Seminar Report On Mobile Networking For Smart Dust
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14-06-2009, 01:57 AM

Seminar Report
Mobile Networking For Smart Dust
Submitted by
Jeena Kleenankandy
In the partial fulfillment of requirements in degree of
Master of Technology (M-Tech)
2005Page 2

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
Smart dust devices are tiny wireless sensors that can detect light and vibrations in
its environment. These motes could eventually be the size of a grain of sand, though each
would contain sensors, Motes can communicate with each other either via radio frequency
or via optical communication.
The operating system known as TinyOS was originally designed specifically for
smart dust. The TinyOS or Tiny Microthreading Operating System is similar to Windows
in that it is run by each and every mote and only requires 8 kilobytes of memory to run.
TinyOS manages the sensors, power, and communication with other motes. To save power,
the software is designed to allow the motes to sleep for over 98 percent of the time. They
wake up once a second, collect data for 50 microseconds and transmit for another 1000
microseconds, and then they return to sleep mode for the next 998,950 microseconds..
Development of mobile networking protocols for Smart Dust represents a
significant challenge. Some critical limitations are: (i) the free-space optical links requires
uninterrupted line-of-sight paths, (ii) the passive and active dust mote transmitters have
directional characteristics that must be considered in system design, and (iii) there are
severe trade-offs between bit rate, energy per bit, distance and directionality in these
energy-limited free-space optical links
We use Smart Dust to pursue project and implimentations such as
¢ deploying defense networks rapidly by unmanned aerial vehicles or artillery;
¢ monitoring rotating-compression-blade high cycle fatigue;
¢ tracking the movements of birds, small animals, and insects;
¢ monitoring environmental conditions crops and livestock;
¢ building virtual keyboards;Page 3

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
1. Introduction
2. Smart Dust Technology
3. Communication among Motes
3.1. Optical Communication
3.1.1. Passive Reflective System
3.1.2. Active Steered Laser System
4. Tiny Active Messages
4.1. Implementation of Smart Tiny Active Messages
4.1.1. Components
4.1.2. Packet Format
4.1.3. Multi-hop Packet Format
4.1.4. Special Addresses
5. Mobile Networking Challenges
5.1. Overview
5.1.1. Line-of-Sight Requirement
5.1.2. Link directionality
5.1.3. Trade-offs Between Bit rate, Distance ,Energy/bit
6. Mobile Networking Opportunities
6.1. Overview
6.1.1. Parallel Read-out
6.1.2. Demand Access
6.1.3. Probe Revisit Rates
7. Applications
8. Conclusion
9. References
32 Page 4

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
As the research community searches for the processing platform beyond the
personal computer, networks of wireless sensors have become quite interesting as a new
environment in which to seek research challenges. These have been enabled by the rapid
convergence of three key technologies: digital circuitry, wireless communications, and
MicroElectroMechanicalSystems (MEMS). In each area, advances in hardware technology
and engineering design have led to reductions in size, power consumption, and cost. This
has enabled remarkably compact, autonomous nodes, each containing one or more sensors,
computation and communication capabilities, and a power supply.
Berkeleyâ„¢s Smart Dust project and implimentation, led by Professors Pister and Kahn, explores the
limits on size and power consumption in autonomous sensor nodes. Size reduction is
paramount, to make the nodes as inexpensive and easy-to deploy as possible. These
millimeter-scale nodes are called Smart Dust. Smart dust devices are tiny wireless
sensors that can detect light and vibrations in its environment. They also go by the name of
.1 P
2001Page 5

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
These motes could eventually be the size of a grain of sand, though each would
contain sensors, computing circuits, bi-directional communication technology and a power
supply as well. Many prototypes that have been developed in the past were about the size
of a small matchbook and it was in 2001 that Kris Pister was able to harness the latest
technology to develop a prototype smaller than the nib of a ballpoint pen (fig.1). Even
though this would seem very small to the human eye, the ideal size would be at least a 100
times smaller than this. It is certainly within the realm of possibility that future prototypes
of Smart Dust could be small enough to remain suspended in air, buoyed by air currents,
sensing and communicating for hours or days on end.
These kinds of networking nodes must consume extremely low power,
communicate at bit rates measured kilobits per second, and potentially need to operate in
high volumetric densities. These requirements dictate the need for novel ad hoc routing and
media access solutions. Smart dust will enable an unusual range of applications, from
sensor- rich smart spaces to self-identification and history racking for virtually any kind
of physical object. Page 6

