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Semantic routing in sensor network

Semantic routing in sensor network

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ENSEIRB - Advanced Project ENSEIRB - Advanced Project Presentation Transcript

  • SRWSN: Semantic Routing on Wireless Sensor Networks
    HUMIDITY
    SRWSN
    TEMPERATURE
    SOUND
    PRESSURE
    LIGHT
    1
    Semantic Routing on Wireless Sensor Networks
  • Introduction
    • Conventional routing requires the destination address to be known.
    • In a scenario where the network is expected to learn its environment, the algorithm has to be flexible.
    • Wireless Sensor Networks.
    2
    Semantic Routing on Wireless Sensor Networks
  • Context
    • Wireless sensor networks cannot afford to have heavy routing tables.
    • The goal is to fulfill a request on a network without knowing its topology.
    3
    SRWSN
    TEMPERATURE?
    I DO!
    Semantic Routing on Wireless Sensor Networks
  • Outline
    4
    Semantic Routing on Wireless Sensor Networks
  • Outline
    5
    Semantic Routing on Wireless Sensor Networks
  • Problem definition
    • Semantic Routing
    • All the metadata associated with a given message can be applied to a semantic reasoning engine in order to forward this data to the most appropriate receivers, over the most appropriate transmission media.
    • A common ontology has to be defined.
    6
    Semantic Routing on Wireless Sensor Networks
  • Problem definition
    • Wireless Sensor Networks
    • Strong energy constraints
    • Communications are 10 times more energy consuming than an internal process.
    • New applications
    • Surveillance
    • Nodes have to act more collaboratively.
    Using semantics to improve the process inside the network.
    7
    Semantic Routing on Wireless Sensor Networks
  • Outline
    8
    Semantic Routing on Wireless Sensor Networks
  • Scenario
    • Supervising a large property while the owners are absent:
    9
    Semantic Routing on Wireless Sensor Networks
  • Specifications
    • Alphabet
    10
    Semantic Routing on Wireless Sensor Networks
  • 11
    Semantic Routing on Wireless Sensor Networks
    Msg Type
    Query Type
    Query Id
    SrcID
    SrcMAC
    DstMAC
    Options
    Specifications
    • Packet Type
    • MsgType : DISCOVERY, NORMAL STATE, ALERT
    • QueryType : REQUEST or ANSWER
    • QueryId: TEMP_VAL, TEMP_ERR, etc...
    • SrcID : id of the query source
    • SrcMAC : source MAC address (of the neighbor sender)
    • DstMAC : destination MAC address (of the neighbor receiver)
    • Options :
    • BLOOM FILTER DISCOVERY
    • VALUE
    • ERROR
    • ALERT_GEN
    • ALERT_TIMESTAMP
    • HOP_COUNT
    NORMAL STATE
    ALERT
  • Specifications
    • Identification Number
    • Distinctly identify a node according to its direction and distance from the sink.
    • ID format:
    Direction MAC Last Byte Hops To Sink
    12
    A B C D
    Semantic Routing on Wireless Sensor Networks
  • Semantic routing tools adaptation
    • BloomTable
    • Based on « peer content »
    • Contains all the Bloom filters of the neighborhood
    • Quickly know its neighbor abilities
    • Payload reduced
    • No three way handshake to discover the abilities
    • Store information in an efficient way
    13
    Semantic Routing on Wireless Sensor Networks
  • Bloom Filters
    • Represent a set of n elements in a compact form
    • Detect the presence of an element
    0
    0
    1
    1
    S
    S0
    1
    0
    S1
    1
    g(si)
    P1
    1
    P1
    1
    0
    h(si)
    P2
    1
    P2
    Sn-1
    0
    0
    Sn
    0
    14
    Semantic Routing on Wireless Sensor Networks
  • Semantic routing tools Adaptation
    • Learning Table
    • Based on the « query history »
    • Mimicking human actions in a social network
    • Process
    • Observe query responses sent to peers
    • Memorize the information (only by listening to traffic) according to its reliability
    • Use the information to select the most relevant peers
    15
    Semantic Routing on Wireless Sensor Networks
  • Learning Mechanism
    Node
    LearningPeer
    Selection
    RELEVANT PEER
    QUERYID
    QueryTypes
    LearningTable
    Neighborhood Table
    ANSWER
    16
    Semantic Routing on Wireless Sensor Networks
  • Query Types
    • Defines the similarities between the queries according to different scenarios:





