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Week 3: Wireless Sensor Networks WSNs

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Title: Week 3: Wireless Sensor Networks WSNs


1
Week 3Wireless Sensor Networks (WSNs)
  • ???
  • lyyu_at_cs.ecnu.edu.cn

2
Outline
  • Introduction to WSN
  • Research directions
  • A WSN for structural monitoring
  • Data dissemination
  • Directed diffusion
  • TTDD
  • An energy-efficient MAC for WSN
  • System architecture directions

3
Introduction to WSN
  • A typical WSN

4
Introduction to WSN
  • Main features
  • is composed of a large number of low-cost,
    low-power, multifunctional sensor nodes
  • sensor nodes communicate untethered in short
    distances
  • sensor network protocols and algorithms must
    possess self-organizing capabilities
  • only transmit the required and partially
    processed data from nodes to the sink
  • the topology changes very frequently

Dont send all raw data
5
Introduction to WSN
  • Main applications
  • Military applications
  • Environmental applications
  • Health applications
  • Home applications
  • Transportation applications

6
Introduction to WSN
  • WSN vs. Mobile Ad Hoc Networks
  • The number of sensor nodes in a WSN can be
    several orders of magnitude higher than the nodes
    in an MANET
  • Sensor nodes are densely deployed
  • Sensor nodes are prone to failures
  • The topology of a WSN changes very frequently

7
Introduction to WSN
  • WSN vs. Mobile Ad Hoc Networks (cont.)
  • Sensor nodes mainly use broadcast communication
    paradigm whereas most MANETs are based on
    point-to-point communications
  • Sensor nodes are limited in power, computational
    capacities, and memory
  • Sensor nodes may not have global ID because of
    the large amount of overhead and large number of
    sensors

One reason why it is challenging and attractive.
8
Introduction to WSN
Quarter Dollar
  • Sensor nodes

Crossbow MICA2DOT?? Size(mm) 25 x 6 Price 105
Crossbow MICAz?? (http//www.xbow.com/) Size(mm)
58 x 32 x 7 Price 125
9
Introduction to WSN
  • Typical components of a sensor node

10
Outline
  • Introduction to WSN
  • Research directions
  • Core Challenges
  • Research Directions
  • A WSN for structural monitoring
  • Data dissemination
  • An energy-efficient MAC for WSN
  • System architecture directions

11
Research Directions
  • Core Challenges
  • Energy Efficient
  • Energy is scarce in WSN.
  • This requirement pervades all aspects of the
    system's design, and drives most of the other
    requirements.
  • Data reduction is key to the energy efficiency of
    the system.
  • A perfect system will reduce as much data as
    possible as early as possible.

12
Research Directions
  • Core Challenges
  • Dynamics
  • Reasons
  • Nodes failure run out of energy / overheat in
    sun / be carried away by wind / crash due to
    software bugs / be eaten by a wild boar
  • Quality of RF communication
  • Result
  • Self-configuring
  • Adaptive

13
Research Directions
  • Research Directions
  • Tiered architectures
  • Routing and in-network processing
  • Automatic localization and time synchronization
  • Storage, search and retrieval
  • Actuation
  • Simulation, monitoring, and debugging
  • Security and Privacy

14
Research Directions
Memory Cache
  • Tiered architectures
  • Numerous, small, cheap, disposable nodes
  • Lower price, better energy efficiency
  • Few, larger, faster, and more expensive hardware
  • More capable, more durable

Heterogenous Wireless Sensor Networks
15
Research Directions
  • Routing and in-network processing
  • Routing is a popular topic in multiple hops
    networks
  • In Internet, routing is to find a way to
    transport packets to a particular endpoint
  • In a sensor network, efficiency demands that we
    do as much in-network processing (e.g., data
    reduction) as possible
  • Aggregating similar data, filtering redundant
    information, and so forth
  • Depend on the application

16
Research Directions
  • Automatic localization and time synchronization
  • Some of the most powerful benefits of a
    distributed network are due to the integration of
    information gleaned from multiple sensors into a
    larger world-view not detectable by any single
    sensor alone.

17
Research Directions
  • Automatic localization and time synchronization
  • Each sensor can know whether it is within the
    sensed phenomenon or not.
  • If the sensor positions are known, integration of
    information from the entire field allows the
    network to deduce the size and shape of the
    target, even though it has no size or shape
    sensors.

