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Presentation on sensor network
 

Presentation on sensor network

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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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      Number of children is unknown.
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      Goal: Count the number of nodes in the network.
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      Goal: Count the number of nodes in the network.
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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” .