Wireless Sensor Networks

1
Wireless Sensor Networks

• Presenter Carlos Pomalaza-Ráez
• carlos_at_ee.oulu.fi
• International Workshop on Wireless Ad Hoc
  NetworksMay 31 June 3, 2004
• University of Oulu, Finland
• http//www.ee.oulu.fi/carlos/IWWAN_04_WSN_Tutoria
  l.ppt

2
Outline

• Introduction
• Examples of sensor networks and sensor nodes
• WIRO A sensor node developed at CWC
• Typical features of WSN
• Design considerations

• Sensor Network Protocol Stack
• Energy consumption model Physical layer
• MAC power saving mechanisms
• Data aggregation and Data centrality
• Transport and Applications layers

3
Outline

• Networking Issues
• MAC
• Routing
• Transport layer
• Summary

• Energy Efficiency Issues
• Node energy model for multihop WSN
• Energy efficient error control mechanisms
• Cooperative communications
• Distributed source coding

4
Introduction
What is a sensor? 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 grouping of low-cost, low-power,
  multifunctional, and small-sized sensor nodes
• They benefit from advances in 3 technologies
• digital circuitry
• wireless communication
• silicon micro-machining

5
Wireless Sensor Networks (WSN)
New technologies have reduced the cost, size, and
power of micro-sensors and wireless interfaces
Circulatory Net
EnvironmentalMonitoring
Structural
6
Some Applications of WSN

• Battlefield
• Detection, classification and
  trackingExamples AWAIRS (UCLA Rockwell
  Science Center)

• Habitat Monitoring Micro-climate and wildlife
  monitoring

• Examples
• ZebraNet (Princeton)
• Seabird monitoring in Maines Great Duck Island
  (Berkeley Intel)

7
Some Applications of WSN

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

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

highway
camera
microphone

• Contaminants detection Examples Multipurpose
  Sensor Program (Boise State University)

8
WSN Communications Architecture
Sensing node
Sensor nodes can be data originators and data
routers
Internet
Sink
Manager Node
Sensor nodes
Sensor field
9
Examples of Sensor Nodes
10
Sensor Node Evolution
11
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
2 Euro coin RF Board
WIRO Box
12
WIRO Power Consumption
RF Board Total Power Consumption
13
WIRO Power Consumption
Sensor Board Total Power Consumption
14
WIRO Power Consumption
15
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

16
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 with
  the 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.

17
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 registers 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
18
Physical Layer

• Frequency selection The use of the industrial,
  scientific, and medical (ISM) bands has often
  been 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
19
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 at the receiver
20
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 eTA can be derived
as,
21
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
22
Data Link Layer
The data link layer is responsible for the
multiplexing of the 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 protocols for sensor networks must have
built-in power conservation mechanisms, and
strategies for the proper management of node
mobility or failure
23
Wireless MAC Protocols
Wireless MAC protocols can be classified into two
categories, distributed and centralized,
according to 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.
24
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 it 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

25
Error Control
Error control is an important issue in any radio
link. In general terms there are two 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 energy
efficient will depend on the channel conditions
and the network requirements such as throughput
and delay.
26
Network Layer
Basic issues to take into account when designing
the network layer for WSNs 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
27
Routing
Phenomenonbeing sensed
Data aggregation takes place here
Sink
Multihop routing is common due to limited
transmission range

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

Some routing issues in WSNs
28
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 at a
node. This situation can happen when more than
one node senses 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 that 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
29
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
30
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
31
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 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 upon
receiving the packet, 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.
32
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 an 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
() W. Heinzelman, J. Kulik, and H. Balakrishnan,
Adaptive Protocols for Information Dissemination
in Wireless Sensor Networks, Proc. 5th ACM/IEEE
Mobicom Conference (MobiCom '99), Seattle, WA,
August, 1999.
33
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
• The border node floods the region with modified
  packet
• Sensor nodes in the region use cost information
  to schedule which border nodes to use

() D. Petrovic, R. C. Shah, K. Ramchandran, and
J. Rabaey, Data Funneling Routing with
Aggregation and Compression for Wireless Sensor
Networks, SNPA 2003, pp. 1-7.
34
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 join 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

35
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
  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

36
Proposed Transport Layer Techniques
Pump Slowly, Fetch Quickly (PSFQ)() 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 protocol are