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
A Smart Dust mote is illustrated in Figure 2. Integrated into a single package are
MEMS sensors, a semiconductor laser diode and MEMS beam-steering mirror for active
optical transmission, a MEMS corner-cube retroreflector for passive optical transmission,
an optical receiver, signal-processing and control circuitry, and a power source based on
thick-film batteries and solar cells. This remarkable package has the ability to sense and
communicate, and is self-powered. A major challenge is to incorporate all these functions
while maintaining very low power consumption, thereby maximizing operating life given
the limited volume available for energy storage. Within the design goal of a cubic
millimeter volume, using the best available battery technology, the total stored energy is on
the order of 1 Joule. If this energy is consumed continuously over a day, the dust mote
power consumption cannot exceed roughly 10 microwatts. The functionality envisioned for
Smart Dust can be achieved only if the total power consumption of a dust mote is limited o
microwatts levels, and if careful power management strategies re utilized (i.e., the various
parts of the dust mote are powered on only when necessary). To enable dust motes to
function over the span of days, solar cells could be employed to scavenge as much energy
as possible when the sun shines (roughly 1 Joule per day) or when room lights are turned
on (about 1 millijoule per day).
Techniques for performing sensing and processing at low power are reasonably well
understood. Developing communication architecture for ultra-low-power represents a more
critical challenge. The primary candidate communication technologies are based on radio
frequency (RF) or optical transmission techniques. Each technique has its advantages and
disadvantages. RF presents a problem because dust motes offer very limited space for
antennas, thereby demanding extremely short-wavelength (i.e., high frequency)
transmission. Communication in this regime is not currently compatible with low power
operation. Furthermore, radio transceivers are relatively complex circuits, making it
difficult to reduce their power consumption to the required microwatt levels. They require
modulation, band pass filtering and demodulation circuitry, and additional circuitry isPage 7

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
required if the transmissions of a large number of dust motes are to be multiplexed using
time-, frequency- or code-division multiple access.
. 2 C
An attractive alternative is to employ free-space optical transmission. Kahn and Pisterâ„¢s
studies have shown that when a line-of-sight path is available, well-designed freespace
optical links require significantly lower energy per bit than their RF counterparts. There are
several reasons for the power advantage of optical links. Optical transceivers require only
simple baseband analog and digital circuitry; no modulators, active bandpass filters or
demodulators are needed. The short wavelength of visible or near-infrared light (of the
order of 1 micron) makes it possible for a millimeter- scale device to emit a narrow beam
(i.e., high antenna gain can be achieved). As another consequence of this short wavelength,
a base-station transceiver (BTS) equipped with a compact imaging receiver can decode thePage 8

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
simultaneous transmissions from a large number of dust motes at different locations within
the receiver field of view, which is a form of space-division multiplexing. Successful
decoding of these simultaneous transmissions requires that dust motes not block one
anotherâ„¢s line of sight to the BTS. Such blockage is unlikely, in view of the dust motesâ„¢
small size. A second requirement for decoding of simultaneous transmission is that the
images of different dust motes be formed on different pixels in the BTS imaging receiver.
To get a feeling for the required receiver resolution, consider the following example.
Suppose that the BTS views a 17 meter by 17 meter area containing Smart Dust, and that it
uses a high-speed video camera with a very modest 256 by 256 pixel imaging array. Each
pixel views an area about 6.6 centimeters square. Hence, simultaneous transmissions can be
decoded as long as the dust motes are separated by a distance roughly the size of a pack of
cigarettes. Page 9

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
Smart Dustâ„¢s full potential can only be attained when the sensor nodes
communicate with one another or with a central base station. Wireless communication
facilitates simultaneous data collection from thousands of sensors. There are several
options for communicating to and from a cubic-millimeter computer. Radio frequency and
optical communications each have their strengths and weaknesses.
Radio-frequency communication is well understood, but currently requires
minimum power levels in the multiple milliwatt range due to analog mixers, filters, and
oscillators. If whisker-thin antennas of centimeter length can be accepted as a part of a dust
mote, then reasonably efficient antennas can be made for radio-frequency communication.
While the smallest complete radios are still on the order of a few hundred cubic
millimeters, there is active work in academia and industry to produce cubic-millimeter
Semiconductor lasers and diode receivers are intrinsically small, and the
corresponding transmission and detection circuitry for on/off keyed optical communication
is more amenable to low-power operation than most radio schema. Perhaps most important,
optical power can be collimated in tight beams even from small apertures. Diffraction
enforces a fundamental limit on the divergence of a beam, whether it comes from an
antenna or a lens. Laser pointers are cheap examples of milliradian collimation from a
millimeter aperture. To get similar collimation for a 1-GHz radio frequency signal would
require an antenna 100 meters across, due to the difference in wavelength of the two
transmissions. As a result, optical transmitters of millimeter size can get antenna gains of
one million or more, while similarly sized radio frequency antennas are doomed by physics
to be mostly isotropic.
Collimated optical communication has two major drawbacks. Line of sight is
required for all but the shortest distances, and narrow beams imply the need for accuratePage 10

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
pointing. Of these, the pointing accuracy can be solved by MEMS technology and clever
algorithms, but an optical transmitter under a leaf or in a shirt pocket is of little use to
anyone. Presently optical communication is the more opted form of communication in
some depth due to the potential for extreme low-power communication. We discuss it in
detail here.
Two approaches to optical communications have been explored to date: passive
reflective systems and active steered laser systems. In a passive communication system, the
dust mote does not require an onboard light source. Instead, a special configuration of
mirrors can either reflect or not reflect light to a remote source.
In its simplest passive configuration, the passive reflective device consists of three
mutually orthogonal mirrors. Light enters the CCR, bounces off each of the three mirrors,
and is reflected back parallel to the direction it entered. In the MEMS version, the device
has one mirror mounted on a spring at an angle slightly askew from perpendicularity to the
other mirrors. In this position, because the light entering the CCR does not return along the
same entry path, little light returns to the source”a digital 0. Applying voltage between
this mirror and an electrode beneath it causes the mirror to shift to a position perpendicular
to other mirrors, thus causing the light entering the CCR to return to its source”a digital 1.
The mirrorâ„¢s low mass allows the CCR to switch between these two states up to a thousand
times per second, using less than a nanojoule per 0?1 transition. A 1?0 transition, on the
other hand, is practically free because dumping the charge stored on the electrode to the
ground requires almost no energy.
Figure 3 illustrates a free-space optical network utilizing the CCR based passive
uplink. The BTS contains a laser whose beam illuminates an area containing dust motes. Page 11

