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Title: Sensor Network Applications


1
Sensor Network Applications
2
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Introduction
  • Habitat and environmental monitoring represent
    essential class of sensor network applications by
    placing numerous networked micro-sensors in an
    environment where long-term data collection can
    be achieved
  • The sensor nodes perform filtering and triggering
    functions as well as application-specific or
    sensor-specific data compression algorithms thru
    the integration of local processing and storage
  • The ability to communicate allows nodes to
    cooperate in performing tasks such as statistical
    sampling, data aggregation, and system health and
    status monitoring
  • Increased power efficiency assists in resolving
    fundamental design tradeoffs, e.g., between
    sampling rates and battery lifetimes

3
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Introduction
  • The sensor nodes can be reprogrammed or retasked
    after deployment in the field by the networking
    and computing capabilities provided
  • Nodes can adapt their operation over time in
    response to changes in the environment
  • The application context helps to differentiate
    problems with simple and concrete solutions from
    open research areas
  • An effective sensor network architecture and
    general solutions should be developed for the
    domain
  • The impact of sensor networks for habitat and
    environmental monitoring is measured by their
    ability to enable new applications and produce
    new results

4
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Introduction
  • This paper develops a specific habitat monitoring
    application, but yet a representative of the
    domain
  • It presents a collection of requirements,
    constraints and guidelines that serve as a basis
    for general sensor network architecture
  • It describes the core components of the sensor
    network for this domain hardware and sensor
    platforms, the distinct networks involved, their
    interconnection, and the data management
    facilities
  • The design and implementation of the essential
    network services power management,
    communications, re-tasking, and node management
    can be evaluated in this context

5
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Habitat Monitoring
  • Researchers in the Life Sciences are concerned
    about the impacts of human presence in monitoring
    plants and animals in the field conditions
  • It is possible that chronic human disturbance may
    adversely effect results by changing behavioral
    patterns or distributions
  • Disturbance effects are of concern in small
    island situations where it may be physically
    impossible for researchers to avoid some impact
    on an entire population
  • Seabird colonies are extreme sensitive to human
    disturbance
  • Research in Maine Anderson 1995, suggests that
    a 15 minute visit to a cormorant colony can
    result in up to 20 mortality among eggs and
    chicks in a given breeding year. Repeated
    disturbance can lead to the end of the colony

6
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Habitat Monitoring
  • On Kent Island, Nova Scotia, research learned
    that Leachs Storm Petrels are likely to desert
    their nesting burrows in case of disturbance
    during the first two weeks of incubation
  • Sensor networks advances the monitoring methods
    over the traditional invasive ones
  • Sensors can be deployed prior to the breeding
    season or other sensitive period or while plants
    are dormant or the ground is frozen on small
    islets where it would be unsafe or unwise to
    repeatedly attempt field studies
  • Sensor network deployment may be more economical
    method for conducting long-term studies than
    traditional personnel-rich methods
  • A deploy em and leave em strategy of wireless
    sensor usage would decrease the logistical needs
    to initial placement and occasional servicing

7
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Great Duck Island
  • The College of Atlantic (COA) is field testing
    in-situ sensor networks for habitat monitoring
  • Great Duck Island (GDI) is a 237 acre island
    located 15 km south of Mount Desert Island, Maine
  • At GDI, three major questions in monitoring the
    Leachs Storm Petrel Anderson 1995
  • What is the usage pattern of nesting burrows over
    the 24-72 hour cycle when one or both members of
    a breeding pair may alternate incubation duties
    with feeding at sea?
  • What changes can be observed in the burrow and
    surface environmental parameters during the
    course of the approximately 7 month breeding
    season (April-October)?

