1. Wireless Access and Networking Technology (WANT) Lab. An Efficient Data Aggregation Approach for Large Scale Wireless Sensor Networks Globecom 2010 Lutful Karim, Nidal Nasser, Hanady Abdulsalam, Imad Moukadem

2. Wireless Access and Networking Technology (WANT) Lab. 2 Outline Introduction Introduction Purposed Algorithm Purposed Algorithm Simulation Results Simulation Results Conclusions Conclusions

3. Wireless Access and Networking Technology (WANT) Lab. 3 Introduction Wireless sensor networks (WSNs) have significant potential in many application domains – Agriculture – Health – Environmental monitoring – Battlefield surveillance – Wild fire detection Cannot be used in large geographical areas – Short communication range of sensors

4. Wireless Access and Networking Technology (WANT) Lab. 4 SUMAC Scalable and Unified Management And Control (SUMAC) Scalable and Unified Management And Control (SUMAC) – A large scale Wireless Sensor Network architecture Meshed WiFi WiMAX Sensors Cluster

5. Wireless Access and Networking Technology (WANT) Lab. DD: Directed Diffusion DD: Directed Diffusion DABDR: Data aggregation based on dynamic routing DABDR: Data aggregation based on dynamic routing TAG: Tiny Aggregation Approach TAG: Tiny Aggregation Approach FEDA : Fault-tolerant Energy- Efficient Data Aggregation FEDA : Fault-tolerant Energy- Efficient Data Aggregation Related works

6. Wireless Access and Networking Technology (WANT) Lab. 6 Directed Diffusion(DD) Interest messages flow from the sink to the source node – Expensive flooding – Multiple paths towards the sink – Sink reinforces only a number of paths Depending on data quality To alleviate expensive flooding for interest propagation in DD – Clustering approaches are used Sink A

7. Wireless Access and Networking Technology (WANT) Lab. 7 Data aggregation based on dynamic routing(DABDR) Cluster based aggregation routing protocol Creates tree structure where parents wait a certain time for child data – Depth field – Depth field :ensures the direction of data flowing from a Sink – Queue length field – Queue length field : Sink A [7,10]

8. Wireless Access and Networking Technology (WANT) Lab. 8 Motivation A large scale WSN should not be application dependent and can work for different types of applications. Most aggregation approaches are not designed for a large scale WSN and not suitable for time critical operations – Emergency responses – Energy efficiency – End to end delay – Accuracy

9. Wireless Access and Networking Technology (WANT) Lab. 9 Goal Propose an efficient data aggregation scheme for large scale WSNs – Energy efficiency – End-to-end delay – Data accuracy – Redundancy

10. Wireless Access and Networking Technology (WANT) Lab. 10 Assumption Sensors are stationary Their positions/locations are known The Wi-Fi node has a large processing and storage capabilities and power

11. Wireless Access and Networking Technology (WANT) Lab. 11 Proposed data aggregation method Zone Creation and Active Node Selection Node Distribution and Path Establishment Data Aggregation

12. Wireless Access and Networking Technology (WANT) Lab. 12 Zone Creation and Active Node Selection Each WSN is organized as a number of small zones Each zone has one or more active and several alternative nodes Wi-Fi node is cluster head (CH) – In each grid active nodes are selected based on the Residual energy Distance Number of sleep rounds Free buffer spaces Active Sleep CH

13. Wireless Access and Networking Technology (WANT) Lab. 13 Node Distribution and Path Establishment Active nodes of zones are considered placing at different levels – Virtual hierarchy – The number of hops they are away from the CH Once active nodes are selected – CH broadcasts the position of nodes – All active nodes know the position and distance to each other 1 2 2 1 1 3 3 3 Level 1Level 2Level 3 Total distance to CH will be the minimum Power consumption will be less CH

14. Wireless Access and Networking Technology (WANT) Lab. 14 Data Aggregation The proposed data aggregation scheme is dynamic considering the aggregation type is changeable on the basis of application requirements – Require periodic data[precision agriculture] – Exceeds some threshold value[temperature] Aggregation rules are implemented in sensor nodes and users can remotely change the rules considering that a WSN can be configured for different types of applications

15. Wireless Access and Networking Technology (WANT) Lab. 15 Data Aggregation TDMA 1 2 2 1 1 3 3 3 Level 1Level 2Level 3 CH 4321 timeslot Distance CH A A

16. Wireless Access and Networking Technology (WANT) Lab. 16 Simulation Parameters ParametersValues Network Size Number of Nodes Number of Zones Cluster Head Position Data Packet Size Energy Consumptions for Sending Data Packets Energy Consumptions in free space/air Initial Node Energy 100x100 Maximum 100 Maximum 8 55x101 512 Bytes 40pJoule 2pJoule 1J

17. Wireless Access and Networking Technology (WANT) Lab. 17 Energy Consumptions of over Rounds

18. Wireless Access and Networking Technology (WANT) Lab. 18 End to End Delay over a number of Rounds

19. Wireless Access and Networking Technology (WANT) Lab. 19 Network Lifetime over Rounds

20. Wireless Access and Networking Technology (WANT) Lab. 20 Conclusions In this paper, a fault tolerant and energy efficient Dynamic Data aggregation technique is proposed. Simulation results and analysis show that the proposed data aggregation approach is more energy aware than that of SUMAC.

21. Wireless Access and Networking Technology (WANT) Lab. 21 Thank you vary much!!