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
This beam can be modulated with downlink data, including commands to wake up and
query the dust motes. When the illuminating beam is not modulated, the dust motes can use
their CCRs to transmit uplink data back to the base station. A highframe- rate CCD video
camera at the BTS sees these CCR signals as lights blinking on and off. It decodes these
blinking images to yield the uplink data. Kahn and Pisterâ„¢s analysis show that this uplink
scheme achieves several kilobits per second over hundreds of meters in full sunlight, at
night, in clear, still air, the range should extend to several kilometers. Because the camera
uses an imaging process separate the simultaneous transmissions from dust motes different
locations, we say that it uses space-division multiplexing
The ability for a video camera to resolve these transmissions is a consequence of
the short wavelength visible or near infrared light. This does not require any coordination
among the dust motes, and thus, it does not complicate their design.
The latest Smart Dust device is a 63-mm³ autonomous bi-directional
communication mote that receives an optical signal, generates a pseudorandom sequence
based on this signal to emulate sensor data, and then optically transmits the result. ThePage 12

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
system contains a micromachined corner-cube reflector, a 0.078-mm3 CMOS chip that
draws 17 microwatts, and a hearing aid battery. In addition to a battery-based operation, we
have also powered the device using a 2-mm² solar cell. This mote demonstrates Smart
Dustâ„¢s essential concepts, such as optical data transmission, data processing, energy
management, miniaturization, and system integration. A passive communication system
suffers several limitations. Unable to communicate with each other, motes rely on a central
station equipped with a light source to send and receive data from other motes. If a given
mote does have a clear line of sight to the central station, that mote will be isolated from
the network. Also, because the CCR reflects only a small fraction of the light emitted from
the base station, this systemâ„¢s range cannot easily extend beyond one kilometer. To
circumvent these limitations, dust motes must be active and have their own onboard light

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
For mote-to-mote communication, an active-steered laser communication system
uses an onboard light source to send a tightly collimated light beam toward an intended
receiver. Steered laser communication has the advantage of high power density; for
example, a 1-milliwatt laser radiating into 1 milliradian (3.4 arc seconds) has a density of
approximately 318 kilowatts per steradian (there are 4 p steradians in a sphere), as opposed
to a 100-watt light bulb that radiates 8 watts per steradian isotropic ally. A Smart Dust
moteâ„¢s emitted beam would have a divergence of approximately 1 milliradian, permitting
communication over enormous distances using milliwatts of power.
Forming ad hoc multihop networks is the most exciting application of mote-to-mote
communication. Multihop networks present significant challenges to current network
algorithms”routing software must not only optimize each packet™s latency but also
consider both the transmitterâ„¢s and receiverâ„¢s energy reserves. Each mote must carefully
weigh the needs to sense, compute, communicate, and evaluate its energy reserve status
before allocating precious nanojoules of energy to turn on its transmitter or receiver.
Because these motes spend most of their time sleeping, with their receivers turned off,
scheduling a common awake time across the network is difficult. If motes donâ„¢t wake up in
a synchronized manner, a highly dynamic network topology and large packet latency result.
Using burst mode communication, in which the laser operates at up to several tens of
megabits per second for a few milliseconds, provides the most energy-efficient way to
schedule this network. This procedure minimizes the moteâ„¢s duty cycle and better utilizes
its energy reserves. The steered agile laser transmitter consists of a semiconductor diode
laser coupled with a collimating lens and MEMS beam-steering optics based on a two
degree-of-freedom silicon micromirror. This system integrates all optical components into
an active 8-mm³ volume.
Many Smart Dust applications rely on direct optical communication from an entire
field of dust motes to one or more base stations. These base stations must therefore be able
to receive a volume of simultaneous optical transmissions. Further, communication must be
possible outdoors in bright sunlight which has an intensity of approximately 1 kilowatt perPage 14

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
square meter, although the dust motes each transmit information with a few milliwatts of
power. Using a narrow-band optical filter to eliminate all sunlight except the portion near
the light frequency used for communication can partially solve this second problem, but the
ambient optical power often remains much stronger than the received signal power.
As with the transmitter, the short wavelength of optical transmissions compared
with radio frequency overcomes both challenges. Light from a large field of view field can
be focused into an image, as in our eyes or in a camera. Imaging receivers utilize this to
analyze different portions of the image separately to process simultaneous transmissions
from different angles. This method of distinguishing transmissions based on their
originating location is referred to as space division multiple access.
Imaging receivers also offer the advantage of dramatically decreasing the ratio of
ambient optical power to received signal power. Ideally, the imaging receiver will focus all
of the received power from a single transmission onto a single photodetector. If the receiver
has an n* n array of pixels, then the ambient light that each pixel receives is reduced by a
factor n
compared with a non-imaging receiver. Typically, using a value for n between 8
and 32 makes the ambient light power negligible compared with the electronic noise in the
analog electronics.
Active Messages is centered on the concept of integrating communication and
computation, as well as matching communication primitives to hardware capabilities. Tiny-
networked devices must take advantage of the efficiencies that can be achieved by this
matching. Furthermore, the inability to support a large number of simultaneous execution
contexts requires that computation and communication be overlapped so that valuable
computational resources
are not wasted. Page 15