8
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Great Duck Island
  • What are the differences in the
    micro-environments with and without large numbers
    of nesting petrels?
  • Presence/absence data is obtained through
    occupancy detection and temperature differentials
    between burrows with adult birds and burrows that
    contain eggs, chicks, or are empty
  • Petrels will most likely enter or leave during
    the daytime however, 5-10 minutes during late
    evening and early morning measurements are needed
    to capture the entry and exit timings
  • More general environmental differentials between
    burrow and surface conditions can be captured by
    records every 2-4 hours during the extended
    breeding season whereas, the differences between
    popular and unpopular sites benefit from
    hourly sampling

9
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Great Duck Island Requirements
  • Internet Access
  • The sensor networks at GDI must be accessible via
    the Internet since the ability to support remote
    interactions with in-situ networks is essential
  • Hierarchical Network
  • Habitats of interest are located up to several
    kilometers away. A second tier of wireless
    networking provides connectivity to multiple
    patches of sensor networks deployed at each of
    the areas.
  • Sensor Network Longevity
  • Sensor networks that runs for several month from
    non-rechargeable power sources would be desirable
    since studies at GDI can span multiple field
    seasons

10
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Great Duck Island Requirements
  • Operating off-the grid
  • Every level of the network must operate with
    bounded energy supplies
  • Renewable energy such as solar power may be
    available some locations, disconnected operation
    is a possibility
  • GDI has enough solar power that run the
    application 24x7 with small probabilities of
    service interruptions due to power loss
  • Management at-a-distance
  • Remoteness of the field sites requires the
    ability to monitor and manage sensor networks
    over the Internet. The goal is no on-site
    presence for maintenance and administration
    during the field season, except for installation
    and removal of nodes

11
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Great Duck Island Requirements
  • Inconspicuous operation
  • It should not disrupt the natural processes or
    behaviors under study
  • Removing human presence from the study areas
    would eliminate a source of error and variation
    in data collection and source of disturbance
  • System behavior
  • Sensor networks should present stable,
    predictable, and repeatable behavior at all times
    since unpredictable system is difficult to debug
    and maintain
  • Predictability is essential in developing trust
    in these new technologies for life scientists

12
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Great Duck Island Requirements
  • In-situ interactions
  • Local interactions are required during initial
    development, maintenance and on-site visits
  • PDAs can be useful in accomplishing these tasks
    they may directly query a sensor, adjust
    operational parameters and so on
  • Sensors and sampling
  • The ability to sense light, temperature,
    infrared, relative humidity, and barometric
    pressure are essential set of measurements
  • Additional measurements may include
    acceleration/vibration, weight, chemical vapors,
    gas concentrations, pH, and noise levels

13
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Great Duck Island Requirements
  • Data archiving
  • Sensor readings must be achieved for off-line
    data mining and analysis
  • The reliable offloading of sensor logs to
    databases in the wired, powered infrastructure is
    essential
  • It is desirable to interactively drill-down and
    explore sensors in near real-time complement
    log-based studies. In this mode of operation, the
    timely delivery of sensor data is the key
  • Nodal data summaries and periodic
    health-and-status monitoring also requires timely
    delivery of the data

14
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture
  • A tiered architecture is developed
  • The lowest level consists of the sensor nodes
    that perform general purpose computing and
    networking as well as application-specific
    sensing
  • The sensor nodes may be deployed in dense patches
    and transmit their data through the sensor
    network to the sensor network gateway
  • Gateway is responsible for transmitting sensor
    data from the sensor patch through a local
    transit network to the remote base station that
    provides WAN connectivity and data logging
  • The base station connects to database replicas
    across the internet
  • At last, the data is displayed to researchers
    through a user interface

15
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture

Figure 1 System architecture for habitat
monitoring
16
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture
  • The autonomous sensor nodes are placed in the
    areas of interest where each sensor node collects
    environmental data about its immediate
    surroundings
  • Since these sensors are placed close to the area
    of interest, they can be built using small and
    inexpensive individual sensors high spatial
    resolution can be achieved through dense
    deployment of sensor nodes
  • This architecture offers higher robustness
    compared to traditional approaches which use a
    few high quality sensors with complex signal
    processing
  • The computational module is a programmable unit
    that provides computation, storage and
    bidirectional communication with other nodes

