MICA: A WIRELESS PLATFORM FOR DEEPLY EMBEDDED NETWORKS
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MICA: A WIRELESS PLATFORM
FOR DEEPLY EMBEDDED
NETWORKS
LOW-POWER INTEGRATION OF SENSING, COMMUNICATION, AND
COMPUTATION REQUIRES A NEW APPROACH TO WIRELESS DESIGN. FLEXIBLE
INTERFACES AND PRIMITIVE ACCELERATORS ENABLE AGGRESSIVE SYSTEM-
LEVEL OPTIMIZATIONS.
Current wireless systems only Exploiting local communication and appli-
scratch the surface of possibilities emerging cation-specific protocols can drastically reduce
from the integration of low-power commu- size, cost, and power use in wireless devices.
nication, sensing, energy storage, and com- These devices won’t need to communicate
putation. Generally, when people consider with the nearest high-power control tower,
wireless devices they think of such items as but only with their local peers. Peer-to-peer
cell phones or personal digital assistants, items networking techniques provide a flexible
with high costs and energy requirements that meshlike interconnect that shuttles data
target specific, highly standardized applica- between thousands of tiny embedded devices.
tions and rely on a powerful infrastructure. A A handful of the devices might act as bridges
new direction in wireless system design, how- between a local embedded communication
Jason L. Hill ever, is extending wireless connectivity to mesh and a traditional data network. Figure 1
small, low-cost embedded devices for a wide depicts a precision agriculture deployment—
David E. Culler range of applications. an active area of application research.
Application possibilities for miniature wire- Researchers are developing new algorithms for
University of California, less sensing devices include inventory asset data aggregation, ad hoc routing, and distrib-
tracking, roadside traffic pattern and open uted signal processing for low-power peer-to-
Berkeley parking spot detection, individual plant mon- peer wireless networks. As researchers envision
itoring for precision agriculture, habitat mon- smaller and lower-cost devices, the range of
itoring in nature preserves, and advanced application scenarios grows dramatically.
building security and automation. The mili- The Mica wireless platform serves as a foun-
tary could blanket fields with sensors to detect dation for the emerging possibilities. Pictured
troop movement. Sensors might enable civil in Figure 2, the Mica platform measures 1.25
engineers to gauge the structural integrity of × 2.25 inches, runs the TinyOS operating sys-
buildings and bridges after earthquakes or tem (http://webs.cs.berkeley.edu/tos), and is
fires. Integrating hundreds of thousands of suited for self-configuring multihop wireless
sensing and control points could provide new networks. With sensing, communication, and
insights into the state of the world. I/O capabilities, Mica can simultaneously act
12 0272-1732/02/$17.00 2002 IEEEFigure 1. Ad hoc, wireless embedded network for precision agriculture. Sensors detect tem-
perature, light levels, and soil moisture at hundreds of points across a field. The system
communicates the data over a multihop network for analysis.
as a data router, sensor interface, and control
point. Nearly a hundred research groups cur-
rently use Mica nodes to explore networking
techniques, data analysis, distributed algo-
rithms, networked services, programming,
and novel applications. We created Mica with
off-the-shelf hardware, but the architecture
and its capabilities represent what could be
implemented in just a few square millimeters
of custom silicon. Mica’s flexible design serves
as a building block for creating efficient appli-
cation-specific protocols. Instead of defining
narrow, standardized application interfaces,
Mica provides a set of richly interconnected
primitives (such as data serializers and timing
extractors) to facilitate cross-layer optimiza-
tions. To explore novel systems approaches,
researchers can develop customized protocols Figure 2. Mica node.
tailored to their application; Mica does not
require use of predefined protocols.
First, power consumption must be drastically
Conventional wireless design comparison reduced. A deeply embedded, battery-operat-
An explanation of the current wireless archi- ed device might need to operate for years on a
tectures and their shortcomings for deeply pair of AA batteries or a lithium coin cell.
embedded devices illustrates the advantages of Power consumption must average in the
the Mica network architecture. Deeply embed- microamps range, requiring powering down
ded wireless networks differ in several key most of the device much of the time—a cell
respects from traditional wireless scenarios. phone would do well to last a couple of weeks
NOVEMBER–DECEMBER 2002 13MICA
devices, protocol processing can consume hun-
Display/keyboard dreds of milliwatts before making significant
Audio I/O battery life impact. In a deeply embedded wire-
less network, however, devices typically require
less than a milliwatt to communicate with their
neighbor nodes. This drastic reduction in
transmission power must be complemented
Voice codec Application controller by a highly efficient protocol processing mech-
anism. In wireless Ethernet (IEEE 802.11b)
cards, radio-frequency (RF) transmission
power ranges from just 25 to 100 mW, yet
DSP device power consumption can exceed
2,000 mW when active due to protocols that
are optimized for high data rates. A pair of AA
batteries would last less than eight hours with
RF protocol processing a standard 802.11 card. Thus, in deeply
embedded wireless networks, protocol pro-
cessing must be optimized for ultralow-power
Power regulator operation, not for high data rates.
