Next Century Challenges:
Mobile Networking for “Smart Dust”
J. M. Kahn, R. H. Katz (ACM Fellow), K. S. J. Pister
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
{jmk, randy, pister}@eecs.berkeley.edu
Abstract
Large-scale networks of wireless sensors are becoming an
active topic of research. Advances in hardware technology
and engineering design have led to dramatic reductions in
size, power consumption and cost for digital circuitry, wireless communications and Micro ElectroMechanical Systems
(MEMS). This has enabled very compact, autonomous and
mobile nodes, each containing one or more sensors, computation and communication capabilities, and a power supply.
The missing ingredient is the networking and applications
layers needed to harness this revolutionary capability into a
complete system. We review the key elements of the emergent technology of “Smart Dust” and outline the research
challenges they present to the mobile networking and systems community, which must provide coherent connectivity
to large numbers of mobile network nodes co-located within
a small volume.
1 Introduction
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 Micro ElectroMechanical Systems (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.
Berkeley’s Smart Dust project, 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. The research team is confident that they can incorporate
the requisite sensing, communication, and computing hardware, along with a power supply, in a volume no more than
a few cubic millimeters, while still achieving impressive
performance in terms of sensor functionality and communications capability. These millimeter-scale nodes are called
“Smart Dust.” 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. At least one
popular science fiction book has articulated just such a
vision [12].
In this paper, we are concerned with the networking and
applications challenges presented by this radical new technology. These kinds of networking nodes must consume
extremely low power, communicate at bit rates measured in
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
tracking for virtually any kind of physical object.
The study of “Smart Dust systems” is very new. The main
purpose of this paper is to present some of the technological
opportunities and challenges, with the goal of getting more
systems-level researchers interested in this critical area. The
remainder of this paper is organized as follows. Section 2
presents an overview of the technology that underlies Smart
Dust. Section 3 outlines the key networking challenges presented by this technology. In Section 4, we describe some of
the potential applications of Smart Dust and the challenges
they pose. Section 5 discusses related projects from the
research community. Section 6 presents our summary and
conclusions.
2 Smart Dust Technology
A Smart Dust mote is illustrated in Figure 1. 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
to microwatt levels, and if careful power management strategies are 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 a communications 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., highfrequency) 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, bandpass filtering and demodulation circuitry, and additional circuitry is required if the transmissions of a large number of
dust motes are to be multiplexed using time-, frequency- or
code-division multiple access [6].
An attractive alternative is to employ free-space optical
transmission. Kahn and Pister’s studies [6] 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 the 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 another’s line of sight
to the BTS. Such blockage is unlikely, in view of the dust
motes’ 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
Figure 1. Smart dust mote, containing microfabricated sensors, optical receiver, passive and active optical transmitters, signalprocessing and control circuitry, and power sources.
1-2 mm
Thick-Film Battery
Solar Cell
Power Capacitor
Analog I/O, DSP, Control
Active Transmitter with Laser
Diode and Beam Steering
Passive Transmitter with
Corner-Cube Retroreflector
Sensors
Receiver with Photodetector
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.
Another advantage of free-space optical transmission is that
a special MEMS structure make it possible for dust motes to
use passive optical transmission techniques, i.e., to transmit
modulated optical signals without supplying any optical
power. This structure is a corner-cube retroreflector, or CCR
(see Figure 2). It comprises three mutually perpendicular
mirrors of gold-coated polysilicon. The CCR has the property that any incident ray of light is reflected back to the
source (provided that it is incident within a certain range of
angles centered about the cube’s body diagonal). If one of
the mirrors is misaligned, this retroreflection property is
spoiled. The microfabricated CCR includes an electrostatic
actuator that can deflect one of the mirrors at kilohertz rates.
It has been demonstrated that a CCR illuminated by an
external light source can transmit back a modulated signal at
kilobits per second. Since the dust mote itself does not emit
light, the passive transmitter consumes little power. Using a
microfabricated CCR, Chu and Pister have demonstrated
data transmission at a bit rate up to 1 kilobit per second, and
over a range up to 150 meters, using a 5-milliwatt illuminating laser [2].
It should be emphasized that CCR-based passive optical
links require an uninterrupted line-of-sight path. Moreover,
a CCR-based passive transmitter is inherently directional; a
CCR can transmit to the BTS only when the CCR body
diagonal happens to point directly toward the BTS, within a
few tens of degrees. A passive transmitter can be made more
omnidirectional by employing several CCRs oriented in different directions, at the expense of increased dust mote size.
If a dust mote employs only one or a few CCRs, the lack of
omnidirectional transmission has important implications for
feasible network routing strategies (see Section 3.1.2).