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
Active Messages (AM) is a simple, extensible paradigm for message-based
communication widely used in large parallel and distributed computing systems. At its
core is the concept of overlapping communication and computation through lightweight
remote procedure calls. Each message contains the name of a handler to be invoked on a
target node upon arrival and a data payload to pass in as arguments. The handler function
serves the dual purpose of extracting the message from the network and either integrating
the data into the computation or sending a response. The AM communication model is
especially well suited to the execution framework of TinyOS, as it is event-driven and
specifically designed to allow a very lean communication stack to process packets directly
over the network, while supporting a wide range of applications. Initiating an Active
Message involves four components, specifying the data arguments, naming the handler,
requesting the transmission, and detecting transmission completion. Receiving involves
invoking the specified handler on a copy of the transmitted data
The SEND MSG command identifies intended recipients (here using the broadcast
address for the local cell of nodes that pick up the radio transmission), the handler that will
process the message on arrival, (here CHIRP MSG), and the source output message buffer
in the local frame. A handler registry is maintained, and TOS MSG extracts the identifier
for the named handler. The status handshake for this command illustrates the general
notion of components managing their bounded resources. The messaging component may
refuse the send request, for example, if it is busy transmitting or receiving a message and
does not have resources with which to queue the request.
The message arrival event is similar to other events. One key difference is that the
Active Message component dispatches the event to the component with the associated
message handler. Many components may register one or more message handlers.
Additionally, the input to the handler is a reference to a message buffer provided by the
Active Message component. The event based handler invocation model allows application
developers to avoid busy-waiting for data to arrive and allows the system to overlap Page 16

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
communication with other activities such as interacting with sensors or executing other
applications. It is this event centric nature of Active Messages which makes it a natural fit
for these devices.
The basic paradigm of typed messages causing handlers to be invoked upon arrival
matches up well with the event based programming model supported by TinyOS and
demanded by the underlying sensor hardware. The low overhead associated with event-
based notification is complementary to the limited resources of networked sensors.
Applications do not need to waste resources while waiting for messages to arrive.
Additionally, the overlap of computational work with application level communication is
essential. Execution contexts and stack space must never be wasted because applications
are blocked, waiting for communication. Essentially, the active messages communication
model can be viewed as a distributed eventing model where networked nodes send each
other events.
In order to make the active messages communication model a reality, certain
primitives must be provided by the system. We believe that the three basic primitives are:
best effort message transmission, addressing, and dispatch. More demanding applications
may need to build more functionality on top of these primitives, but that is left for the
applications developer to decide. By creating the minimal kernel of a communication
system, all applications will be able to build on top of it.
Additionally, it is likely that there will be a large variety of devices with different
physical communication capabilities and needs. By building the communication kernel as
three separate components using the TinyOS component model, developers can pick and
choose which implementations of the basic components they need. This can take the form
of selecting from a collection of delivery components that perform different levels of error
correction and detection. However, by providing a consistent interface to communication
primitives, application developers can easily transfer their applications to different
hardware platforms. Page 17

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
Finally, the selection of an event based communication mechanism does not
preclude the use of a threaded, blocking, and execution model. An event-based model can
easily be transformed into a threaded model through the use of a queue, where an event
simply places the data into a queue structure that can be accessed by the thread. When the
queue is empty, the thread can block until data arrives. On the contrary, it is difficult to
switch from a threaded implementation to an event-based model. Similarly, the immediate
propagation of messages to the application layer does not prevent the use of buffers to
temporarily hold messages until the application is ready to deal with them. An application
level buffer component could be used to accomplish this. However, including extra buffers
inside the communication primitives precludes the application from eliminating them.
The interface to the messaging component is quite simple. It accepts TinyOS commands
from the applications to initiate message transfers and fires off events to message handlers
based on the type of messages that have been received. There is an additional event that
signals the completion of a transmission. Send commands include the destination address,
handler ID, and message body. Internally, the Active Messages component performs
address checking and dispatch and relies on sub components for basic packet transmission.
The underlying packet level processing components simply perform the function of
transmitting the block of bytes out over the radio. It is assumed that this is a best effort
transmission mechanism. While a reliable, error free delivery is not expected; it is assumed
that there will be some basic logic that attempts to avoid transmission collisions. The
interface to the packet level component provides a mechanism to initiate the transmission
of a fixed size, 30 byte packet, as well as two events that are fired when a transmission or aPage 18