Traditional and deeply embedded wireless
RF transceiver devices also differ in their required level of flex-
ibility. Peer-to-peer protocols and in-network
processing implementations must adapt to
Figure 3. Typical cell phone architecture. The design is parti- meet application needs in sensor networks.
tioned into highly specialized pieces, limiting new applica- Currently, cell phones use highly partitioned
tion scenarios. designs; a generic microcontroller provides the
user interface and device configuration, dedi-
cated digital signal processors process audio
on two AA batteries. This hundredfold power with a single and highly specific algorithm, and
consumption reduction mandates drastic complex radio controllers provide the low-level
changes to system architecture. Second, many channel processing. Figure 3 depicts a gener-
deeply embedded systems cannot rely on a pre- alized cell phone architecture. A prolonged
deployed, powerful infrastructure for support. standardization process allowed for high opti-
Cell phone protocols, for example, exploit mization for specific functions in each system
high-powered base stations to reduce power component, with narrow interfaces between
consumption in mobile nodes. In a peer-to- components. New services are typically over-
peer multihop network, typically, only the last laid on the established structure. For example,
hop will communicate with a base station— on second-generation cell phone systems, a
most of the nodes would be located outside of point-to-point layer over what is essentially an
the station’s direct communication range. An audio stream provides an IP data communi-
advantage of a peer-to-peer architecture is that cation stack. The 802.11 designs are also high-
it only requires small communication distances ly partitioned—each of the components
for each transmission. Finally, whereas most service a specific, highly standardized aspect:
wireless devices carry out a single, highly stan-
dardized function, deeply embedded networks • A baseband controller implements the
must be suited to a wide variety of applica- radio channel interface (including spec-
tions. This requires a more general-purpose trum sequencing, framing, and coding);
system design, but also allows employing rad- • A bus controller services the PCMCIA
ical, highly efficient algorithms. interface; and
As wireless transmission power decreases, • A microcontroller shuttles data units
the significance of protocol processing increas- between these controllers according to a
es. An average cell phone uses 750 to specific media access control (MAC)
1,000mW to reach a distant cell tower. In such protocol.
14 IEEE MICROThis strict partitioning makes it difficult for in-network processing to reduce power con-
devices to adapt their behavior to meet appli- sumption by orders of magnitude. For example,
cation-specific requirements. Additionally, the if sensor data is sampled only once per minute,
complex controllers surrounding the radio it might be acceptable to delay transferring the
consume significant power bringing the radio data to the consumer for several seconds, allow-
online, making low-power operation difficult.1 ing the network to coordinate many such flows
The Bluetooth wireless specification targets efficiently while operating at a low duty cycle.
low-power personal-area wireless communi- Such optimizations can extend battery life from
cation. Originally envisioned to replace the weeks to years.
wires of modern PCs—a wireless USB—the Our deeply embedded system approach
Bluetooth design is based on a master-slave emphasizes flexibility in ultralow-power oper-
model in which a single master device com- ation and the opportunity to produce system-
municates with a few peripherals (fewer than level optimization. Rather than a narrow,
eight). While the specification lets devices par- standardized interface to a complex radio con-
ticipate in logical communication groups dis- troller, our deeply embedded designs use sim-
tinct from the primary master-slave ple radios with much of the RF channel
relationship, it has a powerful master in direct control exposed to software through a rich
control of a small collection of physically close interface. Rather than dedicated protocol con-
low-power devices. In the deeply embedded trollers, we provide simple accelerators for
networks we envision—a mesh of thousands protocol primitives that are composed in soft-
of interconnected embedded nodes—the key ware. Rather than partitioning the design into
to power, cost, and size reduction is neighbors dedicated subsystems, this new approach
forwarding and routing data. Ad hoc, multi- pools processing resources and uses fine-
hop interconnections could be simulated as grained multithreading to dynamically allo-
an overlay on the Bluetooth master-slave phys- cate subtask processing. While each of these
ical layer, but are likely to be inefficient. Addi- differences affects performance on simple
tionally, the Bluetooth device power tasks, their real impact is made by enabling
consumption is still an order of magnitude high-level software optimizations.
above our intended target—Bluetooth
chipsets consume 115 mW to communicate Mica design
to a master node.2 Similar to IEEE 802.11 We designed the Mica platform to aid sys-
devices, current Bluetooth designs are parti- tem-level exploration, providing a rich inter-
tioned to implement a single rigid protocol in connection of protocol primitives that
conjunction with a well-powered host device, designers can flexibly assemble into applica-
such as a laptop or, eventually, a personal dig- tion-specific protocols. Our design’s power
ital assistant. and time-efficient primitives significantly
improve key system capabilities including
Exploiting wireless design low-power device startup, time synchroniza-
For the deeply embedded approach, it’s tion, power-aware routing, and localization.
