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Wireless sensor networks in autonomic environments

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... on the Great Duck Island (USA Maine. 2002/2003. UCB & Intel & Atlantic Univ. ... energy map of the network to determine routes in a dynamic fashion, according to ... – PowerPoint PPT presentation

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Title: Wireless sensor networks in autonomic environments


1
Wireless sensor networks in autonomic
environments
  • Shuping Liu
  • Networking Lab
  • HUT

2
Agenda
  • What is sensor?
  • What is WSN?
  • Communication topology
  • Why we need it?
  • WSN special characters
  • Some filed interesting
  • A programmable routing for autonomic WSN
  • Data dissemination in autonomic WSN

3
What is sensor?
4
What is WSN?
  • Habitat monitoring on the Great Duck Island
    (USA Maine. 2002/2003. UCB Intel Atlantic
    Univ.)

5
Communication topology
6
Why we need it?
  • Seamless and Ubiquitous communication with the
    real world.
  • Wide usages
  • Military application
  • Environmental application
  • Health application
  • Home application
  • Traffic Surveillance
  • Other commercial applications

7
WSN special characters
  • Person unattended, inaccessible ? autonomic
  • Limited resource power, memory, MPU
  • Topology changes / breaks frequently (war field,
    etc.)
  • High density employed, broadcast communication
    paradigm (normal ad-hoc networks uses
    point-to-point communications)
  • ? Must be self-organized, self-maintaining and
    operate at low duty cycle.

8
Some fields interesting
  • Efficient routing
  • Data dissemination
  • Low power
  • Security
  • Programming the Ensemble (configuration)
  • ? WSN is a new field, especially in autonomic
    environment. I will introduce some work in the
    first two topics in autonomic WSN

9
A programmable routing for autonomic WSN (1/19)
  • The goal of a WSN is to collect, process, and
    forward sensed data to other sensor nodes and/or
    base stations.
  • Therefore, the proper routing algorithm is
    essential to WSN applications, which must be
    lightweight, due to limited available resources.

10
A programmable routing for autonomic WSN (2/19)
  • Several existing routing for WSN
  • GPSR Greedy Perimeter Stateless Routing
  • GEAR Geographical Energy Aware Routing
  • TBF Trajectory Based Routing
  • DD Directed-Diffusion
  • TTDD Two-Tier Data-Dissemination
  • CBM Content-Based Multicast
  • RR Rumor-Routing

11
A programmable routing for autonomic WSN (3/19)
  • These routings have distinct properties,
  • Try to meet the resource-limited requirements
  • Different from traditional routing such as
    OSPF,RIP,BGP
  • (see table 1 for difference in details)
  • Each of them is designed to meet specific goals
    and therefore is not efficient for all
    applications.
  • e.g. DD is more energy-efficient than TTDD
    when the number of sink nodes is large, while
    TTDD is better when the number of sink nodes is
    small
  • There is a need to have a routing for WSN that
    can adapt to different applications and different
    network conditions ? autonomic WSN

12
A programmable routing for autonomic WSN (4/19)
  • Table 1. Comparison of routing services in WSN
    and Traditional Networks

13
A programmable routing for autonomic WSN (5/19)
  • Currently, it is very difficult, if not
    impossible, to change a routing service in a
    large WSN because the service is statically
    pre-configured into each node, which is often
    unattended.
  • Yu He et. al. in USC propose a programmable
    routing for autonomic WSN.
  • Their work includes a universal routing service
    and an autonomic deployment service.

14
A programmable routing for autonomic WSN (6/19)
  • The universal routing service allows the
    introduction of different services through its
    tunable parameters and programmable components.
  • The deployment service completes the
    configuration of the universal routing service
    throughout a WSN in an autonomic and
    energy-efficient way.
  • Through this deployment service, a
    self-configuration ability is realized for sensor
    routing service.
  • With the changeable parameters and programmable
    components of the universal routing service, the
    self-optimizing as well as other autonomic
    abilities can be explored.

15
A programmable routing for autonomic WSN (7/19)
  • Sensor node architecture with programmable
    routing

16
A programmable routing for autonomic WSN (8/19)
  • Table 2. shows the data-forwarding and
    state-collecting functions of the existing
    routing is covered by the programmable structure

17
A programmable routing for autonomic WSN (9/19)
  • The suggested architecture is proposed to cover
    all existing routing services and to introduce
    new services for WSN.
  • The state information is a list of neighbor
    entries, each of which consists of four parts,
  • Neighbor description (id, location,
    direction, distance, energy reading, etc.)
  • Neighbor interest (type, rate, duration,
    etc.)
  • Neighbor data availability (type, duration,
    etc.)
  • Neighbors latest data copy (data, timestamp,
    etc.)
  • ? the above state involves only local
    information and thus is scalable