• Ensure that all data segments are delivered to
  the intended destinations with minimum special
  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
() C-Y Wan, A. T. Campbell, and L.
Krishnamurthy, PSFQ A Reliable Transport
Protocol For Wireless Sensor Networks, First ACM
International Workshop on Wireless Sensor
Networks and Applications (WSNA 2002), Atlanta,
September 28, 2002, pp. 1-11.
37
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 is 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

() Y. Sankarasubramaniam, O. B. Akan, and I. F.
Akyildiz, ESRT Event-to-Sink Reliable Transport
in Wireless Sensor Networks Proceedings of ACM
MobiHoc03, Annapolis, Maryland, USA, June 2003,
pp. 177-188.
38
Application Layer
There has not been as much development for this
layer as for the other layers. Several general
potential areas have been suggested as listed
below but little work of substance has been
reported in 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
• Authentication, key distribution, and other
  security tasks
• Sensor movement management

Physical

• Interest Dissemination Interest is sent 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

39
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(). Proposed DSC methods make
use of the Slepian-Wolf coding theorem that
states that if the joint distribution quantifying
the sensor correlation structure is known then
there is no theoretical loss in performance using
DSC under certain conditions.
() S. Pradhan and K. Ramchandran, Distributed
Source Coding Using Syndromes (DISCUS) Design
and Construction, IEEE Trans. Information
Theory, vol. 49, no. 3, March 2003, pp. 626-643
40
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 decoding of X and Y is done
jointly. It puts more burden on the decoding side
41
Some Words About 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 do not have many of the
  features 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

42
Networking Issues

• Unlike conventional wireless networks, the
  protocols designed for the efficient networking
  of nodes in a WSN have to allow for a closer
  collaboration or awareness among the layers of
  the protocol stack, in particular the first three
  layers

Application
Transport
Network
Data Link

• For example, the MAC protocols must try to have
  the radio transceivers in a sleeping mode as much
  as possible in order to save energy, however if
  the MAC protocol is not jointly designed with the
  routing algorithms (network layer) the overall
  performance of the network could be severely
  degraded, e.g. excessive packet delay

Physical

• Conversely, WSN routing algorithms designed with
  the concepts of data centric and data aggregation
  create special requirements on the underlying MAC
  protocols that should be met for the routing
  mechanisms to work as intended
• These observations can be extended to the design
  of other layers as well since WSNs call for new
  networking paradigms

43
Example of a MAC Protocol for WSN
Sensor-MAC (S-MAC)() Is an energy-aware
protocol that illustrates design considerations
that MAC protocols for WSNs should address.
Assumptions made in the design of S-MAC are
Data Link

• Most communications will be between neighboring
  sensor nodes rather than between a node and a
  base station
• There are many nodes that are deployed in a
  casual, e.g. not precise, manner and as such the
  nodes must be able to self-configure
• The sensor nodes are dedicated to a particular
  application and thus per-node fairness (channel
  access) is not as important as the application
  level performance
• Since the network is dedicated to a particular
  application the application data processing can
  be distributed through the network. This implies
  that data will be processed as whole messages at
  a time in store-and-forward fashion allowing for
  the application of data aggregation techniques
  which can reduce the traffic
• The application can tolerate latency and has long
  idle periods

() W. Ye, J. Heidemann and D. Estrin, An
Energy-Efficient MAC Protocol for Wireless Sensor
Networks, In Proceedings of the 21st
International Annual Joint Conference of the IEEE
Computer and Communications Societies (INFOCOM
2002), New York, NY, USA, June, 2002, pp. 1-10.
44
Sensor-MAC (S-MAC)

• The main features of S-MAC are
• Periodic listen and sleep
• Collision and Overhearing avoidance
• Message passing
• The basic scheme for each node is

• Each node goes into periodic sleep mode during
  which it switches the radio off and sets a timer
  to awake later
• When the timer expires it wakes up and listens to
  see if any other node wants to talk to it
• The duration of the sleep and awake cycles are
  application dependent and they are set the same
  for all nodes
• Requires a periodic synchronization among nodes
  to take care of any type of clock drift

45
Sensor-MAC (S-MAC)

• The listen and awake periods are much longer than
  typical clock drift rates
• The duration of the sleep and awake cycles are
  application dependent and they are set the same
  for all nodes
• Unlike conventional TDMA schemes S-MAC tolerates
  a much looser synchronization among neighboring
  nodes
• Requires a periodic synchronization among nodes
  to take care of any type of clock drift
• Nodes are free to choose their own listen/sleep
  schedules but to reduce control overhead the
  protocol prefers that neighboring nodes are
  synchronized
• Because of the multihop scenario not all
  neighbors can be synchronized, e.g.

