g.
minimizing inter-node communications, will make
efficient use of the bandwidth and also save
energy. One way to remove the redundancy is by
joint processing based on exchange of information
between the sensors. What is then the price for
minimizing this exchange (to save energy)?
Proposed DSC methods make use of the Slepian-Wolf
coding theorem that states if the joint
distribution quantifying the senor correlation
structure is known then there is no theoretical
loss in performance under certain conditions.
S. Pradhan, K. Ramchandran, Distributed Source
Coding Using Syndromes (DISCUS) Design and
Construction, IEEE Trans. Information Theory,
vol. 49, no. 3, March 2003, pp. 626-643
44
Distributed Source Coding (DSC)
X
Encoder 1
Joint Decoder
Y
Encoder 2
The encoders collaborate and a rate of H(X,Y) is
sufficient
X
Encoder 1
Joint Decoder
Y
Encoder 2
The encoders do not collaborate. The Slepian-Wolf
theorem says that a rate H(X,Y) is also
sufficient provided the decoding of X and Y are
done jointly. It puts more burden on the decoding
side
45
Distributed Source Coding (DSC)
Suppose node A wants to collect the readings from
the other sensor nodes. Lets assume that the
readings are all a 3-binary values, and that the
reading of each child node is correlated with
the one from its parent node in a manner that
the Hamming distance between their readings is no
more than 1 bit. Application of the Slepian-Wolf
theorem results in nodes C and D communicating
their 3-bit readings to their parent, node B,
using 2-bit syndromes. Node B relay these
messages to node A, along with its own 2-bit
syndrome with respect to node A. Node A performs
a successive decoding process by first decoding
its correlated node B (using its own reading) and
then decoding the readings of C and D relative to
the decoded reading of B.
A
B
D
C
46
Cross-Layer Design
Motivations

• Avoid Conflicting Behavior For example a
  routing protocol that favors smaller hops to save
  transmission energy consumption does require a
  proper MAC protocol to coordinate the
  transmissions along the data flow that minimizes
  contention and keeps the transceivers off as much
  as possible
• Remove Unnecessary Layers Some applications do
  not require all layers
• New Paradigm WSNs does not have many of the
  feature of the conventional networks for which
  the OSI protocol layer stack model has proven to
  be successful. Therefore it is quite possible
  that a different mix of layers might prove to be
  more efficient for many WSN applications