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. 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 Pister’s analysis show that this uplink scheme achieves several kilobits
per second over hundreds of meters in full sunlight [6]. At
night, in clear, still air, the range should extend to several
kilometers. Because the camera uses an imaging process to
separate the simultaneous transmissions from dust motes at
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 of
visible or near-infrared light. This does not require any
coordination among the dust motes, and thus, it does not
complicate their design.
When the application requires dust motes to use active optical transmitters, MEMS technology can be used to assemble
a semiconductor laser, a collimating lens and a beam-steering micro-mirror, as shown in Figure 1. Active transmitters
make possible peer-to-peer communication between dust
motes, provided there exists a line-of-sight path between
them. Power consumption imposes a trade-off between
bandwidth and range. The dust motes can communication
over longer ranges (tens of kilometers) at low data rates or
higher bit rates (megabits per second) over shorter distances. The relatively high power consumption of semiconductor lasers (of the order of 1 milliwatt) dictates that these
active transmitters be used for short-duration burst-mode
communication only. Sensor networks using active dust
mote transmitters will require some protocol for dust motes
to aim their beams toward the receiving parties.
3 Mobile Networking Challenges
3.1 Overview
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.
3.1.1 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
Figure 2. Microfabricated corner-cube retroreflector,
consisting of three gold-coated polysilicon mirrors. The base
mirror can be deflected electrostatically, modulating the
optical signal reflected from the device (taken from [2]).
200 Β΅m
angular spread in order to achieve a high signal-to-noise
ratio with acceptably small transmitter power. Specular
reflection may not significantly increase a beam’s angular
spread, but the existence of a properly aligned specular
reflector would be a rare event. Diffuse reflection scatters a
beam’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. Constraints 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.
3.1.2 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 a
pair of binoculars, which is aimed by a human operator.
In certain applications using active dust mote transmitters, it
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 mote’s optical
receiver probably cannot employ an imaging or non-imaging optical concentrator in front of the photodetector. As a
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, it
should not be necessary to aim the dust mote receiver.
The dust mote’s transmitter will exhibit markedly different
directional characteristics than its receiver. A passive dust
mote transmitter is based on the CCR. This device reflects
light directly back to the source within a narrow beam1, provided that it is illuminated from a direction that lies within a
Figure 3. Design of a free-space optical network in which a base-station transceiver communicates simultaneously with a
collection of many dust motes (only one dust mote is shown). A single laser at the base station supplies optical power for the
downlink and the uplink.
Downlink
Laser
Uplink
CCD Corner-Cube
Uplink
Data In
Data
Image
Sensor
Retroreflector
Data In
PhotoDownlink
Data Out
detector
Base-Station Transceiver
Dust Mote
Signal Selection
and Processing
Uplink
Data ...
Out1 OutN
Array
Unmodulated Interrogation
Modulated Reflected
Lens
Lens
Modulated Downlink Data or
Beam for Uplink
Beam for Uplink
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 a
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 CCR’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 a 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. It
should employ a narrow beamwidth, 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 a
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
mote’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, a
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
mote power, the other nodes should acknowledge this dust
mote’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 [4]. In
Smart Dust networks, the uplink (dust mote to BTS) uses
space-division multiplexing. As discussed in Section 2,
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
. (1)
Here, C is a constant, is the average transmitted energy
per bit, is the bit rate, A is the receiver light collection
area2, is the receiver noise power spectral density, d is
the link transmission distance, and Ξ¦ is the transmitter beam
angular spread. This expression assumes that Ξ¦ 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
is proportional to , i.e., the energy per bit is minimized if packets are transmitted in short bursts at a high bit
rate.
The average transmitter power (during transmission of a
packet) is . Hence, transmission at a high bit
rate requires a high-power transmitter. In practice,
should be chosen to be as high as possible, within constraints posed by eye safety and by dust mote current-drive
limitations. Rewriting (1) in terms of , we obtain
. (2)
Given a limit on , to maximize the bit rate and the
distance d, we should maximize the receiver area A and
minimize Ξ¦, 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 . 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.
1. In a well-designed CCR, the angular spread of the reflected
beam is limited by diffraction to the order of , where Ξ» is
the optical wavelength and a is the effective diameter of the CCR.
ΞΈ Ξ» ∼ ⁄ a
2. On a link from BTS to dust mote or from dust mote to dust
mote, A corresponds to the dust mote photodetector area. On a link
from dust mote to BTS, A corresponds to the BTS camera’s
entrance aperture area.
SNR C
Eb
2
RbA2
N0d4
Ξ¦4 = ⋅ -------------------
Eb
Rb
N0
Eb Rb
–1 2⁄
Pt Eb Rb = ⁄
Pt
Pt
SNR C
Pt
2
A2
N0Rbd4
Ξ¦4 = ⋅ --------------------------
Pt Rb
Rb d–4 ∝
3.2 Mobile Networking Opportunities
3.2.1 Overview
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 lowlatency 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 transmitters.
3.2.2 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
receiver’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.