17
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture
  • The computational module interfaces with the
    analog and digital sensors on the sensor module,
    performs basic signal processing and dispatches
    the data according to the needs of the
    application
  • Compared to traditional data logging systems,
    networked sensors offer two main advantages they
    can be re-tasked in the field and they can
    communicate with the rest of the system
  • In-situ re-tasking gives researchers the ability
    to refocus their observations based on the
    analysis of the initial results initially,
    absolute temperature readings are desired, after
    a while, only significant temperature changes
    exceeding a threshold may become more useful

18
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture
  • Individual sensor nodes communicate and
    coordinate with one another
  • These nodes form a multi-hop network by
    forwarding each others messages and if needed,
    the network can perform in-network aggregation
    (e.g., relaying the average temperature across
    the region)
  • Eventually, data from each sensor needs to be
    propagated to the Internet
  • The propagated data may be raw, filtered or
    processed data
  • Since direct wide area connectivity cannot be
    brought to each sensor path due to several
    reasons (e.g., cost of equipment, power,
    disturbance created by the installation of the
    equipment in the environment), wide are
    connectivity is brought to a base station instead

19
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture
  • The base station may communicate with the sensor
    patch using a wireless LAN where each sensor
    patch is equipped with a gateway that can
    communicate with the sensor network and provides
    connectivity to the transit network
  • The transit network may consist of a single hop
    link or series of networked wireless nodes and
    each transit network design has different
    characteristics with respect to expected
    robustness, bandwidth, energy efficiency, cost
    and manageability
  • To provide data to remote end-users, the base
    station includes WAN connectivity and persistent
    data storage for the collection of sensor patches

20
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture
  • It is expected that WAN connection will be
    wireless
  • The architecture needs to address the
    disconnection possibilities
  • Each layer (sensor nodes, gateways, base
    stations) has some persistent storage to protect
    against data loss due to power outage as well as
    data management services
  • At the sensor level, these will be primitive,
    taking the form of data logging
  • The base station may provide relational database
    service while the data management at the gateways
    falls somewhere in between
  • When it comes to data collection, long-latency is
    preferable to data loss
  • Users interact with the sensor network in two ways

21
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • System Architecture
  • Remote users access the replica of the base
    station database
  • This approach assists on integration with data
    analysis and mining tools while masking the
    potential wide area disconnections with the base
    stations
  • On-site users may require direct interaction with
    the network and this can be accomplished with a
    small, PDA-sized device, referred to as gizmo
  • Gizmo allows the user to interactively control
    the network parameters by adjusting the sampling
    rates, power management parameters and other
    network parameters
  • The connectivity between any sensor node and
    gizmo may or may not rely on functioning on
    multi-hop sensor network routing

22
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Sensor Network Node
  • UC Berkeley motes are used as the sensor nodes
  • Mica uses a single channel, 916 MHz radio from RF
    Monolithics to provide bi-directional
    communication at 40 Kbps, an Atmel Atmega 103
    microcontroller running at 4 MHz and 512 KB
    nonvolatile storage
  • A pair of conventional AA batteries and a DC
    boost converter provide the power source
    however, other renewable energy sources can be
    used

23
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Sensor Board
  • The Mica Weather Board provides sensors that
    monitor changing environmental conditions with
    the same functionality as a traditional weather
    station
  • The Mica Weather Board includes temperature,
    photoresistor, barometric pressure, humidity, and
    passive infrared (thermopile) sensors

Table 1 Mica Weather Board
24
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Sensor Board