essential that researchers explore radical direc- Mica combines communication, computa-
tions in system-level optimization. Cell phones, tion, power management, and sensing into a
wireless local area networks, and Bluetooth pro- small experimental platform. The current form
tocols must meet strict bandwidth and latency factor (1.25 × 2.25 inch) is similar in size to a
requirements. Cell phone voice traffic trans- pair of AA batteries, although we have com-
missions cannot suffer signal delays that cause pressed a variant of the design to about the size
noticeable audio variations. Additionally, a of a 2.5-centimeter coin (0.5 cm thick). The
small transmission round-trip time between standby current for Mica’s components is a few
users is required to keep an interactive conver- microamps, enabling applications that last for
sation flowing smoothly. These demands several years on a single set of batteries. Mica
require that these devices meet strict protocol improves experimental flexibility by including
design specifications. In deeply embedded wire- an expansion bus that connects to a wide array
less networks, however, we can exploit trade- of sensor boards. Our current batch of sensor
offs between bandwidth, latency, and boards includes support for monitoring ther-
NOVEMBER–DECEMBER 2002 15MICA
ture with a firmware upload
51-pin I/O expansion connector or during field maintenance.
Eight In our design, however, the
Eight
Digital I/O programming embedded network can be
analog I/Os
lines
dynamically reprogrammed
during routine use. The
Coprocessor coprocessor handling the
DS2401 unique ID
Atmega103 microcontroller
wireless reprogramming is an
Atmel AT90LS2343, 8-pin,
4-Mbit external flash flash-based microcontroller
with an internal system clock
Transmission Hardware
power control accelerators Power regulation MAX1678 (3 V) and five general-purpose I/O
pins. Additionally, to provide
each node with a unique
TR1000 radio transceiver
identification, we include a
Maxim DS2401 silicon seri-
Figure 4. Mica architecture block diagram. The direct connection between application con- al number—a low-cost ROM
troller and transceiver enables flexibility in meeting application demands. Hardware acceler- device with a minimal elec-
ations optionally assist in communication protocols. tronic interface and no power
requirements.
The Mica radio module
mal temperature, barometric pressure, mag- consists of an RF Monolithics TR1000 trans-
netic fields, light, passive infrared frequency, ceiver and a set of discrete components to
acceleration, vibration, and acoustics. operate the radio. Software can externally set
the transceiver’s transmission radius to range
Block diagram overview from inches to hundreds of feet, and it oper-
Figure 4 shows the Mica architecture, con- ates at communication rates up to 115 kilobits
sisting of five major modules: processing, RF per second. This amplitude-shift-keying-
communication, power management, I/O based radio has a fixed transmission frequen-
expansion, and secondary storage. A quick cy of 916.5 MHz. At maximum transmission
survey of the major modules provides a gen- power, it outputs approximately 0.75 mW—
eral overview for the system as a whole, hence, roughly 1/1,000 the power of a cell phone—
a detailed bill of materials, device schematic and consumes 21 mW. With a maximum
and datasheet for all components mentioned receive sensitivity of less than 95 dBm, or deci-
can be found at http://www.tinyos.net. bels relevant to one milliwatt, it provides an
The main microcontroller is an Atmel unobstructed communication range of
Atmega103L or Atmega128 running at 4 approximately 200 feet. In receive mode, the
MHz and delivering about four million radio consumes 15 mW regardless of whether
instructions per second (MIPS). This 8-bit actual communication is occurring. The radio
microcontroller has interface gives direct control over the trans-
mitted signal, allowing the modulation
• a 128-Kbyte flash program memory, scheme, coding, framing, and MAC protocol
• a 4-Kbyte static RAM, to be determined in software. In addition,
• an internal 8-channel 10-bit analog-to- operating system software controls radio
digital converter, transmission strength and can sense the
• three hardware timers, strength of the receive signal.
• 48 general-purpose I/O lines, A 4-Mbit Atmel AT45DB041B serial flash
• one external universal asynchronous chip provides persistent data storage. We
receiver transmitter (UART), and chose this chip because of its interface and
• one serial peripheral interface (SPI) port. small footprint, 8-pin small-outline integrat-
ed circuit. It stores sensor data logs and tem-
Normally, programming of these embed- porarily holds program images received over
ded microcontrollers occurs during manufac- the network interface. To hold a complete
16 IEEE MICROprogram, the flash must be larger than the Table 1. Breakdown of active and idle power consumption for Mica
128-Kbyte program memory. This prevented hardware.
the project from considering use of the lower
power, electronically-erasable-programmable- Component Active (mW) Idle (µW)
ROM-based solutions because they are gen- CPU 16.5 30
erally smaller than 32 Kbytes. Radio 21 (transmit mode) 0
We designed the power subsystem to regu- 15 (receive mode)
late the system’s supply voltage; a Maxim1678 Silicon ID 0.015 0
dc-dc converter provides a constant 3.3-V External flash 45 30
supply. Mica operates with inexpensive alka- LEDs 10 0
line batteries that produce between 3.2 and
2 V (for example, a pair of AA batteries). We
chose the Maxim chip because of its small any RS-232-protocol-based device. Dozens of
form factor and high efficiency. The convert- sensor boards with a variety of sensors have
er takes input voltage as low as 1.1 V and been developed that use this expansion con-
boosts it to 3 V. This supplies a clean, stable nector. It has even been used to let the Mica
voltage source for the rest of the system. Input node control a handful of inch-sized micro-
voltage significantly affects the TR1000 trans- robotic platforms.
mission strength and its receive sensitivity.