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
reception are complete. We have multiple implementations of packet level components
each providing different levels of error correction or detection. They include, basic
transmission without any error detection or correction, CRC checked packets that have
error detection, and forward error corrected packets that provide basic error correction as
well as error detection.
The first two bytes of a received packet are used to identify the destination of the packet
(R0) and the ID of the message handler that is to be invoked on the packet (H0). The AM
component first checks that the address matches the local address and then it invokes the
listed handler, passing on the remaining 28 bytes of the packet. In the event that the
message is bound for a handler that is not present on the receiving device, the packet is
ignored. The dispatch routine that is used by the message handler is automatically
generated at compile time based on the message handlers that are present. This is done to
eliminate the need for expensive handler registration mechanisms.
In order to demonstrate how application specific needs could be met by building on top of
the basic Active Messages primitives, we have a component that supports source based
multi-hop routing. The format, seen in figure.7 dedicates seven additional bytes to allow a
maximum of 4-hop communication. Four of these bytes are used to hold the intermediate
hops of the route (R
, R2, R
, R4), one is used for the number of hops left (N), one is used
to store the source of the packet (S), and one is used for the handler ID that is to be invoked
once the message arrives at its destination (Hf ). Page 19

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
In developing sample applications to test the usability of messaging layer, two
special addresses were defined. The first special address that was needed was the broadcast
address. The concept of a one-to-all broadcast greatly simplifies the route discovery and
exploration algorithms. Combining this with routing handlers designed to record the path
that a packet has taken yields a trivial implementation of a route discovery application. In
its simplest form, an application can send a two-hop packet to the broadcast address
followed by its own address. This will cause any device that is in range to respond with its
own address recorded in the packet that the original device receives.
Secondly, a special address was chosen for the Host PC in the device virtual
network. Arbitrarily chosen to be 0x7e, a device receiving a packet for this destination
forwards the packet to the local data UART instead of the radio. This exposes the basic
need to have the notion of gateway addresses that get treated specially. Page 20

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
Development of mobile networking protocols for Smart Dust represents a significant
challenge. Some critical limitations are: (i) the free-space optical links requires
uninterrupted line-of-sight paths, (ii) the passive and active dust mote transmitters have
directional characteristics that must be considered in system design, and (iii) there are
severe trade-offs between bit rate, energy per bit, distance and directionality in these
energy-limited free-space optical links. These limitations are described in more detail in the
following subsections.
5.1.1 Line-of-Sight Requirement
An unbroken line-of-sight path is normally required for operation of free space optical links
for Smart Dust. These links cannot operate reliably using non-line-of-sight propagation,
which would rely on reflections from one or more objects between the transmitter and
receiver. As shown in Section 3.1.3, the transmitted beam should have a small angular
spread in order to achieve a high signal-to-noise ratio with acceptably small transmitter
power. Specular reflection may not significantly increase a beamâ„¢s angular spread, but the
existence of a properly aligned specular reflector would be a rare event. Diffuse reflection
scatters a beamâ„¢s energy over a wide range of angles, making alignment less critical, but
usually scatters insufficient energy toward the receiver. Hence, diffuse, non-line-of-sight
transmission is likely to be feasible only when active transmitters are used over very short
distances (probably under 1 meter). It is probably impossible to use diffuse, non-line-of
sight transmission with passive transmitters (based on CCRs), because both the
interrogating beam and the reflected beam would be subject to scattering over a wide range
of angles.
A fixed dust mote without a line-of-sight path to the BTS can communicate with the
BTS via multihop routing, provided that a suitable multihop path exists. The existence of
such a path is more likely when the dust mote density is higher. Multihop routing increases
latency, and requires dust motes to be equipped with active optical transmitters. ConstraintsPage 21

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
on size and power consumption of the dust mote digital circuitry dictate the need for low-
complexity ad hoc multihop routing algorithms. When dust motes are floating in the air or
otherwise not fixed, a line-of-sight path to the BTS may become intermittently available. In
such cases, the BTS can continuously interrogate the dust motes. When a line-of-sight path
to a mote becomes available, the mote can transmit a packet to the BTS. When the average
time between occurrence of viable line-of-sight paths is much longer than the packet
duration, latency will probably be minimized by using multihop
routing instead.
5.1.2 Link Directionality
In most Smart Dust systems, the BTS interrogating beam angular spread should be
matched to the field of view of the BTS imaging receiver. These two should be matched in
all systems using passive dust mote transmitters, and in systems using active dust mote
transmitters when the application involves frequent bi-directional transmission between the
BTS and dust motes. Intuitively, it makes little sense for the BTS to interrogate dust motes
from which it cannot receive, and vice versa. In these systems, the interrogating beam and
imaging receiver will be mounted rigidly together in the BTS, and will be aimed together
as a unit. For example, the BTS may reside in a hand-held unit resembling pair of
binoculars, which is aimed by a human operator.
In certain applications using active dust mote transmitters, may be desirable to use a
BTS transmitter beam whose angular spread is smaller than the BTS receiver field of view.
In these applications, the interrogating beam will be aimed at various locations within the
receiver field of view. Because of limited available space, the dust moteâ„¢s optical receiver
probably cannot employ an imaging or non-imaging optical concentrator in front of the
photodetector. As result, the dust mote receiver will be fairly omnidirectional, i.e., it will be
able to receive from most of the hemisphere located in front of the dust mote. In most
applications, should not be necessary to aim the dust mote receiver.
The dust moteâ„¢s transmitter will exhibit markedly different directional
characteristics than its receiver. A passive dust mote transmitter is based on the CCR. ThisPage 22