Figure 2 Mica Hardware Platform The Mica sensor
node (left) with the Mica Weather Board developed
for environmental monitoring applications
25
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Energy Budget
  • Typical habitat monitoring applications need to
    run for nine months
  • The application chooses how to allocate the
    energy budget between sleep modes, sensing, local
    calculations and communications
  • Since different nodes have different functions,
    they also have different power requirements, for
    instance, the nodes near the gateway may need to
    forward all messages from a patch while a node in
    a nest may only need to report its own readings
  • When a set of power limited nodes exhaust their
    power supplies, the network can become
    disconnected and inoperable
  • There is a need to budget the power with respect
    to the energy bottlenecks of the network

26
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Energy Budget
  • The baseline life time of the node is determined
    by the current draw in the sleep state
  • Minimizing power in sleep mode means turning off
    the sensors, the radio and putting the processor
    into a deep sleep mode

Table 2 Power required by various Mica operations
27
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Sensor Deployment
  • A wireless sensor network using Mica motes with
    Mica Weather Board has been deployed in July 2002
  • Environmental protective packaging has been
    designed which minimally obstruct sensing
    functionality

Figure 3 Acrylic enclosure used for deploying
the Mica mote
28
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Patch Gateways
  • Usage of different gateway nodes directly affects
    the underlying available transit network
  • Two designs implemented an 802.11b single hop
    with an embedded Linux system and a single hop
    mote-to-mote network
  • Initially, CerfCube Cerfcube which is a small
    StrongARM-based embedded system to act as a
    sensor patch gateway, is chosen
  • Each gateway is equipped with a CompactFlash
    802.11b adapter
  • Gateway use permanent storage of up to 1GB
  • The mote-to-mote solution consisted of a mote
    connected to the base station and a mote in the
    sensor patch

29
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Patch Gateways
  • The differences between the mote and CerfCube
    include different
  • communication frequency
  • power requirements
  • software components
  • The motes MAC layer does not require
    bi-directional link like 802.11b
  • In addition, the mote sends raw data with a small
    packet header (4 bytes) directly over the radio
    as opposed to overheads imposed by 802.11b and
    TCP/IP connections

30
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Base-station installation
  • For achieve remote access, collection of sensor
    patches is connected to the Internet through a
    wide-area link
  • On GDI, Internet connectivity is accomplished
    through a two-way satellite connection provided
    by Hughes and similar to DirecTV system
  • The satellite system is connected to a laptop
    which coordinates the sensor patches and provides
    a relational database service
  • Database Management System
  • The base station uses Postgres SQL database which
    stores time-stamped readings from the sensors,
    health status of the individual sensors, and
    metadata (e.g., sensor locations)

31
Wireless Sensor Networks for Habitat Monitoring
Mainwaring 2002
  • Implementation Strategies
  • Database Management System
  • The GDI database is replicated every fifteen
    minutes over the wide-area satellite link to
    Postgres database in Berkeley
  • User Interfaces
  • Many user interfaces can be implemented on top of
    the sensor database
  • GIS systems provide a widely used standard for
    analyzing geographical data and most statistics
    and data analysis packages implement interfaces
    to relational databases
  • Number of web interfaces can be implemented to
    provide the ubiquitous interfaces to the habitat
    data

32
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • Introduction
  • Focus is on issues related to dynamic sensor
    networks with mobile nodes and wireless
    communication between them
  • In this system, the sensor nodes collars carried
    by the animals under study wireless ad hoc
    networking techniques are used to swap and store
    data in a peer-to-peer manner and to pass it
    towards a mobile base station that sporadically
    traverses the area to upload data
  • Biology and biocomplexity research has been
    focused on gathering data and observations on a
    range of species to understand their interactions
    and influences on each other
  • For example, how human development into
    wilderness areas affects indigenous species
    there understand the migration patterns of wild
    animals and how they may be affected by changes
    in weather patterns or plant life, by
    introduction of non-native species, and by other
    influences