18
Research Directions
  • Automatic localization and time synchronization
  • Nodes require the capability of localizing
    themselves after they have been deployed
  • Time synchronization is also a crucial service
    necessary to combine the observations of multiple
    sensors with each other

19
Research Directions
  • Automatic localization and time synchronization
  • GPS
  • Provide nodes with both their position and a
    global clock
  • Too expensive, not be practical

20
Research Directions
  • Storage, search and retrieval
  • Energy, bandwidth, storage, memory, processing
    constrain on sensor nodes
  • The traditional database approach is not suitable
    for WSN
  • In-network processing

21
Research Directions
  • Actuation
  • In many cases, a sensor network is an entirely
    passive system
  • Actuation can dramatically extend the
    capabilities of a network in two ways
  • can enhance the sensing task, by pointing
    cameras, aiming antennae, or repositioning
    sensors
  • can affect the environment - opening valves,
    emitting sounds, or strengthening beams

22
Research Directions
  • Actuation

23
Research Directions
  • Simulation, monitoring, and debugging
  • In WSN, simulation and debugging environments
    are particularly important
  • e.g. how can we be sure that the final,
    high-level sensing result delivered by the system
    is an accurate reflection of the state of the
    environment?
  • Several example TOSSIM, EmStar and sensor
    network extensions to GloMoSim and ns-2

24
Research Directions
  • Security and Privacy
  • The physical security of the nodes making up the
    network can not be assured
  • The limited resources on the smallest sensor
    nodes also can pose challenges
  • Sensor networking, similarly, is a technology
    that can be used to enrich and improve our lives,
    or turned into an invasive tool

25
Outline
  • Introduction to WSN
  • Research directions
  • A WSN for structural monitoring
  • Introduction
  • Three challenges
  • Data dissemination
  • An energy-efficient MAC for WSN
  • System architecture directions

26
A WSN for Structural Monitoring
  • Introduction
  • Structural health monitoring systems seek to
    detect and localize damage in buildings, bridges,
    ships, and aircraft
  • Currently, structural engineers use wired or
    single-hop wireless data acquisition systems to
    acquire such data sets

27
A WSN for Structural Monitoring
  • Introduction
  • These systems consist of a device that collects
    and stores vibration measurements from a small
    number of sensors
  • power and wiring constraints
  • impose significant setup delays
  • limit the number and location of sensors

Wireless sensor networks can help address these
issues.
28
A WSN for Structural Monitoring
  • Introduction
  • In this paper, authors describe the design of
    Wisden, a wireless sensor network system for
    structural-response data acquisition.
  • Wisden continuously collects structural response
    data from a multi-hop network of sensor nodes,
    and displays and stores the data at a base
    station.

29
A WSN for Structural Monitoring
  • Introduction
  • Wisden overview
  • A typical Wisden deployment will consist of
    several tens of nodes placed at different
    locations on a large structure.
  • Each node has an attached accelerometer that is
    capable of sensing up to three channels of
    vibration data, with a configurable sampling rate.

30
A WSN for Structural Monitoring
  • Introduction
  • Wisden overview
  • A base station provides the functionality
    equivalent to a data logger or acquisition
    unitthe ability to store samples and to provide
    near real-time display of samples.
  • Nodes self-configure to form a tree topology,
    then send their vibration data to the base
    station, potentially over multiple-hops.

31
A WSN for Structural Monitoring
  • Introduction
  • Structural response data is generated at higher
    data rates than most sensing applications
    (typically, structures are sampled upwards of 100
    Hz).
  • This application requires loss intolerant data
    transmission, and time synchronization of
    readings from different sensors.

32
A WSN for Structural Monitoring
  • Introduction
  • Three challenges in Wisden
  • Reliable Data Transport
  • Compression
  • Data Synchronization

33
A WSN for Structural Monitoring
  • Reliable Data Transport
  • In Wisden, nodes self-organize themselves into a
    routing tree rooted at the base station.
  • Wisden uses both hop-by-hop and end-to-end
    recovery.

34
A WSN for Structural Monitoring
  • Reliable Data Transport
  • Hop-by-hop NACK-based reliability scheme
  • Each source stores generated vibration data in
    its EEPROM, then transmits the data to its
    parent.
  • Parents keep track of sequence numbers of packets
    that they receive, on a per source basis.
  • A gap in the sequence number of sent packets
    indicates packet loss.
  • Each node maintains a list of missing packets.

35
A WSN for Structural Monitoring
  • Reliable Data Transport
  • Hop-by-hop NACK-based reliability scheme
  • When a loss is detected, a tuple containing a
    source ID and sequence number of the lost packet
    is inserted into this list.
  • Entries in the missing packets list are
    piggybacked in outgoing transmissions, and
    children infer losses by overhearing this
    transmission.
  • Nodes keep a small cache of recently transmitted
    packets, from which a child can repair losses
    reported by its parent.

