Modeling In-Network Processing and Aggregation in Sensor Networks

1. Modeling In-Network Processing and Aggregation in Sensor Networks Ajay Mahimkar EE 382C Embedded Software Systems Prof. B. L. Evans May 5, 2004

2. Sensor Networks • Monitor physical environment from remote locations • Challenges • Battery is the most pressing • Deployment of sensors in thousands • No manual intervention • Design protocols that extend network lifetime • Network lifetime is the time at which first node dies

3. In-Network Processing • Why data aggregation??? • Individual sensor readings are of limited use • Delivering large amount of data from all nodes to a central point consumes lot of energy • Conserves limited energy and bandwidth • Increases system lifetime

4. Existing Approaches • Directed Diffusion [Intanagonwiwat, 2003] • LEACH (Low Energy Adaptive Clustering Hierarchy) [Heinzelman, 2000] • Cluster-Head responsible for data aggregation

5. Existing Approaches … cont. • PEDAP (Power Efficient Data gathering and Aggregation Protocol) [Tan, 2003] • MST (Minimum Spanning Tree) based routing using energy as the metric • Disadvantages • Locally optimizes energy • Increases end-to-end latency

6. 4 5 A B C 6 3 PEDAP D S DEEPADS 3 7 E F G H 2 1 2 DEEPADS – A Novel Approach • Distributed Energy-Efficient Protocol for Aggregation of Data in Sensor Networks (DEEPADS) • Novel approach that globally maximizes the energy and increases system lifetime

7. C-DEEPADS • Uses Clustering Approach • Two Tier Methodology • Sensors organize themselves into clusters, each cluster represented by a cluster-head • Global energy metric similar to DEEDAP • Cluster-head aggregates data and transmits to the base station • Reduces end-to-end latency

8. Simulation • Using Ptolemy-II, VisualSense and Java • Discrete Event Model • Network Simulation • Setup • Environment • 100 m x 100 m area • Sensors location • Uniformly distributed x and y random variables Simulation Parameters

9. Sensor Node Model

10. Performance Evaluation

11. Performance Evaluation … cont.

12. Discussion • Results • DEEPADS & C-DEEPADS perform much better than existing approaches • Increase in the system lifetime • Reduction in the total energy consumption • Future Work • Repeat experiments taking into consideration the sleep mode in sensors

13. Questions ???Comments !!!