18
A programmable routing for autonomic WSN (10/19)
  • Different packets are used to collect each part
    of the state information, (state collecting)
  • Neighbor description hello / announcement /
    query packets
  • Neighbor interest query packets
  • Neighbor data availability announcement /
    data packets
  • Neighbor latest data copy data packets

19
A programmable routing for autonomic WSN (11/19)
  • The deployment service receives deployment
    packets that contain parameters or modules of the
    programmable routing services and deploy services
    according to packet content.
  • There are three levels of deployment,
  • (1) the deployment service only changes
    parameters to the state-collecting and/or
    data-forwarding modules. (least bandwidth
    requirement ? relatively frequently)
  • (2) either of the two modules is replaced.
    (middle case)
  • (3) the entire routing service is changed.
  • (most overhead ? only occasionally)

20
A programmable routing for autonomic WSN (12/19)
  • Note that this deployment service allows
    different routing services to reside in different
    parts of WSN. For example, GPSR service and RR
    (Rumor-Routing) service can be deployed in
    heterogeneous parts of a WSN.

21
A programmable routing for autonomic WSN (13/19)
  • Now let us consider a case with complex routing
    service, then we will deploy a large code.
  • Transferring the large routing code can be very
    expensive in WSN where energy is a very scarce
    resource.
  • A. Boulis et. al. proposed a separate running
    environment for deployment service. But it is
    computation inefficiency.
  • A deployment approach for routing services should
    be both energy-efficient and computation-efficient
    .

22
A programmable routing for autonomic WSN (14/19)
  • The approach proposed by Yu He. et. al. is to
    move a part of routing service code into WSN,
    which contains common routing services operations
    and is designed as a shared library, before
    deploying routing service modules.
  • With shared library, the written routing modules
    have small code size while keeping the
    computation efficiency.

23
A programmable routing for autonomic WSN (15/19)
  • A sample node architecture with shared library

24
A programmable routing for autonomic WSN (16/19)
  • The deployment discussed above assumes that all
    nodes in a network can be reached at one time.
  • But this is generally not the case for WSN
    because,
  • Sensor node is prone to fail due to running
    out of energy
  • Communication failure due to lossy channel or
    obstacles
  • Sensor node sleep periodically or dynamically
    for some time due to energy-saving mechanisms
  • ? inconsistency among nodes for deployed
    services

25
A programmable routing for autonomic WSN (17/19)
  • Yu He et. al. proposed a synchronization protocol
    that enables a sensor node to make itself
    consistent with its neighbors in an
    energy-efficient way.
  • Each node runs this protocol after waking up from
    sleeping or after a period.
  • Each node maintains a version number for each
    deployed component (a parameter or a module).

26
A programmable routing for autonomic WSN (18/19)
  • A broadcasts an initial request among its
    neighbors
  • ? each neighbors Ni with greater version
    number starts a timer
  • ?after timeout, the neighbor sends an initial
    reply to A
  • ?A also starts a timer after sending initial
    request
  • ?A sends formal request to the node with
    higher version number
  • ? reply with formal reply
  • ? complete synchronization

27
A programmable routing for autonomic WSN (19/19)
  • Deployment synchronization from neighbors

28
Data dissemination in autonomic WSN (1/5)
  • In WSNs, data communication, from the point of
    view of the communication entities, can be
    divided into three cases,
  • From sensor to a monitoring node
  • Among neighboring sensors
  • From a monitoring node to sensors

29
Data dissemination in autonomic WSN (2/5)
  • Data communication schemes in WSNs

30
Data dissemination in autonomic WSN (3/5)
  • Reliable data dissemination is crucial to WSN
    since a monitoring node has to perform some
    specific activities, such as
  • Change the operational mode of part or entire
    WSN
  • Broadcast a new interest to the network
  • Activate / deactivate one or more sensors
  • Send queries to the network

31
Data dissemination in autonomic WSN (4/5)
  • Max do Val Machado et. al. proposed a new data
    dissemination algorithm, TEDD (Trajectory and
    Energy-based Data Dissemination).
  • The key idea is to combine concepts presented in
    TBF (Trajectory-Based Forwarding) with the
    information provided by the energy map of the
    network to determine routes in a dynamic fashion,
    according to the energy level of the sensor nodes.

32
Data dissemination in autonomic WSN (5/5)
  • Simulation result revealed that the energy spent
    with the data dissemination activity can be
    concentrated on nodes with high-energy reserves,
    whereas low-energy node can use their energy only
    to perform sensing activity or to receive
    information addressed to them.

33
Thanks!Any comments and questions?
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