    17
    Semantic Routing on Wireless Sensor Networks
  • Algorithm
    Maturity
    Time
    18
    Semantic Routing on Wireless Sensor Networks
  • Deployment
    BloomTable
    BloomGlobal
    BloomPerso
    19
    Semantic Routing on Wireless Sensor Networks
  • Algorithm
    • HandleMessage() function
    20
    Semantic Routing on Wireless Sensor Networks
  • Algorithm
    21
    SendResponse
    1545
    ForwardResponse
    ForwardRequest
    1256
    SendRequest
    1234
    Semantic Routing on Wireless Sensor Networks
  • Algorithm (intern)
    22
    Node
    QUERYID
    PEER
    Relevant Peer
    Bloom
    Table
    No
    Reliable Peer
    Learning
    Table
    No
    Random
    Selection
    Random Peer
    Semantic Routing on Wireless Sensor Networks
  • Alert management
    • Alert message contains :
    • Value
    • Error
    • Alerts are directly (hop by hop) sent to the sink
    • If the neighborhood does not record any alert then the alert is ignored
    • Receiving a false alert message
    • Update its « reference values »
    23
    Semantic Routing on Wireless Sensor Networks
  • Outline
    24
    Semantic Routing on Wireless Sensor Networks
  • Simulation
    • Simulation Software
    • Omnet++
    • Why?
    • ZigBeeunderTest
    • Abstraction of material problems (such as memory management)
    • Easy to add components
    • Other simulators
    • NS-2
    • TOSSIM
    25
    Semantic Routing on Wireless Sensor Networks
  • Work
    • Implementing the network layer
    • Implementing the tools
    • Wiki :
    • Algorithm
    • Platform installation
    • SVN
    • How to participate in our project
    http://rsimogaetan.online.fr/pfawiki/index.php5?title=PFAWiki
    26
    Semantic Routing on Wireless Sensor Networks
  • Outline
    27
    Semantic Routing on Wireless Sensor Networks
  • Performances
    • Storage reduction
    • Bloom filter
    • Error probability : 10%
    • Alphabet size : 20 words
    • Hash functions : 2
    • Vector length = 96 bits = 12 Bytes = Stored size
    • Without using Bloom filters
    • Stored size ≈ 1200 bits
    Compression Ratio ≈ 8%
    28
    Semantic Routing on Wireless Sensor Networks
  • Performances
    • Deployment
    • Nodes : 25
    • Average number of neighbors : 3
    • Scope of a node : 100 m
    Time to deploy : 150 s
    Message size: 120 bits
    29
    Semantic Routing on Wireless Sensor Networks
  • Performances
    30
    Semantic Routing on Wireless Sensor Networks
  • Performances
    • Normal process
    • Random node generates a request
    • TTL = 4
    • Network learns from communications
    31
    Semantic Routing on Wireless Sensor Networks
  • Performances
    • Normal process
    • A learning network .
    32
    Semantic Routing on Wireless Sensor Networks
    Gain of 50%
    Receivedrequests
    Simulation time
  • Outline
    33
    Semantic Routing on Wireless Sensor Networks
  • Conclusion
    • Implementation of an adaptative semantic routing algorithm.
    • SRWSN meets the Wireless Sensor energy and storage constraints.
    • SRWSN is quickly deployed although nodes are randomly set.
    • SRWSN learns from its environment and can adapt to new query types.
    34
    Semantic Routing on Wireless Sensor Networks
  • Further work
    • Learning events
    • Recording the succession of alerts for one event
    • For instance : Fire = Light  Temperature
    • Using ID’s form to direct traffic
    • Add location-based queries
    • Especially for queries from the sink to one node
    • Use another data-oriented algorithm in our scenario to show SRWSN comparison
    • Alert management improvement
    • Using events
    • Predict a temperature alert in case of a previous light one
    35
  • Thank you
    HUMIDITY
    Questions
    TEMPERATURE
    SOUND
    PRESSURE
    LIGHT
    36
    Semantic Routing on Wireless Sensor Networks