36
A WSN for Structural Monitoring
  • Reliable Data Transport
  • Discussion when does hop-by-hop NACK-based
    reliability not work well?
  • First, heavy packet losses can lead to large
    missing packet lists that might exceed the memory
    of the motes.
  • More fundamentally, a topology change could cause
    loss of missing packet list information. For
    example, when a node selects a new parent.

37
A WSN for Structural Monitoring
  • Reliable Data Transport
  • End-to-end recovery scheme
  • The end-to-end recovery scheme is essentially
    implemented in much the same way as the
    hop-by-hop scheme.
  • It leverages the fact that the base station has
    significantly more memory and can keep track of
    all missing packets.
  • The base station attempts hop-by-hop recovery of
    a missing packet.

38
A WSN for Structural Monitoring
  • Reliable Data Transport
  • Experimental Evaluation
  • Deployed 25 mica2 motes on three floors of a
    medium-sized office building
  • 15 of those motes were programmed to generate
    artificial traffic
  • 10 motes only forwarded traffic, and were placed
    to ensure the multihop topology
  • 10 nodes dynamically selected different parents
    to trigger the end-to-end recovery

39
A WSN for Structural Monitoring
  • Achieved 100 reliability in all experiments.
  • When packet injecting rate is 2 packet/second,
    network essentially collapses and very few of the
    packets are received
  • Reliable Data Transport

40
A WSN for Structural Monitoring
  • EEPROM ? sources retransmitting
  • RAM ? intermediate nodes retransmitting
  • Reliable Data Transport

41
A WSN for Structural Monitoring
  • Compression
  • Motivation
  • Even if each of 20 nodes generated only 10
    minutes worth of 3-channel vibration data, it
    would take almost an hour transmit the data to
    the base station assuming a nominal radio
    bandwidth of 2 KBps.

42
A WSN for Structural Monitoring
  • Compression
  • Approaches
  • Event detection only transmit samples that
    exceed a certain threshold
  • Progressive storage and transmission stores
    vibration data locally and transmits a lossy
    version (using wavelet compression) of the data
    to the base station

43
A WSN for Structural Monitoring
  • Compression
  • Event detection
  • If samples within a small window have a low value
    and are comparable in value, the structure is
    quiescent
  • Such quiescent periods are compressed using
    run-length encoding
  • Samples in non-quiescent periods are transmitted
    without compression

Run Length Encoding consists of the process of
searching for repeated runs of a single symbol in
an input stream, and replacing them by a single
instance of the symbol and a run count.
44
A WSN for Structural Monitoring
  • Compression
  • Event detection
  • Discussion does event detection have any
    limitation?
  • The number of instrumentation locations is
    constrained by the rate at which a structure is
    expected to vibrate, especially for forced
    vibrations experiment
  • This approach does not reduce the user-perceived
    latency of data acquisition. Due to the global
    nature of vibration events, vibration data is
    usually generated from all node simultaneously.

45
A WSN for Structural Monitoring
  • Compression
  • Progressive Storage and Transmission
  • In order to reduce the latency of data
    acquisition
  • This approach uses local storage on the motes as
    a in-network cache for raw data and transmits
    low-resolution compressed summaries of data in
    near real-time.
  • The raw data can be collected from the
    distributed caches when required.

46
A WSN for Structural Monitoring
  • Data Synchronization
  • Samples need to be accurately timestamped in
    order to correlate readings from different
    sensors.
  • In order to distinguish responses due to
    different events.
  • Wisden uses a light-weight approach in that it
    focuses on timestamping the data consistently at
    the base station, rather than synchronizing
    clocks network-wide.

47
A WSN for Structural Monitoring
  • Data Synchronization
  • In Wisden, each node calculates the amount of
    time spent by a sample at that particular node
    using its local clock.
  • This amount is added to an residence time field
    attached to a packet as the packet leaves the
    node.
  • Thus, the delay from the time of generation of
    the sample to the time it is received by the base
    station is stored in the packet.
  • This is the time the packet resides in the
    network.
  • The base station can calculate the time of
    generation of the sample by subtracting the
    residence time from its local time.

48
A WSN for Structural Monitoring
  • Data Synchronization
  • Time synchronization example

the residence time at the ith hop node (ms)
the propagation delay for the ith hop (ns)
the residence time from A
when base station received the packet
The sample must be generated at
49
A WSN for Structural Monitoring
  • Conclusion
  • In this paper, the design of a wireless
    structural data acquisition system called Wisden
    is described.
  • Reliable Data Transport
  • Compression
  • Data Synchronization
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