Nodes A and B are neighbors but they are
synchronized to their other neighbors, C and D
respectively. Nodes broadcast their schedules
from time to time to ensure that neighboring
nodes can talk to each other even if they have
different schedules. If multiple neighbors want
to talk to a node, they need to contend for the
medium.
46
Sensor-MAC (S-MAC)

• Choosing and Maintaining Schedules
• Each node maintains a schedule table that stores
  schedules of all its known neighbors
• To establish the initial schedule the following
  steps are followed
• A node first listens for a certain amount of time
• If it does not hear a schedule from another node,
  it randomly chooses a schedule and broadcasts its
  schedule immediately
• This node is called a Synchronizer
• If a node receives a schedule from a neighbor
  before choosing its own schedule, it just follows
  this neighbors schedule, i.e. becomes a Follower
  and it waits for a random delay and broadcasts
  its schedule
• If a node receives a neighbors schedule after it
  selects its own schedule, it adopts both
  schedules and broadcasts its own schedule before
  going to sleep
• It is expected that very rarely a node adopts
  multiple schedules since every node tries to
  follow existing schedules before choosing an
  independent one

47
Sensor-MAC (S-MAC)

• Maintaining Synchronization
• Timer synchronization among neighbors is needed
  to prevent clock drift. The updating period can
  be relatively long (tens of seconds)
• Done by periodically sending a SYNC packet that
  only includes the address of the sender and the
  time of its next sleeping period
• Time of next sleep is relative to the moment that
  the sender finishes transmitting the SYNC packet
• A node will go to sleep when the timer fires
• Receivers will adjust their timer counters
  immediately after they receive the SYNC packet
• A node periodically broadcasts a SYNC packet to
  its neighbors even if it has no followers

48
Sensor-MAC (S-MAC)

• Maintaining Synchronization (cont.)
• Listen interval is divided into two parts one
  for receiving SYNC packets and the other for
  receiving RTS (Request To Send)

49
Sensor-MAC (S-MAC)

• Collision and Overhearing Avoidance
• Similar to IEEE 802.11, i.e. use RTS/CTS
  mechanism to address the hidden terminal problem
• Perform carrier sense before initiating a
  transmission
• If a node fails to get the medium, it goes to
  sleep and wakes up when the receiver is free and
  listening again
• Broadcast packets are sent without RTS/CTS
• Unicast packets follow the sequence of
  RTS/CTS/DATA/ACK between the sender and receiver
• Duration field in each transmitted packet
  indicates how long the remaining transmission
  will be, so if a node receives a packet destined
  for another node, it knows how long it has to
  keep silent
• The node records this value in network allocation
  vector (NAV) and sets a timer for it
• When a node has data to send, it first looks at
  NAV. If this value is not zero, then the medium
  is busy (virtual carrier sense)
• The medium is determined as free if both virtual
  and physical carrier sense indicate the medium is
  free
• All immediate neighbors of both the sender and
  receiver should sleep after they hear the RTS or
  CTS packet until the current transmission is over

50
Sensor-MAC (S-MAC)

• Message Passing
• A message is a collection of meaningful,
  interrelated units of data
• Transmitting a long message as a packet is
  disadvantageous as the re-transmission cost is
  high if the packet is corrupted
• Fragmentation into small packets will lead to
  high control overhead as each packet should
  contend using RTS/CTS
• S-MAC fragments message into small packets and
  transmits them as a burst
• Only one RTS and one CTS packets are used
• Every time a data fragment is transmitted the
  sender waits for an ACK from the receiver, if it
  does not arrive the fragment is retransmitted and
  the reservation is extended for the duration of
  the fragment
• Advantages
• Reduces latency of the message
• Reduces control overhead
• Disadvantage
• Node-to-node fairness is reduced, as nodes with
  small packets to send will have to wait until the
  message burst is transmitted

