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    Intelligent & Reliable Data

    Transmission Protocol for

    Highly Destructible Wireless

    Sensor Networks

    By:Zeeshan Dawoodani (20363758)

    MEng (ECE)

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    Introduction

    WSN A large number of sensor nodes interconnected

    wirelessly to accomplish a common task

    Applications Real time applications such as in battlefield, vehicletracking, wildlife monitoring, environmental

    applications

    Characteristics Mobility, Power constraint, prone to failure, short life

    span, prone to damage, transmit and forward data

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    DWSN

    Deployed for a class of special applications that havethe common requirement on instantly responding to

    collecting and transmitting sensory data.

    Applications: Volcanic eruption monitoring, nuclear

    leakage detection, battlefield surveillance.

    Two challenging issues exist in these applications for

    successfully accomplishing the task:

    1. Prone to Damage

    2. Short Duration

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    Architecture of DWSN

    Hierarchal cluster based network architecture

    One Base Station and numerous sensor nodes

    which are self organized into number of clusters.

    Cluster head can be reached by all its cluster

    members.

    Randomized rotation to take the duty of being

    cluster head.

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    Low EnergyAdaptive Clustering

    Hierarchy (L

    EA

    CH) Employs hierarchal clustering

    scheme, in which sensor

    nodes organize themselves

    into cluster

    Within each cluster a cluster

    head is elected to coordinate

    the message transmission

    between its cluster membersand the base station.

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    Efficient Clustering of Data Gathering

    protocol (ECDG) Groups sensor nodes into

    clusters

    Builds a routing tree basedon evenly distributed cluster

    headers

    Only root node of the

    routing tree communicateswith the base station.

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    IRDT Protocol

    It is deployed in cluster heads and is composed ofthree mechanism.

    1. Correct Probability Calculation Mechanism (CPCM)

    2. Information Classification Mechanism (CM)3. Intelligent Balancing Mechanism (IBM)

    I. Redundancy Filter Component (RFC)

    II. Compensation Judgment Component (CJC)III. Message Compensation Component (MCC)

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    Architecture of IRDT Protocol

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    Correct Probability Calculation

    Mechanism Estimates the correct probability that can allow the

    cluster head to decide the amount of messages to be

    sent to the base station.

    It can guarantee that at least one message arrives at

    the base station successfully.

    It can prune the excessive message and reduce the

    communication overhead.

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    Correct Probability Calculation

    Mechanism (cont.) Error Rate: The rate of the number of messages

    incorrectly received to the total number of messages

    sent during a specified time interval

    Correct Probability: The probability that a node

    receives message successfully from another node

    during a certain time interval

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    Correct Probability Calculation

    Mechanism (cont.) The amount of packets correctly received by the

    receiver can be given as:

    Ar

    =Ai(1-Pe)

    The correct probability can be estimated as:

    Pt = (1-Pe)(Hi-1)

    Now, if we want that at least 1 message sent from

    cluster head arrives at the base station i.e. Ar=1. Then

    Ai = 1 / (1-Pe) (Hi-1)

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    Classification Mechanism

    Responsible for message classification and

    dissemination of different types of messages

    Types of Messages:1) Generated by the cluster head itself

    2) Generated by the other non-cluster heads nodes in the same

    cluster

    3) Forwarded from other cluster heads

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    Classification Mechanism (cont)

    Contains a buffer named Loglist.

    Loglist

    L = length of Loglist

    T = service time of the cluster head

    = birth rate of messages for each

    sensor

    h = probability of arrival in time

    interval (h>0)

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    Intelligent Balancing Mechanism

    It performs the compensation judgment, whichdecides whether the cluster head should filter or

    compensate the message. It consists of three

    components:

    a) Redundancy Filter Component (RFC)

    Multiple nodes in the same cluster can report a single event

    with the same message.

    RFC component focuses on filtering the redundant messages.

    We aggregate the message and send a certain amount of

    messages for reliability purpose.

