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Presentation on sensor network Presentation on sensor network Presentation Transcript

  • Aggregation In Wireless Sensor Network.
    Under the guidance of
    Dr. N. Marchang.
    By
    H. Saratchandra
    MT/11/CSE/04
  • I. Introduction
    sensor networks composed of small and cost effective sensing devices equipped with wireless radio transceiver for environment monitoring.
  • Advantages
    does not require infrastructure such as
    electric mains for power supply
    wired lines for Internet connections to collect data.
    human interaction while deploying.
    These sensor nodes can monitor the environment.
  • Aggregation
    The intelligent way to combine and compress the data belonging to a single cluster is known as data aggregation in cluster based environment.
    Clustering
    process of grouping the sensor
    nodes in a densely deployed large-scale sensor network
  • Goal of aggregation
    The main goal of these algorithms is to gather and aggregate data in an energy efficient manner
    network lifetime is enhanced.
    WSN offer an increasingly attractive method of data gathering in distributed system architectures and dynamic access via wireless connectivity.
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  • Issues in clustering
    how many clusters should be formed that could optimize some performance parameter.
    how many nodes should be taken into a single cluster.
    the selection procedure of cluster-head in a cluster.
  • II. Problem Definition
    Aims of aggregation protocols.
    eliminating redundant data transmission.
    improve the lifetime of energy constrained wireless sensor network.
  • Multi-hop fashion .
    Nodes neighbor nodes close to sink.
    Not energy efficient.
    Improvement over the above approach.
    Clustering.
    nodes
    CH(cluster-head)
    perform aggregation
    Sink
  • Cont.
    Performing aggregation function over CH still causes significant energy wastage.
    homogeneous sensor network CH will soon die out and again re-clustering has to be done which again cause energy consumption.
  • III. DATA AGGREGATION:
    Data aggregation is a process of aggregating the sensor data using aggregation approaches.
    Low Energy Adaptive Clustering Hierarchy
    Tiny Aggregation
    Fig : General architecture of the data aggregation algorithm
  • There are many types of aggregation techniques
    • Centralized Approach
    • In-Network Aggregation
    • Tree-Based Approach
    • Cluster-Based Approach
  • Cluster-based approach
    the LEACH protocol is proposed to cluster sensor nodes.
    let cluster-heads aggregate data and communicate with the base-station(BS) directly using high transmission power.
    The cluster-heads are randomly elected in each round to distribute energy consumption among all nodes.
  • uses the base-station to broadcast CH assignment to further spreading out the CHs throughout the network.
    refines the cluster-head election algorithm that does not require the participation of the base-station and scatters CHs more evenly across the network.
  • node2
    node3
    node1
    Broadcast at the setup stage of each round
    node4
    node5
    Fails to conserve energy
    Highest transmission power
  • LEACH based protocol assumes that BS can be reach by any Node in one hop.
    Limit the size of Network.
    Disadvantages
    Data cannot be aggregated properly.
    CH has to send many packets to the BS using high transmission power.
  • IV. QUERY PROCESSING
    Query Models.
    Query Language in TinyDB.
    Queries and Aggregates .
  • 1.Query Models.
    COUGAR approach proposes a query layer to support aggregate queries.
    the clients can issue queries without knowing how the results are generated, processed and returned by the sensor network to them.
    TAG also proposes a query model for supporting aggregate queries.
  • 2. Query Language in TinyDB
    based on SQL TinySQL
    Supports:-
    selection
    projection
    determining sampling rate
    group aggregation
    user defined aggregation
    event trigger
    lifetime query
    setting storing point and
    simple join
  • 3. Queries and Aggregates
    Simple queries.
    Complex queries.
    Event Driven queries.
  • 1. Simple queries
    These are non aggregate queries.
    E.g. "SELECT temperature FROM sensor WHERE node = z".
    These are generally mapped into broadcast or point to point queries.
  • 2. Complex queries
    They may contain sub queries.
    E.g. "SELECT temperature FROM sensor WHERE room = (SELECT room WHERE floor = ’3’)"
  • 3. Event Driven Queries
    continuous query that returns the values periodically at specified time intervals.
    Eg: “SELECT AVG (temperature) FROM sensor where node = z“
  • The Grammar of TinySQL query language is as follows:
    SELECT select-list
    [FROM sensors]
    WHERE predicate 294
    [GROUP BY gb-list]
    [TRIGGER ACTION command-name[(param)]]
    [EPOCH DURATION time]
    attribute list of the unlimited virtual
    relational table
    Query Condition
    subordinate clause which defines the trigger
    Attribute list
    trigger operation
    query cycle
  • an example of a TinyDB query,
    SELECT nodeid, AVG(light), AVG(temp)
    FROM sensors
    WHERE AVG(light)=100
    GROUP BY nodeid
    EPOCH DURATION 5min
  • V. SIMULATION
    Simulation Tools:
    TOSSIM,
    NS-2,
    OPNET,
    OMNet++,
    J-Sim,
    GlomoSim, and
    Qualnet
  • TOSSIM
    discrete event simulator for TinyOS sensor networks.
    Instead of compiling a TinyOS application for a mote, users can compile it into the TOSSIM framework, which runs on a PC.
    allows users to debug, test, and analyze algorithms in a controlled and repeatable environment.
  • VI. CONCLUSION
    The two most important parts of data communication in sensor networks-
    query processing,
    data aggregation.
    communication in sensor networks is different from other wireless networks.
    It is an energy constrained network. The process of data aggregation becomes an important issue and optimization is needed. Efficient data aggregations not only provide energy conservation but also remove redundancy data and hence provide useful data only.
  • Thank you
  • Reference:-
    S. Lindsey and C. Raghavendra, “PEGASIS: Power-efficient gathering in sensor information systems,” in Proceedings of IEEE AerospaceConference, vol. 3, Mar. 2002, pp. 1125–1130.
    Nandini. S. Patil, Prof. P. R. Patil, “Data Aggregation in Wireless Sensor Network” .