The converter chip increases the system’s avail- Operating system
able power because more than 50 percent of The Mica hardware platform uses the
the energy in an alkaline cell lies below 1.2 V, TinyOS multithreading execution model
which is unusable without a boost converter. developed at the University of California,
For ultralow-power sleep mode, disabling the Berkeley.4 TinyOS is an event-based operating
power system lets the system run directly off system in which individual components act
the unregulated input voltage, reducing power together to form a complete application and
consumption by the boost converter and the to implement all system functions. This com-
microcontroller. The radio will not operate, ponent-based structure lets an application
however, without the boost converter enabled. designer select from a catalog of system com-
Table 1 summarizes Mica’s node component ponents to meet application-specific goals.
power consumption. The TinyOS execution model provides
The I/O subsystem interface consists of a fine-grained allocation of processing resources
51-pin expansion connector that we designed across multiple components. This lets high-
to interface with a variety of sensing and pro- level application code and low-level protocol
gramming boards. We divided the connector code coexist on a single CPU. Each compo-
into the following sections: nent acts like a finite state machine that uses
commands and events to transition from one
• eight analog lines, state to the next. There is no blocking or wait-
• eight power control lines, ing in TinyOS. This forces components, after
• three pulse-width-modulated lines, finishing a calculation, to release the CPU for
• two analog compare lines, use by other components.
• four external interrupt lines, TinyOS performs high-level, long-running
• an I2C-bus from Philips Semiconductor,3 application processing in special execution
• an SPI bus, contexts, called tasks. When executed, a task
• a serial port, and runs to completion and other tasks cannot
• a collection of lines dedicated to pro- preempt it. However, low-level system events
gramming the microcontrollers. can preempt tasks, allowing TinyOS to tem-
porarily reallocate the CPU to low-level sys-
The expansion connector can also program tem processing. TinyOS shields the
the device and communicate with other application-level processing from the under-
devices, such as a PC serving as a gateway lying concurrent scheduling, yet exposes low-
node. Additionally, it contains a standard level system components to meet their
UART interface to control or provide data to real-time requirements.
NOVEMBER–DECEMBER 2002 17MICA
In contrast, most wireless devices use ded- components determine all aspects of the com-
icated protocol processors to handle low-level munication protocol. In contrast, Bluetooth
processing. This partitioned approach requires radio chipsets dictate bit rates, signaling
enough power in the application and system- schemes, data-encoding methods, framing,
level processors to handle the peak demand; MAC protocols, and the routing scheme to
though system demand for these two proces- the host processor. With Bluetooth, the oper-
sors might never occur simultaneously. The ating system can only spool packets across the
pooled processing approach used in TinyOS interface; delays through the interface have a
allows dynamically allocating a single CPU to large, unpredictable variance, and the system
a given task, so peak demand is close to aver- or application components cannot observe the
age processing. For example, the radio pack- activity or physical characteristics of the radio
et start symbol detection requires a peak of channel. Researchers have observed similar
3 MIPS, but only at the instant a packet is shortcomings with IEEE 802.11 designs.5 Fig-
received (less than one percent of the time). ure 5 depicts a standard packet-based proto-
Suppose the signal processing algorithms to col implemented on the Mica node.
analyze sensor readings require 2 MIPS each The TR1000 radio used on the Mica gives
time a sample arrives. A partitioned system the controller direct access to the signal
would require a total of 5 MIPS; however, strength of the incoming RF transmission. It
using a shared pool approach, slightly more also allows sampling the level of background
than 3 MIPS could handle this application. noise during periods when there is no active
Additionally, in a real application with a mix transmission and adjusting transmission
of operations of varying cost, efficiency strength. Using this information in multihop
decreases further because of overprovisioning networking applications can dramatically
of the partitioned system to the worst case. improve efficiency. Interactions between
Furthermore, if a more efficient mechanism transmitter and receiver are very predictable,
for performing start symbol detection were as is the delay through the radio interface.
