Wireless Sensor Networks - PowerPoint PPT Presentation


PPT – Wireless Sensor Networks PowerPoint presentation | free to download - id: 749e1-ZDc1Z


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation

Wireless Sensor Networks


Centre for Wireless Communications. Wireless Sensor Networks. Presenter: Carlos Pomalaza-R ez ... Seabird monitoring in Maine's Great Duck Island (Berkeley & Intel) ... – PowerPoint PPT presentation

Number of Views:1229
Avg rating:3.0/5.0
Slides: 125
Provided by: carlospom
Learn more at: http://www.ee.oulu.fi


Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Wireless Sensor Networks

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

  • 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

  • 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

What is a sensor? A device that produces a
measurable response to a change in a physical or
chemical condition, e.g. temperature, ground
  • 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

Wireless Sensor Networks (WSN)
New technologies have reduced the cost, size, and
power of micro-sensors and wireless interfaces
Circulatory Net
Some Applications of WSN
  • Battlefield
  • Detection, classification and
    trackingExamples AWAIRS (UCLA Rockwell
    Science Center)
  • Habitat Monitoring Micro-climate and wildlife
  • Examples
  • ZebraNet (Princeton)
  • Seabird monitoring in Maines Great Duck Island
    (Berkeley Intel)

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
  • Examples ATON project (UCSD)

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

WSN Communications Architecture
Sensing node
Sensor nodes can be data originators and data
Manager Node
Sensor nodes
Sensor field
Examples of Sensor Nodes
Sensor Node Evolution
Mote Type WeC Rene Rene2 Dot Mica
Date Sep-99 Oct-00 Jun-01 Aug-01 Feb-02
Microcontroller (4MHz) Microcontroller (4MHz) Microcontroller (4MHz) Microcontroller (4MHz) Microcontroller (4MHz) Microcontroller (4MHz)
Type AT90LS8535 AT90LS8535 ATMega163 ATMega163 ATMega103/128
Prog. mem. (KB) 8 8 16 16 128
RAM (KB) 0.5 0.5 1 1 4
Communication Communication Communication Communication Communication Communication
Radio RFM TR1000 RFM TR1000 RFM TR1000 RFM TR1000 RFM TR1000
Rate (Kbps) 10 10 10 10 10/40
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 Power Consumption
CPU Board CPU Board CPU Board CPU Board CPU Board
CPU Active CPU Active CPU Sleep CPU Sleep
CPLD 3 mA/3.3 V 9.9 mW 0.01 mA/3.3 V 0.033 mW
AT mega128 15 mA/3.3 V 49.5 mW 0.04 mA/3.3 V 0.13 mW
Flash-memory 4 mA/3.3 V 13.2 mW 0.002 mA/3.3 V 0.007 mW
RF Board RF Board RF Board RF Board RF Board RF Board RF Board
Tx Tx Rx Rx Sleep Sleep
CPLD 3mA/3.3V 9.9mW 3mA/3.3V 9.9mW 0.01mA/3.3V 0.033mW
RF-Transceiver 10mA/3.3V 33mW 5.8mA/3.3V 19mW 0.7µA/3.3V 0.0023mW
Other Circuitry 0.5mA/5V 2.5mW 0.5mA/5V 2.5mW 0.5mA/5V 2.5mW
RF Board Total Power Consumption
WIRO Power Consumption
Sensor Board Sensor Board Sensor Board Sensor Board Sensor Board
Active Active Sleep Sleep
Magnetometer 20mA/5V 100mW 0 0
Accelerometer 0.6mA/3.3V 2mW 0.6mA/3.3V 2mW
Humidity Sensor 0.55mA/3.3V 2mW 0.3µA/5V 0.0015mW
Pressure Sensor 6mA/5V 30mW 0 0
CPLD 3mA/3.3V 9.9mW 0.01mA/3.3V 0.033mW
Amplifier 0.5mA/5V 2.5mW 0.5mA/5V 2.5mW
Sensor Board Total Power Consumption
WIRO Power Consumption
Power Supply Board Power Supply Board Power Supply Board Power Supply Board Power Supply Board
Connected to the USB-bus Connected to the USB-bus Not Connected to the USB-bus Not Connected to the USB-bus
CPLD 1mA/3.3V 3.3mW 0.01mA/3.3V 0.033mW
EEPROM 1mA/5V 5mW 0.005mA/5V 0.025mW
USB 25mA/5V(from USB) 125mW 0.2mA/5V 1mW
Estimated Operation Time on Battery Power Estimated Operation Time on Battery Power Estimated Operation Time on Battery Power Estimated Operation Time on Battery Power
ton /tsleep Avg Power Avg Battery Current Op Time/550mAh
100 325.3mW 104mA 5.3h
10 44.2mW 14.1mA 39h
1 16.1mW 5.2mA 107h
0.1 13.3mW 4.3mA 129h
0 13.0mW 4.2mA 132h
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
  • Nodes do not have a global ID such as an IP
  • The security, both physical and at the
    communication level, is more limited than
    conventional wireless networks

Design Considerations
  • Fault tolerance The failure of nodes should not
    severely degrade the overall performance of the
  • 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.