3.2.3 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 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 [5]. 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 wideaperture 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.
3.2.4 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.
4 Applications
4.1 Introduction
Depending on the application, individual dust motes may be
affixed to objects that one wishes to monitor, or a large collection of motes may simply be dispersed (and floating!) at
random throughout an environment. The motes record sensor readings and, when queried, report these readings via
the optical techniques described in Section 2. In some applications, dust motes will communicate directly (and passively) with the BTS, In others, peer-to-peer active
communication between dust motes will be used to relay
information to the BTS. Depending on the application, the
base station may be separated from the dust motes by distances ranging from tens of meters to kilometers.
For example, the BTS may actually reside in a hand-held
unit, much like a pair of binoculars. This permits the user to
simultaneously view a scene while displaying measured
data overlaid on top of it. As another example, the BTS may
reside in a small flying vehicle, which flies over an area to
query the Smart Dust.
We envision numerous civilian and military applications for
Smart Dust. Smart Dust may be deployed over a region to
record data for meteorological, geophysical or planetary
research. It may be employed to perform measurements in
environments where wired sensors are unusable or lead to
measurement errors. Examples include instrumentation of
semiconductor processing chambers, rotating machinery,
wind tunnels, and anechoic chambers. In biological
research, Smart Dust may be used to monitor the movements and internal processes of insects or other small animals. Considering the military arena, Smart Dust may be
deployed for stealthy monitoring of a hostile environment,
e.g., for verification of treaty compliance. Here, acoustic,
vibration or magnetic field sensors could detect the passage
of vehicles and other equipment. Smart Dust could be used
for perimeter surveillance, or to detect the presence of
chemical or biological agents on a battlefield.
The overarching applications challenge, from a processing
and communications viewpoint, is how to implement complex “ensemble” behavior from a large number of individual, relatively simple sensors. This is sometimes called
“beehive”, “swarm”, or “emergent” behavior. A critical
enabler is the ability for the sensors to communicate their
readings with each other and with the more centralized
intelligent processor residing at the base station. Proper
design of the network is the key. We describe an applications scenario and some of the technology challenges to
implement such a system in this section.
4.2 Scenario: Multi-Sensor Emergent
Behavior
It is useful for sensors to operate in ensembles. Rather than
implementing a broad range of sensors in a single integrated
circuit, it is possible to simply deploy a mixture of different
sensors in a given geographical area and allow them to selforganize.
Sensors are typically specialized to detect certain signatures. One kind detects motion, another heat, and a third
sound. When one sensor detects its critical event signature,
it makes other nearby sensors aware of its detection. They
then orient their sensing function in a particular, signaturespecific way. For example, a simple motion-detecting sensor
might cue more sophisticated sensors detecting thermal or
other radiation properties. The array, acting as an ensemble,
not only performs the operation of detecting an intruder, but
demonstrates more intelligent processing, by distinguishing
between one that is a human and another that is a small animal (e.g., the former has a body heat signature spread over a
larger volume than the latter).
A more complex sensor cued in this fashion may then
increase its own scan rate to obtain a higher-resolution signature, or dedicate its detection energy budget into a particular narrow band or a specific direction. These operations
have implications for power consumption. Maximizing
detection probability and resolution while minimizing
power consumption is a key optimization challenge.
4.3 Technology Approaches for Realizing the
Scenario
There are two ways to construct such a cueing system. The
first is a centralized scheme. The motion sensor communicates with the BTS, which in turn communicates with a
nearby heat sensor. If passive communications techniques
can be used, this may well be the most power-efficient way
to propagate the detection information.
The centralized/passive schemes cannot be used if the lineof-sight path is blocked, or if the probe revisit rate is too
infrequent to meet detection latency constraints. In these
cases, the detecting mote must employ an active transmitter.
If the line-of-sight path is blocked, then the mote will need
to use ad hoc, multihop techniques to communicate with the
BTS or nearby sensor nodes.
Detecting a blocked path between a mote and the BTS is not
difficult (note that a blocked path and a disabled BTS can be
treated in the same way). We can assume some maximum
duty cycle between probe visits. If sufficient time has passed
since the last visit, the mote can assume that it is blocked.
Weighted by the importance of what it has detected, the
mote can decide to go active.
Building a multihop route in this environment is quite challenging. Because of the directionality of the on-board laser,
active transmission in all directions is not feasible, and we
cannot assume that if a next hop node receives our transmission that we will be able to receive a transmission from it.
A possible scheme is the following. A node transmits for a
short burst and waits for an ACK response from any listening node to determine that its transmission has been
received. Determining true reachability between pairs of
motes requires a full four phase handshake (“Can you see
me?” “Yes, I can see you. Can you see me?” “Yes” “Good.
We can communicate with each other.”). This must be executed in the context of appropriate timeouts and made
robust to dynamic changes in the positions of the communicating nodes, which may be floating in the air.