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    Algorithm of RFC Input Mnew from CJC;

    ifMnew

    LogListand Frequency > = MAXthen {

    Count the amount of the type ofMnew;

    Filterredundant messages during a time period;

    Update the LogList;

    }

    else {

    Transmit Mnewto BS;

    Update the LogList;

    }

    ifSent message insufficient then {

    Send compensation requirement to CJC;

    Invoke MCC;

    }

    return

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    Intelligent Balancing Mechanism (cont..)

    b) The Compensation Judgment Component (CJC)

    The CJC component judges whether or not compensate the

    message.

    It decides whether to invoke the compensation component or

    not based on saturation information feedback from RFC

    Compares the new incoming message (Mnew) from the cluster

    node with history records in Loglist (Mi) to identify the type ofnew message.

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    Algorithm of CJC

    Input Mnew;

    Transmit Mnewto BS via RFC directly;

    ifget the message insufficient feedback Then{

    Invoke compensation function;

    }

    return

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    Algorithm for Matching Message Input Mnew;

    fori = 1 to D.Length{ ifsim (Mnew, Mi) Threshodthen {

    Mi.Frequency++;

    Upate LogList;

    Break; // Match correctly

    } }

    ifi D.Length then{

    Mnew is new type message;

    RegisterMnew into LogList;

    Update LogList; //RegisterMnew

    }

    Return

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    Intelligent Balancing Mechanism (cont..)

    c) The Message Compensation Component (MCC)

    It compensates the number of sending messages in case of

    disaster in a cluster to ensure reliability.

    The MCC component is invoked in the following situations:

    1. The cluster is damaged in large proportion which causes

    the message insufficient.

    2. The cluster catches transient events which happen and end

    within a certain period.

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    Algorithm of MCC

    Input compensation command from CJC; ifMnewLogListand Frequency < MAXthen {

    Sent duplicate of Messagex;

    Update LogList

    }

    ifMnew.Frequency < MAXthen goto 01;

    return

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    Cluster Destruction in DWSN

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    IRDT Benefits

    IRDT generates the least amount of error messagesfor same number of sent messages.

    IRDT sends fewer messages in order to ensure that

    the message has been sent reliably to the base station.

    IRDT protocol can compensate the insufficient

    messages in the WSN deformity period.

    IRDT also performs better in terms of the networklifetime.

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    Conclusion

    In addition to reducing the amount of messages

    transmitted and compensating messages for the

    insufficient collection, the IRDT protocol can

    improve the reliability of instant sensory data

    gathering and transmission in the DWSN.

    The only limitation of the protocol is that it is only

    implemented in the cluster head rather than in all the

    nodes of the sensor network

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    References N. Heo and P. K. Varshney,An IntelligentDeployment and Clustering Algorithm fora

    D

    istr

    ibuted Mobile Sensor

    Network

    , Pr

    oceedings of IEEE Inter

    national Confer

    ence onSystems, Man and Cybernetics, October, 2003

    M.T. Hsu, F. Y. S. Lin, Y. S. Chang and T. Y. Juang, The Fault Probability Estimation

    andDecision Reliability Improvement in WSNs, Proceedings of the IEEE Region 10

    Annual International Conference (TENCON), Taipei, Taiwan, October30-November

    2, 2007.

    T. Sun, L. J. Chen, C. C. Han, M. Gerla, Reliable SensorNetworks forPlanet

    Exploration, The 2005 IEEE International Conference On Networking, Sensing andControl (ICNSC 2005), 2005.

    S. Bandyopadhyay and E. J. Coyle,An Energy Efficient Hierarchical Clustering

    Algorithm forWireless SensorNetworks, Proceeding of IEEE INFOCOM03, San

    Francisco, April, 2003.

    F. Zhen, Y. Yuan and P. Myong-Soon, Efficient Clustering ofData Gathering in

    Wir

    eless Sensor

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