selected for a particular application scenario, Because software can quickly and predictably
TinyOS could reallocate the freed resource. turn radio power on or off, low duty cycle
The biggest advance gained from exploiting operation can occur without global coordi-
a shared pool of computation is that the inter- nation or complex time slotting. This direct,
faces between system components are not low-level interface to the radio provides flex-
constrained by narrow chip-to-chip communi- ibility for application developers. Researchers
cation mechanisms defined by physical hard- from the University of California, Los Ange-
ware. System components can provide rich les, have exploited this flexibility to create
interfaces to other components to enable cross- energy-aware MAC protocols.6
layer optimization. Additionally, software-based
interfaces facilitate interface evolution as new Communication accelerators
features are added to system components. The drawback of a low-level interface to the
radio is that it places a significant overhead on
Raw radio interface the main controller, because of the frequency
The radio subsystem is a prime example of of programmed I/O operations and the inef-
the rich simple interface approach. From this ficiency of conventional instruction sets for
subsystem’s low-level interface, designers can expressing these operations. It’s inefficient to
build customized arbitrary signaling proto- handle the bit-serial sliding window correla-
cols to meet application requirements. Only tion operation required for start symbol detec-
the radio dictates certain parameters, that is, tion on a general-purpose data path, although
signaling should occur over a half-duplex bit- this takes just a few gates to implement in
serial link using amplitude shift keying with a hardware. The design of dedicated protocol
minimum physical bit time of 10 microsec- processors typically contains support for such
onds (µs), and the need for a rough direct cur- operations. To compensate for this, the Mica
rent (dc) balance (for example, there should architecture includes hardware accelerators for
not be more than four consecutive high bits or the most demanding primitives used in pro-
four low bits). Beyond that, system software tocol construction and allows these primitives
18 IEEE MICROPreamble Start symbol
Transmission transmission
MAC delay Transmitting individual bits
Bit modulations
Radio samples
Slow, periodic sampling Receiving individual bits
Reception
Activity monitoring Precise synchronization
Start symbol search Start symbol detection
Figure 5. Anatomy of packet reception and transmission. For reception, slow sampling detects arrival of a 10-kilobits-per-
second (Kbps) start signal. The receiver must determine the packet’s precise timing to synchronize for the 50-Kbps data pay-
load. Data sample timing for the entire packet is based on the initial synchronization. For transmission, after a short random
delay, the preamble, then a start symbol, and then the data are sent.
to be composed in software, making rich small fraction of the processor, whereas pro-
interfaces available. In general, these primi- grammed I/O peaks at 20 Kbps using the
tives could be implemented in board-level entire processor. Other microcontrollers with
logic, field-programmable gate arrays, appli- a double-buffered SPI transmit port can
cation-specific integrated circuits, or inte- achieve the full 115 Kbps of the radio. The
grated logic, depending on the byte streaming performance of more sophisti-
implementation technology.7 For the Mica cated versions of this accelerator would
platform, we built the critical hardware accel- approach conventional direct memory access
erators using conventional serializers in channel performance, yet with precise control
unconventional ways. While they provide a over timing.
significant efficiency boost, they represent just The Mica node also incorporates a syn-
the beginning of the possibilities we can chronization accelerator that captures the
include as we progress toward custom devices. exact timing of an incoming packet to with-
The first accelerator provides a simple shared in one clock cycle (250 nanoseconds) at the
memory buffer between the bit-parallel data start of packet reception. Shared memory
path and the bit-serial radio channel. This lets stores this packet time stamp, and the data
the processor deal with communication data path can read it. This hardware accelerator is
in efficient chunks and overlap its data manip- critical to our design because at high bit rates,
ulation with the low-level spooling of bits to or determining transmission timing is extreme-
from the radio, at defined intervals. The mech- ly difficult. The synchronization accelerator
anism doesn’t dictate channel coding or sig- forwards this time stamp to the buffering
naling and can be bypassed to let the accelerator so that it can perform automatic
microcontroller directly interact with the radio channel sampling at the center of each bit
by using programmed I/O. This option meets transmission. The timing information is not
real-time requirements when necessary, for buried in the radio interface; it can also be
example, during start symbol detection, but delivered to application software for use in
doesn’t force real-time processing of all trans- higher-level synchronization operations.
fer options. Software can deal with data in 8- We built both of these hardware accelera-
bit chunks when its optimal, but the data can tors out of standard microcontroller func-
also be directly accessed bit-by-bit as it arrives. tional units. SPI is a synchronous chip-to-chip
This accelerator lets the Atmel controller drive interconnect with a serial data line and a sep-
the radio at 50 kilobits-per-second using a arate clock signal that an external SPI master
NOVEMBER–DECEMBER 2002 19MICA
will provide. We drive the asynchronous radio several sources and communicate results
by combining the functionality of input cap- rapidly to engage some response. This wake
ture registers, timer-controlled output pins, up would normally be realized above the mes-
and the SPI communication hardware. The saging layer, passing packets to propagate the
input capture register automatically captures event notification to initiate aggregate pro-
a timing pulse contained in the packet. This cessing. However, we can exploit the flexible
value is used to configure the timing register interface to the radio to implement an
that controls an output pin. One control ultralow-power network wake-up signal.
option lets hardware automatically toggle the More specifically, this flexibility lowers system
output pin each time the counter expires; this cost for wake-up checking.