33
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • Introduction
  • Finding and learning these details require
    long-term position logs and other biometric data
    such as heart rate, body temperature, and
    frequency feeding
  • Current wildlife tracking studies rely on simple
    technology, for example, many studies rely on
    collaring a sample subset of animals with simple
    VHF transmitters
  • Researchers periodically drive through and/or fly
    over an area with a receiver antenna, and listen
    for pings from previously collared animals
  • Once animal is found, its behavior can be
    observed and its observed position can be logged
    however, there are limits to such studies
  • First, data collection is infrequent and can miss
    many interesting events

34
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • Introduction
  • Second, data collection is mostly limited to
    daylight hours, but animal behavior and movements
    in night hours can be different
  • Third, data collection is impossible or very
    limited for secluded species that avoid human
    contact
  • The most elegant trackers commercially available
    use GPS to track position and use satellite
    uploads to transfer data to a base station
  • These systems also suffer from several
    limitations
  • First, at most a log of 3000 position samples can
    be logged and no biometric data
  • Second, since satellite uploads are slow and uses
    high power consumption, they are done
    infrequently this limits how often position
    samples can be gathered without overflowing
    3000-entry log storage

35
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • Introduction
  • Third, downloads of data from the satellite to
    the researchers are both slow and expensive,
    therefore, constraining the amount of data
    collected
  • Finally, these systems operate on batteries
    without recharge when power is drained, the
    system become unusable unless it is retrieved,
    recharged and re-deployed
  • ZebraNet project is building tracking nodes that
    include a low-power miniature GPS system with
    user-programmable CPU, non-volatile storage for
    data logs, and radio transceivers for
    communicating either with other nodes or with a
    base station

36
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • Introduction
  • One of the key principles of ZebraNet is that the
    system should work in arbitrary wilderness
    locations no assumptions are made about the
    presence of of fixed antenna towers or cellular
    phone service
  • The system uses peer-to-peer data swaps to move
    the data around periodic researcher drives bys
    and/or fly-overs can collect logged data from
    several animals despite encountering relatively
    few within range
  • Even though ad hoc sensor networks have been
    heavily studied, not much has been published
    about the characteristics of mobile sensor
    networks with mobile base stations and very few
    studies focus on building real systems

37
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • Introduction
  • This paper has the following unique
    contributions
  • To the best knowledge of authors, this is the
    first study of mobile sensor networks protocols
    in which the base station is also mobile. It is
    presumed that researchers will upload data while
    driving or flying by the region
  • Zebra-tracking is a domain in which the node
    mobility models are unknown which makes it a
    research goal. Understanding how, when and why
    zebras undertake long-term migrations is the most
    essential biological question of this work.
  • ZebraNets data collection has communication
    patterns in which data can be cooperatively
    passed towards a base station
  • Energy tradeoffs are examined in detail using
    real system energy measurements for ZebraNet
    prototype hardware in operation

38
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • Introduction
  • Some of the interesting research questions to be
    explored are
  • How to make the communications protocol both
    effective and power-efficient?
  • To what extent can we rely on ad hoc,
    peer-to-peer transfers in a sparsely-connected
    spatially-huge sensor network?
  • How can we provide comprehensive tracking of a
    collection of animals, even if some of the
    animals are reclusive and rarely are close enough
    to humans to have their data logs updated
    directly?
  • This research work gives quantitative
    explorations of the design decisions behind some
    of these questions

39
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • ZebraNet Design Goals
  • The ZebraNet project is a direct and ongoing
    collaboration between researchers in experimental
    computer systems and in wildlife biology
  • The wildlife biologists have determined the
    trackers overall design goals
  • GPS position samples are taken every three
    minutes
  • Detailed activity logs taken for three minutes
    every hour
  • One year of operation without direct human
    intervention that is, not counting on
    tranquilizing and re-collaring an animal more
    than once per year
  • No fixed base stations, antennas, or cellular
    service
  • A high success rate for eventually delivering all
    logged data is essential while latency is not as
    critical
  • For a zebra collar, a weight limit of 3-5 lbs is
    recommended