51
Sensor-MAC (S-MAC)

• Implementation
• Testbed
• Rene motes, developed at UCB
• Atmel AT90LS8535 microcontroller with TinyOS
• Uses the TR 1000 from RFM which provides a
  transmission rate of 19.2 Kbps (OOK). Three
  working modes receiving (4.5mA), transmitting
  (12mA, peak), and sleeping (5µA)
• Two type of packets. Fixed size data packets
  with a 6-byte header, a 30-byte payload, and a
  2-byte CRC. Control packets (RTS, CTS, ACK) with
  a 6-byte header and a 2-byte CRC
• MAC protocols implemented
• Simplified IEEE 802.11 DCF
• Message passing with overhearing avoidance (no
  sleep and listen periods). The radio goes to
  sleep when its neighbors are in transmission
• The complete S-MAC. Listen period is 300 ms and
  sleep time can take different values, e.g. 300
  ms, 500 ms, 1 s, etc.

The duration of the carrier sensing is random
within the contention window. The microcontroller
does not go to sleep.
52
Sensor-MAC (S-MAC)

• Topology
• Two-hop network with two sources and two sinks
• Sources periodically generate a sensing message
  which is divided into fragments
• Traffic load is changed by varying the
  inter-arrival period of the messages

53
Sensor-MAC (S-MAC)
54
Sensor-MAC (S-MAC)
55
Sensor-MAC (S-MAC)
56
Sensor-MAC (S-MAC)

• Conclusion
• The S-MAC protocol has good energy conserving
  properties when compared with the IEEE 802.11
  standard
• Comments
• Need of a mathematical analysis
• Need to study the effect of different topologies
• Fragmenting long packets into smaller ones is not
  energy efficient. The argument about more chances
  of the packet being corrupted is not correct
  unless other options such as the use of error
  control coding have also been explored
• Several features behind the S-MAC protocol are
  still captured in the traditional way to do
  business at the Link Layer level, e.g. use of
  RTS/CTS/ACK, etc.
• The protocol does not address the fact that in
  most sensor net applications neighboring nodes
  are activated almost at the same time by the
  event to be sensed and as such they will attempt
  to communicate at approximately the same time.
  There is also a high degree of correlation
  between the data they want to communicate

57
Deep Sleep is Healthy not just for WSN
sol 101-102 (May 10, 2004) ... Opportunity awoke
on sol 102 from its first deep sleep. This set
of activities was initiated to conserve the
energy that ... http//marsrovers.jpl.nasa.gov
58
Routing

• Problem How to efficiently route
• Data from the sensors to the sink and,
• Queries and control packets from the sink to the
  sensor nodes

59
Routing
In addition to the concepts of data aggregation,
data centrality, flooding, and gossiping that
were described earlier it is important to
identify the nature of the WSN traffic, which
will depend on the application. Assuming a
uniform density of nodes, the number of
transmissions can be used as a metric for energy
consumption. Since receiving a packet consumes
almost as much energy as transmitting a packet it
is then important that the MAC protocol limits
the number of listening neighbors in order to
conserve energy.
60
Routing
If N is the number of nodes, Q the number of
queries, and E the number of events, and some
type of flooding mechanism is being used then

• If the number of events is much higher than the
  number of queries it is better to use some type
  of query flooding since the number of
  transmissions is proportional to NQ which is
  much less than NE
• If the number of events is low compared with the
  number of queries it is better to use some type
  of event flooding since now NE is much less than
  NQ
• In both cases it is assumed that the return
  path (for the events or the queries) is built
  during the flooding process
• Other underlying routing mechanisms are
  recommended if the number of events and queries
  are of the same order

61
Directed Diffusion()
A mechanism developed for the case where it is
expected that the number of events is higher than
the number of queries

• Is data-centric in nature
• The sink propagates its queries or interests in
  the form of attribute-value pairs
• The interests are injected by the sink and
  disseminated throughout the network. During this
  process, gradients are set at each sensor that
  receives an interest pointing towards the sensor
  from which the interest was received
• This process can create, at each node, multiple
  gradients towards the sink. To avoid excessive
  traffic along multiple paths a reinforcement
  mechanism is used at each node after receiving
  data, e.g. reinforce
• Neighbor from whom new events are received
• Neighbor who consistently performing better than
  others
• Neighbor from whom most events received
• There is also a mechanism of negative
  reinforcement to degrade the importance of a
  particular path