output pin becomes a clocking signal that For any RF-based wake-up protocol, each
times each arriving bit. Finally, SPI hardware node must periodically turn on its radio and
captures the value of the radio signal each time check for a wake-up signal. Consider a pro-
the counter triggers the clock line. We accom- tocol in which a node checks for a signal every
plish this by connecting the counter- 4 seconds. Since the protocol assumes that
controlled output pin to the synchronous the wake-up alarm is rare, the source can
clock line of the SPI port. On the Mica node, transmit a signal continuously for a period of
we combine the radio’s incoming receive data time after the event. A packet interface uses
with an artificially generated clock signal to the detection of a start symbol pattern to dif-
create an SPI master. The clock signal is the ferentiate data from noise on the channel.
output of the timing register fed back into the Thus, to implement the wake-up check over
controller’s SPI port. This results in the SPI a packet-based radio interface, a node must
port automatically latching and buffering the turn on its radio for at least the duration of
incoming transmission with precise timing— two packets. We typically use 30-byte pack-
as long as the internal timing register is con- ets with a dc-balanced, single-error correc-
figured correctly at the start of reception. tion, dual-error detection encoding that
results in 540 bits per packet. Thus, at 10
Cross-layer optimizations Kbps, the check time would be 108 ms, or
Many deeply embedded applications spend 21 ms at 50 Kbps; just checking for wake up
the vast majority of the time in a very low yields a 2.7 percent active duty cycle of the
power state, slowly draining their available device, or 0.5 percent at the faster rate.
energy supply by processing sensor readings to Although reducing the responsiveness to the
confirm that no particular action need be alarm or modifying the packet interface for
taken. Infrequently, these applications com- an early rejection on the check could reduce
municate monitoring results, and rarely, por- this cost, we perform a more radical cross-
tions of the network become extremely active layer optimization.
upon detection of an important event. Perfor- Instead of interacting with the radio over a
mance improvements in an application’s active high-level packet interface, our low-power
work, such as processing and messaging, sleep mode interacts directly with the analog
enhance the application’s overall effectiveness baseband. The wake-up signal is nothing
and let it return to a low-power state more more than a long RF pulse. A node checks for
quickly. However, the larger impact of the rich- the wake-up signal by sampling the energy on
ly integrated approach to wireless design is that the channel and can determine whether the
enables optimization of the rest of the appli- wake-up signal is present in less than 50 µs.
cation. Often these optimizations reach across With a 4-second check interval, this 2,000-
traditional layers of abstraction, using low-level fold speedup in the check time results in a
information to achieve a high-level goal. 0.00125 percent radio duty cycle. To put this
in perspective, the same energy consumed by
RF wake up packet-based checks in a week could last 38
Upon detection of an important event, a years using low-level wake up. We have used
node will typically awaken, or start up, a sub- this ultralow duty cycle implementation to
stantial portion of the network. The network consistently wake up multihop sensor net-
will collect, transport, and process data from works of more than 800 nodes.
20 IEEE MICROTime synchronization mentation is only possible because of the
Many sensor applications require time-cor- shared access to a high-accuracy system timer
related sensor readings or multimode coordi- between the bottom of the network stack and
nation, and therefore need an underlying the top of the application. Partitioned wireless
time-synchronization mechanism. For exam- devices—such as Bluetooth chipsets—hide the
ple, if a sensor network were used to capture exact timing information from applications.
the propagation of earthquake vibrations (Generally the receive packet path has less jit-
through a building, sensor readings across the ter than the transmit path, so an alternative
network would need to be synchronized to approach uses the broadcast nature of the radio
within hundreds of microseconds. The accu- channel to synchronize multiple receivers, even
racy of distributed synchronization protocols if they are poorly synchronized with the trans-
is bounded by the unpredictable jitter on com- mitter.9) Mica’s time synchronization primi-
munication times. Aside from variations in the tives provide highly accurate pairwise
actual network latency, the variation in delay synchronization between any two nodes. This
going through sophisticated protocol proces- primitive can aid construction of network-
sors can be hundreds of milliseconds due to wide time synchronization to within tens of
buffering, MAC protocols, and backoff. Unlike microseconds.9
wide-area time synchronization protocols—
such as the network time protocol8—we can Determining device location
determine all sources of communication delay. Many applications need to associate loca-
Our use of rich interfaces lets us expose the tion information with the data obtained from
sources of delay to the application, reducing sensor nodes. Using the radio as both a sensor
the unknown jitter. Additionally, by exploiting and a high-fidelity time synchronization
shared system timers, we can assign precise time mechanism can facilitate localization. RF sig-
stamps to incoming and outgoing packets nal strength falls off with distance, so sam-
beneath the sources of variation. pling the strength of the baseband signal,
We designed the Mica platform to use an combined with information on the transmit
internal 16-bit high-frequency counter to act power level, provides an indication of dis-
as the lower 16 bits of a 32-bit continually tance. The distance estimates can aid an elab-
running system clock. This highly accurate orate form of triangulation to determine
system clock is directly linked to the syn- device position.5,10 Variations in strength read-
chronization accelerator used to capture the ings due to multipath effects, interference, and
exact timing of an incoming packet. To syn- transmitter/receiver tuning make this
chronize a pair of nodes, a packet can be time approach more effective for determining prox-
stamped with a sender’s clock value as it is imity than absolute position.