40
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • ZebraNet Design Goals
  • Ultimately, this detailed information may include
    several position estimates, temperature
    information, weather data, environmental data,
    and body movements that will serve as signatures
    of behavior however, in this initial system, the
    focus is only on position data
  • Overall, the key goal is to deliver to
    researchers a very high fraction of the data
    collected over the months or years that the
    system is in operation
  • Therefore, ZebraNet must be power-efficient,
    designed with appropriate data log storage, and
    must be rugged to ensure reliability under tough
    environmental conditions

41
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • ZebraNet Problem Statement
  • The biologists design goals need to be translated
    into the engineering task at hand
  • Success rate at delivering position data to the
    researchers data homing rate should approach
    100
  • Weight limits on each node translate almost
    directly to computational energy limits since
    weight of the battery and solar panel takes bulk
    of the total weight of a ZebraNet node
    therefore, collar and protocol design decisions
    must manage the number and size of data
    transmissions required
  • System design choices must be made that limit the
    range of transmissions since the required
    transmitter energy increases dramatically with
    the distance transmitted

42
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • ZebraNet Problem Statement
  • The amount of storage needed to hold position
    logs must be limited if many redundant copies
    are stored and swapped, the storage requirements
    can scale as O(n2)
  • Although the energy cost of storage is small
    compared to that of transmissions, it is still
    necessary to develop storage-efficient design
  • Due to limited transceiver, coverage and a base
    station only sporadically available, ZebraNet
    must forward data through other nodes in
    peer-to-peer manner and store redundant copies of
    position logs in other tracking nodes
  • Some of the key challenges in ZebraNet come from
    the spatial and temporal scale of the system

43
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • ZebraNet Problem Statement
  • In terms of temporal scale, keeping a system
    running autonomously months at a time is
    challenging it requires tremendous design-time
    attention to both hardware and software
    reliability
  • In terms of spatial scale, ZebraNet is also
    aggressive it is the specific intent of the
    system to operate over an area of hundreds or
    thousands of square square kilometers
  • Due to the large distances involved and sparse
    sensor coverage, energy/connectivity tradeoffs
    become key

44
Energy-Efficient Computing for Wildlife Tracking
Design Tradeoffs and Early Experiences with
ZebraNet Juang 2002
  • ZebraNet Problem Statement
  • These challenges mentioned here tackles several
    open problems
  • ZebraNet protocol promises good communication
    behavior on mobile sensors forwarding data
    towards a mobile base station
  • ZebraNet explores design issues for sensors that
    are more coarse-grained than many prior sensor
    proposals. Larger the weight limits and storage
    budgets allow researchers to consider different
    protocols with improved leverage for
    sparsely-connected, physically-widespread sensors

45
References
  • Anderson 1995 J.G.T. Anderson, Pilot survey of
    mid-coast Maine seabird colonies an evaluation
    of techniques, Bangor, ME, 1995. Report to the
    State of Maine Dept. of Inland Fisheries and
    Wildlife.
  • Cerfcube Cerfcube embedded StrongARM system,
    http//www.intrinsys.com/products/cerfcube
  • Juang 2002 P. Juang, H. Oki, Y. Wang, M.
    Martonosi, L-S Peh, and D. Rubenstein,
    Energy-Efficient Computing for Wildlife Tracking
    Design Tradeoffs and Early Experiences with
    ZebraNet, ACM SIGARCH Computer Architecture News,
    vol. 30, no. 5, December 2002 .
  • Mainwaring 2002 A. Mainwaring, J. Polastre, R.
    Szewczyk, D. Culler, and J. Anderson, Wireless
    Sensor Networks for Habitat Monitoring, 1st ACM
    International Workshop on Wireless Sensor
    Networks and Applications (WSNA 2002), Atlanta,
    Georgia, September 28, 2002.
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