() C. Intanagonwiwat, R. Govindan, and D.
Estrin, Directed Diffusion A Scalable and
Robust Communication Paradigm for Sensor
Networks, Proc. ACM Mobicom, Boston MA, August
2000, pp. 1-12.
62
Directed Diffusion
Gradient represents both direction towards data
matching and status of demand with desired update
rate
Uses application-aware communication
primitivesexpressed in terms of named data
The choice of path is made locally at every node
for every packet
Consumer of data initiates interest in data with
certain attributes
Nodes diffuse the interest towards producers via
a sequence of local interactions
This process sets up gradients in the network to
draw events matching the interest
Probability ? 1/energy cost
Every route has a probability of being chosen
Collect energy metrics along the way
Four-legged animal
Source
Sink
63
Directed Diffusion
Reinforcement and negative reinforcement used to
converge to efficient distribution
Has built in tolerance to nodes moving out of
range or dying
Source
Sink
64
Directed Diffusion
65
Sensor Protocol for Information via Negotiation
(SPIN)()
A mechanism developed for the case where the
number of queries is higher than the number of
events.

• Use information descriptors or meta-data for
  negotiation prior to transmission of the data
• Each node has its own energy resource manager
  which is used to adjust its transmission activity
• The family of SPIN protocols are
• SPIN-PP For point-to-point communication
• SPIN-EC Similar to SPIN-PP but with energy
  conservation heuristics added to it
• SPIN-BC Designed for broadcast networks. Nodes
  set random timers after receiving ADV and before
  sending REQ to wait for someone else to send the
  REQ
• SPIN-RL Similar to SPIN-BC but with added
  reliability. Each node keeps track of whether it
  receives requested data within the time limit, if
  not, data is re-requested

() J. Kulik, W. Rabiner Heinzelman, and H.
Balakrishnan, Negotiation-Based Protocols for
Disseminating Information in Wireless Sensor
Networks, ACM/IEEE Int. Conf. on Mobile
Computing and Networking, Seattle, WA, Aug. 1999.
66
SPIN-BC
Sensor broadcasts data
It sends meta-data to neighbors
A node senses something interesting
Neighbor sends a REQ listing all of the data it
would like to acquire
Neighbors aggregate data and broadcast (advertise)
meta-data
The process repeats itself across the network
ADV
REQ
DATA
67
SPIN-BC
Advertise meta-data
Advertise
Send data
Send data
Advertise meta-data
I am tired I need to sleep
Send data
Advertise
Send data
Request data
Nodes do need not to participate in the process
Request data
Request data
68
SPIN

• Pros
• Energy More efficient than flooding
• Latency Converges quickly
• Scalability Local interactions only
• Robust Immune to node failures
• Cons
• Nodes always participating
• It does not propose the type of MAC layer needed
  to support an efficient implementation of this
  protocol. The simulation analysis uses a modified
  802.11 MAC protocol

69
Summary

• In recent years a very large number of routing
  algorithm for WSNs have been proposed and
  analyzed
• For most of the proposed techniques the analysis
  has been mainly carried out using simulation
  experiments
• Recent routing algorithms such as the Data
  Funneling() scheme described earlier are more
  in line with the WSN paradigm
• Most if not all of the proposed routing
  algorithms are not supported by a proper MAC
  protocol
• A proper MAC protocol should also be more in tune
  with the important features of the WSN paradigm,
  e.g. asymmetric flow, no need to have to use
  individual node addresses or links, have the
  radio in sleep mode as much as possible, etc.
• Another Data Link Layer aspect that needs more
  research is the impact of error control coding on
  the consumption of energy

() D. Petrovic, R. C. Shah, K. Ramchandran, and
J. Rabaey, Data Funneling Routing with
Aggregation and Compression for Wireless Sensor
Networks, SNPA 2003, pp. 1-7.
70
Spatiotemporal MAC
Rationale To be able to save energy it is
necessary to have a schedule for the radios to be
awake or asleep. This means that there is a
mechanism to distribute this schedule across the
network, e.g. a long range broadcast from the
sink node. There is no reason why the MAC
schedule has to be the same for all nodes. A
spatiotemporal schedule would help to avoid
contention for the channel, allowing time for
data aggregation, and finally forcing the
sensed data to come to the sink
Sink
71
Spatiotemporal MAC
72
Pump Slowly, Fetch Quickly (PSFQ)
A transport protocol for WSNs that attempts to
pace the data from a source node at a relatively
low speed to allow intermediate nodes to fetch
missing data segments from their neighbors, e.g.
hop-by-hop recovery instead of traditional
transport layer end-to-end recovery mechanisms
73
PSFQ
Three basic operations pump, fetch, and report