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
device reflects light directly back to the source within a narrow beam1, provided that it is
illuminated from a direction that lies within few tens of degrees of the cube body diagonal.
If dust motes use only one CCR each, then any given dust mote, if fixed in a random,
upright orientation, has only about a 10% probability of being able to transmit to the BTS.
This probability can be increased significantly by equipping each dust mote with several
CCRs, each oriented along a different direction. As an alternative, a single CCR may be
mounted on MEMS aiming mechanism. This mechanism need only aim the CCR with an
accuracy of the order of 10 or 20 degrees. Still other solutions exist for coping with the
CCRâ„¢s directionality. It may be possible to distribute randomly an excess number of dust
motes, with the goal of communicating only with those whose CCRs happen to point
toward the BTS. If the dust motes are not fixed, it may be best for dust mote to simply
delay transmitting until it moves into an orientation that enables transmission to the BTS.
An active dust mote transmitter is based on a laser diode. should employ a narrow beam
width, typically of the order of a few degrees or less (see Section 3.1.3). This necessitates
equipping the dust mote with an active beam-steering mechanism. Pister and his students
are working on MEMS-based mechanism capable of steering a beam to any position within
a hemisphere. Beam-steering algorithms for systems with active dust mote transmitters
represent a current research challenge. It would be desirable for each dust mote to
autonomously steer its beam toward the desired direction. One approach would be to make
the dust mote receiver directional, and to mount the receiver and transmitter on the same
aiming mechanism. Accordingly, by aiming its receiver so as to maximize the signal
received from the BTS or another mote, the dust mote would be aiming its transmitter at
that node. The need for active dust mote transmitters to determine the direction to other
nodes slows down connection set up, but if nodes remain fixed then the directions of
various nodes, once determined, can be stored in the dust mote for future use. Under most
of the scenarios discussed above, the dust moteâ„¢s transmitter and receiver have different
angular spreads. This leads to non-reciprocal link characteristics, wherein a dust mote may
receive from another node, but be unable to transmit to it, or vice versa. As a consequence,
dust mote may receive queries from other nodes, and may attempt to answer them, unaware
that its transmissions are in vain. When dust motes are fixed, in order to conserve dust motePage 23

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
power, the other nodes should acknowledge this dust moteâ„¢s transmissions, and this dust
mote should not answer further queries from nodes that do not acknowledge its
transmissions. It is known that in free-space optical networks, non-reciprocity can lead to
hidden nodes, which can cause collisions during medium access. For example, this effect
is observed in networks having a shared-bus physical topology, and using MAC protocols
based on random time-division multiplexing, such as CSMA-CA with RTS/CTS . In Smart
Dust networks, the uplink (dust mote to BTS) uses space-division multiplexing. Uplink
collisions will not occur as long as the dust motes are sufficiently separated that their
transmissions are detected by different pixels in the BTS imaging receiver. Collisions
during active peer-to-peer communications are a potential problem in Smart Dust networks.
A peer-to-peer collision avoidance scheme must cope with a dynamic network
configuration, while not introducing excessive complexity or latency.
3.1.3 Trade-Offs Between Bit Rate, Distance and Energy per Bit
Free-space optical links are subject to trade-offs between several design parameters.
For simplicity, we consider the case of links employing active laser transmitters. The
receiver signal-to-noise ratio (SNR) is given by .
.SNR = C. E
¦¦¦¦¦¦¦¦¦.. (1)
Here, C is a constant, is the average transmitted energy per bit, is the bit rate, A is
the receiver light collection area
, N
is the receiver noise power spectral density, d is the
link transmission distance, and F is the transmitter beam angular spread. This expression
assumes that F is small, and that the transmitter beam is well-aimed at the receiver. The
SNR governs the probability of bit error, and must be maintained at a suitably high value to
insure reliable link operation. From (1), we see that in order to achieve a given SNR with
all other parameters fixed, the required value of E
is proportional to R
, i.e., the energy
per bit is minimized if packets are transmitted in short bursts at a high bit rate. Hence,
transmission at a high bit rate requires a high-power transmitter. In practice, P
should bePage 24

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
chosen to be as high as possible, within constraints posed by eye safety and by dust mote
current-drive limitations.
Given a limit on P
, to maximize the bit rate R
and the distance d, we should
maximize the receiver area A and minimize F, i.e., use a highly directional transmitter.
Once all other parameters have been fixed, to maintain a required SNR, the permissible bit
rate and distance are related by R
? d
. Hence, it is possible to extend the link distance
by drastically lowering the bit rate. If a multihop route is available, overall latency may be
minimized by transmitting at a higher bit rate over several hops. Page 25

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
The optical free-space communication method presents many opportunities beyond low-
power, passive communications. Since the application of interest in sensor networks is
primarily sensor read-out, the key protocol issues are to perform read-out from a large
volume of sensors co-located within a potentially small area. Random access to the
medium is both energy consuming and bandwidth inefficient. So it is extremely useful to
exploit passive and broadcast- oriented techniques when possible. Fortunately the free-
space approach supports multiple simultaneous readout of sensors, mixes active and
passive approaches using demand access techniques, and provides efficient and low latency
response to areas of a sensor network that are undergoing frequent changes. These are
described in more detail in the following subsections, with emphasis on passive dust mote
6.1.1 Parallel Read-Out
A single wide beam from the BTS can simultaneously probe many dust motes. The
imaging receiver at the BTS receives multiple reflected beams from the motes, as long as
they are sufficiently separated in space to be resolved by the receiverâ„¢s pixel array. The
probe beam sweeps the three dimensional space covered by the base station on a regular
basis, most likely determined by the nature of the application and its need for moment-by
moment sensor readings.
6.1.2 Demand Access
To save transmit power, if the mote must use active communications, then it is best
to use the active transmitter in a high-bit-rate, short-burst mode. Familiar demand access
methods can be used to combine the low latency advantages of active communications with Page 26