transmitted and after all MAC delays have Alternatively, obtaining accurate time
occurred (prior to transmission, a node might stamps can help determine the propagation
have to wait for the radio channel to be clear). delay of acoustic pulses as a basis for localiza-
The receiver’s synchronization accelerator can tion.11 Some sensor boards contain an elec-
then tag the packet with the receiver’s clock tronic sounder and a microphone. These
value. The application can use the difference boards transmit a radio packet in unison with
between the two time stamps to determine an acoustic pulse. The RF packet causes the
how to adjust its system clock. receiver to start a counter to measure the delay
Our implementation synchronizes a pair of until the acoustic pulse arrives, providing cal-
nodes to within 2 µs. We can directly attribute ibration parameters to map measured delay to
the skew of +/− 2 µs to several sources of jitter. distance. This mapping compensates for
When sending, there is a jitter of +/− 1µs in delays in the acoustic transmission/receive
the transmission propagation due to the inter- path. As with the radio, a rich interface
nal circuit dynamics of the radio. Hardware reduces the sources of unknown jitter.
then captures the arriving pulse with an accu-
racy of +/− .25 µs. Finally, to synchronize the Application evaluation
clock based on the captured value introduces The ultimate goal of the Mica node is
an additional +/− .625 µs of jitter. This imple- enabling novel applications that shape the
NOVEMBER–DECEMBER 2002 21MICA
Table 2. Node energy costs in a persistent data monitoring application that reports every
5 minutes and has a maximum of five children. The table shows results for basic and
optimized implementations.
Implementation Base Optimized Improvement factor
Data communication (mJ/day) 2,262 452 5
Children’s transmission waiting time (mJ/day) 669 33 20
Alarm check (mJ/day) 54,237 25 2,160
Sensing (mJ/day) 17 17 1
Total active (mJ/day) 57,187 528 108
Sleep (mJ/day) 5,038 5,182 1
Total (mJ/day) 62,225 5,711 11
role of deeply embedded networks. Not only environmental change, any node can send an
do the application requirements differ dras- emergency notification to its parent at any
tically from those of traditional wireless sce- time. The parent checks for emergency mes-
narios, they differ dramatically from one sages every 4 seconds. Table 2 summarizes the
another. In our exploration of these new sce- theoretical impact of the Mica optimizations
narios, two distinct classes of applications for a base case without the hardware acceler-
have emerged. The first is categorized by a ators and a case with the accelerators and the
low duty-cycle, low data-rate, long latency, cross-layer optimizations that they enable.
static topology and a long expected lifetime. Mica’s support of application-specific proto-
For these networks, lifetime is the main eval- cols results in a 10× increase in overall appli-
uation criterion. A second class of applica- cation performance.
tions is that of highly dynamic The energy cost of data transmission assumes
sense-and-control networks with higher data that the worst-case node is responsible for five
rates, latency limits, and highly mobile nodes. children. The node must receive a summary
Instead of passively monitoring a relatively from each of the children, combine them, and
static environment, these networks attempt transmit a new summary to its parent. The pro-
to control the environment in real time. This cessing time is small compared with the time
class places strict latency and throughput needed to transmit or receive a message. The
requirements on the network, which act as hardware accelerators reduce—proportionally
the main measure of system performance. to the increase in bandwidth—the energy con-
A common, low duty cycle scenario for sen- sumption of this portion of the application.
sor networks is the continual monitoring of Since communication is infrequent and the
an environmental space for low-frequency radio consumes energy whenever it’s powered
environmental changes combined with detec- on—whether it’s receiving data or not—nodes
tion of important events. These scenarios leave their radios powered off whenever pos-
include heating, ventilation, and air condi- sible. In a rendezvous protocol, nodes agree to
tioning monitoring of large buildings or cli- communicate at a future time and turn off
matic monitoring of outdoor habitats. The their radios until that time. In these protocols,
Mica optimization opportunities come synchronization precision translates into lower
together to determine the application’s capa- power consumption. If a scheduled applica-
bility and lifetime at a given energy budget. tion-level rendezvous is only accurate to
Consider a scenario where the network forms approximately100 ms, then the receiver must
itself into a tree and each node samples envi- wake up 100 ms early to ensure that it’s not
ronmental data every 4 seconds, aggregates a late; this could result in the receiver’s waiting
statistical summary over 5 minute’s worth of 200 ms before the transmission actually begins.
readings, and transmits the summary to its For the short transmissions common in sen-
parent node. Each parent combines the read- sor networks, this results in a four-to-five-times
ings from its children and sends a single sum- increase in cost. The use of bit-level time syn-
mary to its parent. In the event of a drastic chronization reduces the energy consumed
22 IEEE MICROwaiting for the rendezvous by a factor of 20. References
The relatively high frequency of the wake- 1. M. Stemm et al., “Reducing Power Con-
up check makes it the single largest consumer sumption of Network Interfaces in Hand-
of energy in the base design. Exploiting the Held Devices,” IEICE Trans. Comm., vol.