• Pump
• Node broadcasts a packet to its neighbors every
  Tmin until all the data fragments have been sent
  out
• Neighbors who receive the packet check against
  their local cache discarding any duplicates
• If it is just a new message the packet is
  buffered and the Time-To-Live (TTL) field in the
  header is decreased by 1
• If TTL is not zero and there is no gap in the
  sequence number the packet then is scheduled for
  transmission within a random time Ttx, where

• The random delay before forwarding the message
  allows a downstream node to recover missing
  segments before the next segment arrives from an
  upstream node
• It also allows reducing the number of redundant
  broadcasts of the same packet by neighbors

74
PFSQ

• Fetch
• A node goes into fetch mode when a sequence
  number gap is detected
• In fetch mode a node aggressively sends out NACK
  messages to its immediate neighbors to request
  missing segments
• Since it is very likely that consecutive packets
  are lost because of fading conditions, a window
  is used to specify the range of missing packets
• A node that receives a NACK message checks the
  loss window field against its cache. If found the
  packet is scheduled for transmission at a random
  time in (0, Tr)
• Neighbors cancel a retransmission when a reply
  for the same segment is overheard
• NACK messages are not propagated to avoid message
  implosion
• There is also a proactive fetch mode to take
  care of situations such as when the last segment
  of a message is lost. In this case the node sends
  a NACK for the remaining segments when they have
  not been received after a time period Tpro

75
PFSQ

• Report
• Used to provide feedback data of delivery status
  to source nodes
• To minimize the number of messages, the protocol
  is designed so that a report message travels back
  from a target node to the source nodes
  intermediate nodes can also piggyback their
  report messages in an aggregated manner

• Simulation and experimental evaluation
• When compared to a previously proposed similar
  protocol (Scalable Reliable Multicast) the
  simulation results show that the PFSQ protocol
  has a better performance in terms of error
  tolerance, communications overhead, and delivery
  latency
• The experimental results were obtained by using
  the TinyOS platform on RENE motes. The
  performance results were much poorer than the
  simulation results. The discrepancy is attributed
  to the simulation experiment being unable to
  accurately model the wireless channel and the
  computational demands on the sensor node processor

76
Event-to-Sink Reliable Transport (ESRT)

• In a typical sensor network application the sink
  node is only interested in the collective
  information of the sensor nodes within the region
  of an event and not in any individual sensor data
• Traditional end-to-end reliability requirements
  do not then apply here
• What is needed is a measure of the accuracy of
  the information received at the sink, i.e. and
  event-to-sink reliability

77
ESRT

• The basic assumption is that the sink does all
  the reliability evaluation using parameters that
  are application dependent
• One such parameter is the decision time interval
  t
• At the end of the decision interval the sink
  derives a reliability indicator ri based on the
  reports received from the sensor nodes
• ri is the number of packets received in the
  decision interval
• If R is the number of packets required for
  reliable event detection then ri gt R is needed
  for reliable event detection
• There is no need to identify individual sensor
  nodes but instead there is the need to have an
  event ID
• The reporting rate, f, of a sensor node is the
  number of packets sent out per unit time by that
  node
• The ESRT protocol aims to dynamically adjust the
  reporting rate to achieve the required detection
  reliability R at the sink

78
ESRT
r versus f based on simulation results
n number of source nodes
for f gt fmax the reliability drops because of
network congestion
r increases with the source reporting rate f
79
ESRT Protocol Overview

• The algorithms mainly run on the sink
• Sensor nodes
• Listen to sink broadcasts and update their
  reporting rates accordingly
• Have a simple congestion detection mechanism and
  report to the sink
• The sink
• Computes a normalized reliability measure ?i
  ri /R
• Updates f based on ?i and if f gt fmax or lt
  fmax in order to achieve the desired reliability
• Performs congestion decisions based on feedback
  reports from the source nodes
• Congestion detection
• Uses local buffer level monitoring in sensor
  nodes
• When a routing buffer overflows the node informs
  the sink by setting the congestion notification
  bit in the header packets traveling downstream