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
the low-power advantages of the passive approach. When the mote needs to transmit
information, it actively transmits a short duration burst signal to the BTS. The BTS,
detecting this signal, then probes in the general geographical area from which the burst was
detected. Assuming that the passive transmitter (i.e., CCR) is properly oriented toward the
BTS, the mote can respond by modulating the reflected probe beam with the data it needs
to transmit. Logically, the communications structure described above has much in common
with familiar cellular and satellite networks. The paging channel is acquired using
contention access techniques. The BTS grants a channel to the node requesting attention. In
a cellular network, this is accomplished by assigning a frequency, time slot, and/or code to
the node. In the scheme described for dust motes, the channel is granted by the incident
probe beam. Note that there are as many channels (paging or data) as there are resolvable
pixels at the BTS. The BTS has no way to distinguish between simultaneously
communicating dust motes if they fall within the same pixel in the imaging array. One
possible way to deal with this is to introduce time slotted techniques not unlike that found
in time division multiple access (TDMA) communications systems. A wide aperture beam
from the BTS could be modulated in such a fashion as to offer a common time base by
which to synchronize the motes. The BTS can then signal an individual mote the particular
time slot it has assigned to it for communication. The mote must await its time slot to
communicate, whether it uses an active or a passive transmitter.
6.1.3 Probe Revisit Rates
Probe beam revisit rates could be determined in an application- specific manner. It
is a well-known observation from statistical data management that areas where changes are
happening most rapidly should be revisited most frequently. If sensor readings are not
changing much, then occasional samples are sufficient to obtain statistically significant
results. So it is better to spend probe dwell time on those sensors that are experiencing the
most rapid reading changes, and for which infrequent visit would lead to the greatest
divergence from the current sensor values. Page 27

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
The various applications that Smart Dust can be put are endless as can be seen from the
various scenarios listed below. Smart Dust can be implemented in practically any field
because of its ability to collect information
The Defense Advanced Research Projects Agency (DARPA) was among the
original patrons of the mote idea. One of the initial mote ideas implemented for DARPA
allows motes to sense battlefield conditions. For example, imagine that a commander wants
to be able to detect truck movement in a remote area. An airplane flies over the area and
scatters thousands of motes, each one equipped with a magnetometer, a vibration sensor
and a GPS reciever. The battery-operated motes are dropped at a density of one every 100
feet (30 meters) or so. Each mote wakes up, senses its position and then sends out a radio
signal to find its neighbors.
All of the motes in the area create a giant, amorphous network that can collect data.
Data funnels through the network and arrives at a collection node, which has a powerful
radio able to transmit a signal many miles. When an enemy truck drives through the area,
the motes that detect it transmit their location and their sensor readings. Neighboring motes
pick up the transmissions and forward them to their neighbors and so on, until the signals
arrive at the collection node and are transmitted to the commander. The commander can
now display the data on a screen and see, in real time, the path that the truck is following
through the field of motes. Then a remotely piloted vehicle can fly over the truck, make
sure it belongs to the enemy and drop a bomb to destroy it.
This might seem like a lot of trouble, but it is really more effective than the
solutions of the past. In the past, the tool a commander used to prevent truck or troop
movement through a remote area has been land mines. Soldiers would lace the area with
thousands of anti-truck or anti-personnel mines. Anyone moving through the area -- friend
or foe -- is blown up. Another problem, of course, is that long after the conflict is over the
mines are still active and deadly -- laying in wait to claim the limbs and even lives of anyPage 28

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
passerby. According to a UNICEF report, over the last 30 years, landmines have killed or
maimed more than 1 million people -- many of whom are children. With motes, what is left
behind after a war are tiny, completely harmless sensors. Since motes consume so little
power, the batteries would last a year or two. Then, the motes would simply go silent
presenting no physical threat to civilians nearby.
It is also possible to think of motes as lone sensors.
Motes can be embedded in bridges when the concrete is poured. The mote could
have a sensor on it that can detect the salt concentration within the concrete. Then
once a month a truck could be over the bridge that sends a powerful magnetic field
into the bridge. The magnetic field would allow the motes, which are buried within
the concrete of the bridge, to power on and transmit the salt concentration. Salt
(perhaps from deicing or ocean spray) weakens concrete and corrodes the steel
rebar that strengthens the concrete. Salt sensors would let bridge maintenance
personnel gauge how much damage salt is doing. Other possible sensors embedded
into the concrete of a bridge might detect vibration, stress, temperature swings,
cracking, etc., all of which would help maintenance personnel spot problems long
before they become critical.
Sensors can be built onto a mote that can monitor the condition of machinery --
temperature, number of revolutions, oil level, etc. and log it in the mote's memory.
Then, when a truck drives by, the mote could transmit all the logged data. This
would allow detailed maintenance records to be kept on machinery (for example, in
an oil field), without maintenance personnel having to go measure all of those
parameters themselves.
Mote could be attached to the water meters or power meters in a neighborhood. The
motes would log power and water consumption for a customer. When a truck drives
by, the motes get a signal from the truck and they send their data. This would allow
a person to read all the meters in a neighborhood very easily, simply by driving
down the street. Page 29

