Data aggregation in wireless sensor network , 11751 d5811


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Data aggregation in wireless sensor network , 11751 d5811

  1. 1. Presented ByP.Praveen Kumar(09751A0581)B.TECH (CSE),SITAMS.
  2. 2. Sensor networks are collection of sensor nodeswhich co-operatively send sensed data to base station.As sensor nodes are battery driven, an efficientutilization of power is essential in order to use networksfor long duration hence it is needed to reduce data trafficinside sensor networks, reduce amount of data that needto send to base station. The main goal of dataaggregation algorithms is to gather and aggregate datain an energy efficient manner so that network lifetime isenhanced. Wireless sensor networks (WSN) offer anincreasingly Sensor nodes need less power forprocessing as compared to transmitting data. It ispreferable to do in network processing inside networkand reduce packet size.
  3. 3.  Data aggregation is a process of aggregating the sensor data using aggregation approaches. The algorithm uses the sensor data from the sensor node and then aggregates the data by using some aggregation algorithms such as centralized approach, LEACH(low energy adaptive clustering hierarchy),TAG(Tiny Aggregation) etc. This aggregated data is transfer to the sink node by selecting the efficient path.
  4. 4. This is an address centric approach where each node sends data to a central node via the shortest possible route using a multi-hop wireless protocol. Thesensor nodes simply send the data packets to a leader, which is the powerful node. The leader aggregates the data which can be queried.
  5. 5. In-network aggregation is the Global process of gathering and routing information through a multi-hop network, processing data at intermediate nodes with the objective of reducing resource consumption (in particular energy), thereby increasing network lifetime. There are two approaches for in-network aggregation: with size reduction and without size reduction.
  6. 6. Tree based approach
  7. 7. In the tree-based approach perform Aggregation by constructing an aggregation tree, which could be a minimum spanning tree, rooted at sink and source nodes are considered as leaves. Each node has a parent node to forward its data. Flow of data starts from leaves nodes up to the sink and therein the aggregation done by parent nodes.
  8. 8. In cluster-based approach, whole Network is divided in to several clusters. Each cluster has a cluster-head which is selected among cluster members. Cluster heads do the role of aggregator which aggregate data received from cluster members locally and then transmit the result to sink.
  9. 9. We have plenty of simulation tools orsimulators for simulating wireless networksThe simulators which are most popular areTOSSIM, NS-2, OPNET, OMNet++, J-Sim,GlomoSim, and Qualnet and so on. TOSSIMis a discrete event simulator for TinyOS (TinyOSis a popular sensor network operating system)sensor networks.
  10. 10.  1) Simple Queries These are aggregate queries. Eg. "SELECT temperature FROM sensor WHERE node = z". These are generally mapped into broadcast or point to point quires
  11. 11.  They may contain sub queries. Eg. "SELECT temperature FROM sensor WHERE room = (SELECT room WHERE floor = ’3’)"
  12. 12.  These are the continuous query that returns the values periodically at specified time intervals. Eg: “SELECT AVG (temperature) FROM sensor where node =“Z”
  13. 13.  With aggregation query: SELECT MAX (temp), AVG (light) FROM SENSORS SAMPLE PERIOD 2048 Without aggregation query: SELECT light FROM sensors SAMPLE PERIOD 2048 With aggregation and with clustering query: SELECT AVG(light) FROM SENSORS GROUP BY NODEID % 2SAMPLE PERIOD 2048.
  14. 14. Simulation results and comparison
  15. 15.  Enhance robustness and accuracy of information Reduce traffic load &conserve energy of sensors
  16. 16.  Malicious attacker Cannot ensure correctness Increase power consumption
  17. 17. CONCLUSION In this work we have studied the twomost important parts of data communication insensor networks- query processing, dataaggregation and realized how communicationin sensor networks is different from otherwireless networks. Wireless sensor networksare energy constrained network. Since most ofthe energy consumed for transmitting andreceiving data, the process of data aggregationbecomes an important issue and optimizationis needed. Efficient data aggregations not onlyprovide energy conservation but also removeredundancy data and hence provide useful dataonly.