Sensor Network Protocol Stack
Power Management How the sensor uses its power,
e.g. turns off its circuitry after receiving a
Mobility Management Detects and registers the
movements of the sensor nodes
Task Management
Mobility Management
Power Management
Task Management Balances and schedules the
sensing tasks given to a specific region
Data Link
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
  • Baseband transmission, i.e. no intermediate or
    carrier frequencies
  • Generally uses pulse position modulation
  • Resilient to multipath
  • Low transmission power and simple transceiver

Data Link
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
Physical Layer
Assuming a linear relationship for the energy
spent per bit by the transmitter and receiver
eTC, eTA, and eRC are hardware dependent
An explicit expression for eTA can be derived
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
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
Data Link
  • Medium Access Control (MAC)
  • Let multiple radios share the same communication
  • 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
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
Wireless MAC protocols
DistributedMAC protocols
CentralizedMAC protocols
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
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

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.
Network Layer
Basic issues to take into account when designing
the network layer for WSNs are
  • 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
Phenomenonbeing sensed
Data aggregation takes place here
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
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
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
Flow of the request
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
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.
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.
  • SPIN messages
  • ADV- advertise data
  • REQ- request specific data
  • DATA- requested data
  • Resource management
  • Nodes decide their capability of participation in
    data transmissions

() 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.
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
  • 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.
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
  • The border node collects all packets and then
    sends one packet with all the data back to the

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

  • 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
  • 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

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
  • 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.
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
  • 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.
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
Data Link
  • Sensor Management Protocol (SMP) Carries out
    tasks such as
  • Turning sensors on and off
  • Exchanging data related to the location finding
  • Authentication, key distribution, and other
    security tasks
  • Sensor movement management

  • 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

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
Distributed Source Coding (DSC)
Encoder 1
Joint Decoder
Encoder 2
The encoders collaborate and a rate of H(X,Y) is
Encoder 1
Joint Decoder
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
Some Words About Cross-Layer Design
  • 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

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

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

  • 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

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.
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

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
  • 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
  • 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
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

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

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)

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
  • 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
  • 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

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

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.
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

Sensor-MAC (S-MAC)
Sensor-MAC (S-MAC)
Sensor-MAC (S-MAC)
Sensor-MAC (S-MAC)
  • Conclusion
  • The S-MAC protocol has good energy conserving
    properties when compared with the IEEE 802.11
  • 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

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

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.
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
  • 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

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
  • 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.
Directed Diffusion
Gradient represents both direction towards data
matching and status of demand with desired update
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
Directed Diffusion
Reinforcement and negative reinforcement used to
converge to efficient distribution
Has built in tolerance to nodes moving out of
range or dying
Directed Diffusion
Sensor Protocol for Information via Negotiation
A mechanism developed for the case where the
number of queries is higher than the number of
  • 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
  • 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.
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)
The process repeats itself across the network
Advertise meta-data
Send data
Send data
Advertise meta-data
I am tired I need to sleep
Send data
Send data
Request data
Nodes do need not to participate in the process
Request data
Request data
  • 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

  • In recent years a very large number of routing
    algorithm for WSNs have been proposed and
  • For most of the proposed techniques the analysis
    has been mainly carried out using simulation
  • 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
  • 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.
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
Spatiotemporal MAC
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
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
  • 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

  • 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
  • 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

  • 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
  • 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

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

  • 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
  • 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
  • The ESRT protocol aims to dynamically adjust the
    reporting rate to achieve the required detection
    reliability R at the sink

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
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
  • When a routing buffer overflows the node informs
    the sink by setting the congestion notification
    bit in the header packets traveling downstream

ESRT Network States
Optimal Operating Region
(Congestion, High reliability)
(No congestion, High reliability)
(Congestion, Low reliability)
(No congestion, Low reliability)
ESRT Frequency Update
State f update Action
(NC, LR) Multiplicative increase f to achieve required reliability as soon as possible
(NC, HR) Decrease f conservatively, reduce energy consumption and not lose reliability
(C, HR) Aggressively decrease f to relieve congestion as soon as possible
(C, LR) Exponential decrease. k is the number of successive decision intervals spent in state (C, LR)
OOR Unchanged
ESRT Summary and Conclusions
  • Uses a new paradigm for transport layer
  • Sensor networks are more interested in event to
    sink reliability than on individual end-to-end
  • 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
  • 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

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
() 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
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
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.
Energy Model
An explicit expression for eTA can be derived
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
() 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.
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.,
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
Modulation Method Typical Bandwidth(Null-To-Null)
QPSK, DQPSK 1.0 x Bit Rate
MSK 1.5 x Bit Rate
BPSK, DBPSK, OFSK 2.0 x Bit Rate
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.
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.
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.
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.
Energy Consumption - Multihop Networks
It can also be shown that the optimal number of
hops is,
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
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
()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,
Energy Consumption - Multihop Networks
where ? is a LaGranges multiplier. Taking the
partial derivatives of L with respect to di and
equating to 0 gives,
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
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,
About PowerShow.com