Routing tables can be constructed from such pairwise discovery of connectivity. However, standard routing algorithms, like RIP, OSPF, and DVRMP, assume bidirectional
and symmetric links. This will not always be the case for
Smart Dust. It may be possible for mote A to communicate
with mode B, but not vice versa. Even if the communications is bidirectional, it need not exhibit the same bandwidth
or loss characteristics in both directions.
Therefore, new routing algorithms must be developed to
deal with the general case of links that are unidirectional
and/or asymmetric in their performance. A strong group at
INRIA in France has been leading the IETF Unidirectional
Link Routing Working Group discussions on these issues
[3][13].
Unfortunately, the current efforts are focusing on supporting
high-bandwidth unidirectional links where all nodes have at
least low-bandwidth bidirectional links (e.g., a high-bandwidth satellite link superimposed on nodes interconnected
via slow-speed telephone links). Even modifying existing
algorithms will not help much, since the connectivity
among floating dust motes is dynamic with short time
scales. The more general case still remains to be addressed.
4.4 Other Applications Issues
One possible improvement is to make use of emerging
MEMS technology for on-board inertial navigation circuits
[1] to make sensors more aware of near neighbors even as
they drift out of line-of-sight of the BTS. The BTS can
determine the relative location of dust motes within its field
of view. It could then disseminate this “near neighbor information” to motes able to observe its probe beam. The onboard inertial navigation capability, combined with these
periodic relative location “snapshots”, could assist motes in
orienting their laser and detector optics to improve their
ability to establish links with nearby motes.
5 Related Projects
Several projects have recently been initiated to investigate a
variety of communications research aspects of distributed
sensor networks. The following description is by no means
exhaustive.
The Factoid Project [8] at the Compaq Palo Alto Western
Research Laboratory (WRL) is developing a portable device
small enough to be attached to a key chain. The device collects announcements from broadcasting devices in the environment, and these can be uploaded to a user’s home
basestation. In its first generation, the prototype devices are
much larger than smart dust motes, communications is
accomplished via RF transmission, and the networking
depends on short-range point-to-point links.
The Wireless Integrated Network Sensors (WINS) Project
[7] at UCLA is very similar in spirit to what has been
described in this paper. It is developing low power MEMSbased devices that in addition to sensing and actuating can
also communicate. The essential difference is that WINS
has chosen to concentrate on RF communications over short
distances.
The Ultralow Power Wireless Sensor Project [9] at MIT is
another project that focuses on low power sensing devices
that also communicate. The primary thrust is extremely low
power operation. The prototype system will transmit over a
range of data rates, from 1 bit/sec to 1 megabit/sec, with
transmission power levels that span from 10 microwatts to
10 milliwatts. The RF communications subsystem is being
developed for the project by Analog Devices. Again, optical
technologies are not being investigated. Ultimately the
design team will need to face the multi-hop wireless networking protocol issues outlined in this paper (e.g., see [10],
[11]).
6 Summary and Conclusions
The research community is searching for a new environments in which to generate innovative ideas and prove their
effectiveness. A new paradigm beyond desktop computing
is capturing the imaginations of systems designs: the socalled “post-PC” era. Wireless sensor networks is one area
that promises to yield important applications and demands
new approaches to traditional networking problems.
We have described Smart Dust, 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.
Acknowledgments
Kahn and Pister’s research is supported in part by DARPA
Contract DABT63-98-1-0018, “Smart Dust.” Katz and Pister’s research is supported in part by a new DARPA Contract, “Endeavour Expedition to the Information Technology
Future.”
7 References
[1] B. Boser, “Electronics for Micromachined Inertial
Sensors,” Transducers’97, Chicago, Il., (June 1997),
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[2] P. B. Chu, N. R. Lo, E. C. Berg, K. S. J. Pister, “Optical Communication Using Micro Corner Cube
Reflectors”, Proc. of IEEE MEMS Workshop,
Nagoya, Japan, (January 1997), pp. 350-355.
[3] W. Dabbous, E. Duros, T. Ernst, “Dynamic Routing in
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[4] F. Gfeller and W. Hirt, “A Robust Wireless Infrared
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[6] V. S. Hsu, J. M. Kahn, and K. S. J. Pister, “Wireless
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Research Laboratory Memorandum Number M98/2,
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[7] http://www.janet.ucla.edu/WINS.
[8] http://www.research.digital.com/wrl/projects/Factoid/
index.html.
[9] http://www-mtl.mit.edu/~jimg/project_top.html.
[10] J. Jubin, J. D. Turnow, “The DARPA Packet Radio
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[11] G. S. Lauer, “Packet-Radio Networks,” Chapter 11 in
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[12] N. Stephenson, The Diamond Age, Bantam Books,
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[13] Unidirectional Link Routing Protocol Working Group
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