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cost by a factor of 2,000. Taken together, the 2. TC2000 Single Chip Bluetooth Solution,
three optimizations (RF wake up, time syn- Zeevo, Santa Clara, Calif., 2001; http://www.
chronization, and high-speed communica- zeevo.com/pdf_files/tc2k_public.pdf.
tion) reduce energy consumption of the active 3. I 2C-Bus Specification v2.1, Philips Semicon-
part of the application by two orders of mag- ductor, Eindhoven, Netherlands, 2000; http://
nitude. Table 2 shows the impact of each indi- www.semiconductors.philips.com/acrobat/
vidual optimization as well as the overall various/I2C_BUS_SPECIFICATION_3.pdf.
impact on system lifetime for a theoretical 4. J. Hill et al., “System Architecture Directions
deployment. In the base case, the power drain for Networked Sensors,” Proc. 9th Int’l
in sleep state was a reasonable 10 percent of Conf. Architectural Support for Programming
the overall budget, but it dominates the opti- Languages and Operating Systems (ASP-
mized application. When looking at the appli- LOS), ACM Press, New York, 2000.
cation as a whole, battery life is improved by 5. P. Bahl and V. Padmanabhan, “RADAR: An
a factor of 10, resulting in an expected life- In-Building RF-Based User Location and
time of 10 years for a pair of AA batteries (that Tracking System,” Proc. Ann. Joint Conf.
is, 9 years for the base and 1 year for the opti- IEEE Computer and Comm. Soc. (IEEE Info-
mized implementation). Fortunately, further com), vol. 2, 2000, IEEE Press, Piscataway,
integration of the design will further reduce N.J., pp. 775-784.
the standby power drain. 6. W. Ye, J. Heidemann, and D. Estrin, “An
The application must control the duty cycle Energy-Efficient MAC Protocol for Wireless
and rendezvous schedule of the protocol, Sensor Networks,” Proc. Ann. Joint Conf.
because these elements vary greatly depending IEEE Computer and Comm. Soc. (IEEE Info-
on the application scenario. For example, tem- com), IEEE Press, Piscataway, N.J., 2002.
perature sensing might require 1-minute inter- 7. J.L. Da Silva Jr. et al., Design Methodology
vals between reports with only a byte of data for Pico Radio Networks, Berkeley Wireless
collected per node, while network monitoring Research Center, Berkeley, Calif., 2001.
of plant photosynthesis could need more com- 8. D.L. Mills, “Internet Time Synchronization:
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T he exploration of deeply embedded sen-
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nologies in new directions. Many research
1482-1493.
9. J. Elson and D. Estrin, “Time Synchroniza-
tion for Wireless Sensor Networks,” Proc.
groups in the US that are exploring these IPDPS Workshop Parallel and Distributed
directions use the Mica node as a foundation Computing Issues in Wireless Networks and
for their research. A single-chip version of the Mobile Computing, Springer-Verlag, Heidel-
architecture is in development today. It will berg, Germany, 2001.
generalize Mica’s architecture, provide addi- 10. J. Hightower and G. Borriello, “Location Sys-
tional accelerators, and dramatically reduce tems for Ubiquitous Computing,” Computer,
the standby power consumption. MICRO vol. 34, no. 8, 2001, pp. 57-66.
11. N.B. Priyantha, A. Chakraborty, and H. Bal-
Acknowledgments akrishnan, “The Cricket Location-Support
We thank Crossbow (http://www.xbow. System,” Proc. 6th Ann. Int’l Conf. Mobile
com) for manufacturing and distributing the Computing and Networking (MobiCom),
Mica platform, Intel for support during devel- ACM Press, New York, 2000, pp. 32-43.
opment, UC Berkeley’s Smart Dust and Webs
research groups, the TinyOS development Jason L. Hill is currently working toward his
team, Kris Pister, Robert Szewczyk, Alec Woo, PhD in electrical engineering and computer
and Phil Levis. science at UC Berkeley. His research interests
NOVEMBER–DECEMBER 2002 23MICA
include developing hardware and software to ed abstract machine; and data flow systems.
enable the proliferation of wireless sensor net- Culler has a BA from UC Berkeley, and an
works and developing millimeter-scale wire- MS and PhD from the Massachusetts Insti-
less sensor nodes by incorporating tute of Technology. He was awarded the NSF
communication, computation, and storage Presidential Young Investigator in 1990 and
onto a single CMOS chip. Hill has a BS and the Presidential Faculty Fellowship in 1992,
an MS in electrical engineering and comput- and holds three patents.
er science from UC Berkeley.
Direct questions and comments about the
David E. Culler is a professor of computer sci- article to Jason Hill, 467 Soda Hall,
ence at UC Berkeley and founding director of Berkeley, CA 94720-1776; jhill@cs.
Intel Research, Berkeley. His research inter- berkeley.edu.
ests include vast networks of small, embed-
ded wireless devices; parallel computer
architecture; parallel programming languages;
high-performance communication; TinyOS; For further information on this or any other
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