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
All of these ideas are good; some allow sensors to move into places where they have
not been before (such as embedded in concrete) and others reduce the time needed to read
sensors individually.
However, much of the greatest excitement about motes comes from the idea of
using large numbers of motes that communicate with each other and form ad hoc networks.
This concept of ad hoc networks -- formed by hundreds or thousands of motes that
communicate with each other and pass data along from one to another -- is extremely
powerful. Here are several examples of the concept at work:
Imagine a suburban neighborhood or an apartment complex with motes that monitor
the water and power meters (as described in the previous section). Since all of the
meters (and motes) in a typical neighborhood are within 100 feet (30 meters) of
each other, the attached motes could form an ad hoc network amongst themselves.
At one end of the neighborhood is a super-mote with a network connection or a
cell-phone link. In this imagined neighborhood, someone doesn't have to drive a
truck through the neighborhood each month to read the individual water or power
meters -- the motes pass the data along from one to another, and the super-mote
transmits it. Measurement can occur hourly or daily if desired.
A farmer, vineyard owner, or ecologist could equip motes with sensors that detect
temperature, humidity, etc., making each mote a mini weather station. Scattered
throughout a field, vineyard or forest, these motes would allow the tracking of
A building manager could attach motes to every electrical wire throughout an office
building. These motes would have induction sensors to detect power consumption
on that individual wire and let the building manager see power consumption down
to the individual outlet. If power consumption in the building seems high, the
building manager can track it to an individual tenant. Although this would be
possible to do with wires, with motes it would be far less expensive. Page 30

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
A biologist could equip an endangered animal with a collar containing a mote that
senses position, temperature, etc. As the animal moves around, the mote collects
and stores data from the sensors. In the animal's environment, the biologists could
place zones or strips with data collection motes. When the animal wanders into one
of these zones, the mote in the collar would dump its data to the ad hoc network in
the zone, which would then transmit it to the biologist.
Motes placed every 100 feet on a highway and equipped with sensors to detect
traffic flow could help police recognize where an accident has stopped traffic.
Because no wires are needed, the cost of installation would be relatively low.
The possibilities in implementing Smart Dust are endless. The following are some of
the ideas floating around that show a few of the ways that smart does can affect our lives in
the future:
¢ The monitoring of weather and seismology “ Better prediction of earthquakes and
¢ The monitoring of environments on Mars and other planets.
¢ Internal spacecraft monitoring “ this can be useful in preventing the shuttle from
crashing due to technical problems by finding them before they occur.
¢ Land to space communication networks “ faster communication from earth to space
with real time data.
¢ Chemical and biological sensors - could be used to monitor the purity of drinking or
sea water, to detect hazardous chemical or biological agents in the air or to locate
and destroy tumor cells in the body
¢ Defense related sensor networks “ this will be a great help for military action such
as surveillance.
¢ Weapons stockpile monitoring “ monitor weapons of mass destruction Page 31

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
¢ Inventory Control “ Know where your products are and what shape they're in any
time, anywhere. Sort of like FedEx tracking on steroids for all products in your
production stream from raw materials to delivered goods.
¢ Product quality monitoring “ smart dust can have many positive effects on quality
control: Temperature, humidity monitoring of meat, produce, dairy products, etc.
¢ Smart offices and smart homes “environmental conditions in the office or home are
tailored to the desires of every individual.
¢ Sports “ smart dust could bring a whole new aspect to sporting events. Sailboat
racers can monitor the changes in the wind and current to gain an advantage. Also,
think about the possibilities of putting motes on the balls during games to monitor
things such as ball spin and speed. Page 32

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
Smart Dust, is an integrated approach to networks of millimeter-scale
sensing/communicating nodes. Smart Dust can transmit passively using novel optical
reflector technology. This provides an inexpensive way to probe a sensor or acknowledge
that information was received. Active optical transmission is also possible, but consumes
more power. It will be used when passive techniques cannot be used, such as when the line
of-sight path between the dust mote and BTS is blocked.
Smart dust provides a very challenging platform in which to investigate applications
that can harness the emergent behavior of ensembles of simple nodes. Dealing with partial
disconnections while establishing communications via dynamic routing over rapidly
changing unidirectional links poses critical research challenges for the mobile networking
community. Page 33

Seminar Report-2005 Mobile Networking For Smart Dust
Department of Computer Science
¢ J. M. Kahn, R. H. Katz (ACM Fellow), K. S. J. Pister. Next Century Challenges:
Mobile Networking for Smart Dust
¢ Brett Warneke, Matt Last, Brian Liebowitz and Kristofer S.J. Pister .In Smart Dust:
Communicating with a Cubic- Millimeter Computer,2001 IEEE
¢ Ross Anderson, Haowen Chan and Adrian Perrig .In Key Infection: Smart Trust
For Smart Dust, May 2003
¢ H. Chan, A. Perrig, and D. Song. Random key predistribution schemes for sensor
networks. In IEEE Symposium on Security and Privacy, May 2003.
¢ Philip Buonadonna, Jason Hill and
David Culler. In Active Message
Communication for Tiny Networked Sensors, February 2003.
¢ and implimentations/individual_57.html
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