80
ESRT Network States
Optimal Operating Region
(Congestion, High reliability)
(No congestion, High reliability)
(Congestion, Low reliability)
(No congestion, Low reliability)
81
ESRT Frequency Update
82
ESRT Summary and Conclusions

• Uses a new paradigm for transport layer
  reliability
• Sensor networks are more interested in event to
  sink reliability than on individual end-to-end
  reliability
• The congestion control mechanism results in
  energy savings
• Analytical performance evaluation and simulation
  results show that the system converges to the
  state OOR regardless of the initial state
• This self configuration property of the protocol
  is very valuable for random and dynamic
  topologies
• Issues still to be addressed are
• Extension to handle concurrent multiple events
• Development of a bi-directional reliable protocol
  that includes the sink-to-sensor transport

83
Energy Efficiency Issues
Node Energy Model()A typical node has a sensor
system, A/D conversion circuitry, DSP and a radio
transceiver. The sensor system is very
application dependent. As discussed earlier the
communication components are the ones who consume
most of the energy on a typical wireless sensor
node. A simple model for a wireless link is shown
below
() H. Karvonen, Z. Shelby, and C.A.
Pomalaza-Ráez, Coding for Energy Efficient
Wireless Embedded Networks, to be presented at
the International Workshop on Wireless Ad Hoc
Networks, May 31 - June 3, 2004, Oulu, Finland
84
Energy Model
The energy consumed when sending a packet of m
bits over a one hop wireless link can be
expressed as,
where, ET energy used by the transmitter
circuitry and power amplifier ER energy used
by the receiver circuitry PT power consumption
of the transmitter circuitry PR power
consumption of the receiver circuitry Tst startu
p time of the transceiver Eencode energy used
to encode Edecode energy used to decode
85
Energy Model
Assuming a linear relationship for the energy
spent per bit at the transmitter and receiver
circuitry ET and ER can be written as,
eTC, eTA, and eRC are hardware dependent
parameters and a is the path loss exponent whose
value varies from 2 (for free space) to 4 (for
multipath channel models). The effect of the
transceiver startup time, Tst, will greatly
depend on the type of MAC protocol used. To
minimize power consumption it is desirable to
have the transceiver in a sleep mode as much as
possible however constantly turning on and off
the transceiver also consumes energy to bring it
to readiness for transmission or reception.
86
Energy Model
An explicit expression for eTA can be derived
as(),
Where, (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 Gant antenna gain ?amp transmitter
power efficiency Rbit raw bit rate in bits per
second
() P. Chen, B. ODea, E. Callaway, Energy
Efficient System Design with Optimum Transmission
Range for Wireless Ad Hoc Networks, IEEE
International Conference on Comm. (ICC 2002),
Vol. 2, pp. 945-952, 28 April -2 May 2002, pp.
945-952.
87
Energy Model
The expression for eTA can be used for those
cases where a particular hardware configuration
is being considered. The dependence of eTA on
(S/N)r can be made more explicit if the previous
equation is written as
This expression shows explicitly the relationship
between eTA and (S/N)r. The probability of bit
error p depends on Eb/N0 which in turns depends
on (S/N)r. Eb/N0 is independent of the data
rate. In order to relate Eb/N0 to (S/N)r, the
data rate and the system bandwidth must be taken
into account, i.e.,
88
Energy Model
where Eb energy required per bit of
information R system data rate BT system
bandwidth ?b signal-to-noise ratio per bit,
i.e., (Eb/N0)
Typical Bandwidths for Various Digital Modulation
Methods
89
Energy Model
Power Scenarios Two possible power scenarios are

• Variable transmission power. In this case the
  radio dynamically adjust its transmission power
  so that (S/N)r is fixed to guarantee a certain
  level of Eb/N0 at the receiver. The transmission
  energy per bit is given by,

Since (S/N)r is fixed at the receiver this also
means that the probability p of bit error is
fixed at the same value for each link.
90
Node Energy Model
Since for most practical deployments d is
different for each link, then (S/N)r will also be
different for each link. This translates to a
different probability of bit error for each
wireless hop.
91
Energy Consumption - Multihop Networks
Consider the following linear sensor array
To highlight the energy consumption due only to
the actual communication process the energy
spent in encoding, decoding, as well as on the
transceiver startup is not considered in the
analysis that follows.
92
Energy Consumption - Multihop Networks
The initial assumption is that there is one data
packet being relayed from the node farthest from
the sink node towards the sink. The total energy
consumed by the linear array to relay a packet of
m bits from node n to the sink is,
It then can be shown that Elinear is minimum when
all the distances dis are made equal to D/n,
i.e. all the distances are equal.
93
Energy Consumption - Multihop Networks
It can also be shown that the optimal number of
hops is,
where
dchar depends only on the path loss exponent a
and on the transceiver hardware dependent
parameters. Replacing the value of dchar in the
expression for Elinear
94
Energy Consumption - Multihop Networks
A more realistic assumption for the linear sensor
array is that there is a uniform probability
along the array for the occurrence of events().
In this case, on the average, each sensor will
detect the same number of events and the
information collected needs to be relayed towards
the sink. Without loss of generality one can
then assume that each node senses one event.
This means that sensor i will have to relay (n-i)
packets from the upstream sensors plus the
transmission of its own packet. The average
energy per bit consumption by the linear array is
then
()Z. Shelby, C.A. Pomalaza-Ráez, and J. Haapola,
Energy Optimization in Multihop Wireless
Embedded and Sensor Networks, to be presented at
the 15th IEEE International Symposium on
Personal, Indoor, and Mobile Radio
Communications, September 5-8, 2004, Barcelona,
Spain.
95
Energy Consumption - Multihop Networks
where ? is a LaGranges multiplier. Taking the
partial derivatives of L with respect to di and
equating to 0 gives,
96
Energy Consumption - Multihop Networks
Thus for a2 the values for di are,
For n10 the next figure shows an equally spaced
sensor array and a linear array where the
distances are computed using the equation above
(a2)
97
Energy Consumption - Multihop Networks
The sensors farther away consume most of their
energy by transmitting over longer distances
whereas sensors closer to the sink consume a
large portion of their energy by relaying packets
from the upstream sensors towards the sink. The
total energy per bit spent by a linear array with
equally spaced sensors is
The total energy per bit spent by a linear array
with optimum separation and a2 is,
98
Energy Consumption - Multihop Networks
For eTC eTR 50 nJ/bit, eTA 100 pJ/bit/m2, and
a 2, the total energy consumption per bit for
D 1000 m, as a function of the number of sensors
is shown below.
99
Energy Consumption - Multihop Networks
The energy per bit consumed at node i for the
linear arrays discussed can be computed using the
following equation. It is assumed that each node
relays packets from the upstream nodes towards
the sink node via the closest downstream
neighbor. For simplicitys sake only one
transmission is used, e.g. no ARQ type mechanism
Energy consumption at each node (n20, D1000 m)
100
Error Control Multihop WSN
For link i assume that the probability of bit
error is pi. Assume a packet length of m bits.
For the analysis below assume that a Forward
Error Correction (FEC) mechanism is being used.
Then call plink(i) the probability of receiving a
packet with uncorrectable errors. Conventional
use of FEC is that a packet is accepted and
delivered to the next stage which in this case is
to forward it to the next node downstream. The
probability of the packet arriving to the sink
node with no errors is then
101
Error Control Multihop WSN
Assume the case where all the dis are the same,
i.e. di D/n. Since variable transmission power
mode is also being assumed the probability of bit
error for each link is fixed and Pc is,
The value of plink will depend on the received
signal to noise ratio as well as on the
modulation method used. For a noncoherent
(envelope or square-law) detector with binary
orthogonal FSK signals in a Rayleigh slow fading
channel the probability of bit error is
Where is the average signal-to-noise ratio.
102
Error Control Multihop WSN
Consider a linear code (m, k, d) is being used.
For FSK-modulation with non-coherent detection
and assuming ideal interleaving the probability
of a code word being in error is bounded by
where wi is the weight of the ith code word and
M2k. A simpler bound is
For the multihop scenario being discussed here
plink PM and the probability of packet error
can be written as
103
Error Control Multihop WSN
The probability of successful transmission of a
single code word is,
Radio parameters used to obtain the results
shown in the next slides
104
Error Control Multihop WSN
The expected energy consumption per information
bit is defined as
Paramete