Coverage in Wireless Sensor Network

1. Coverage in Wireless Sensor Network Phani Teja Kuruganti AICIP lab

2. Sensors and Coverage • Sensors are of different type – uni-directional, multi-directional, omni-directional. • Coverage of each sensor is determined by the kind of sensing. • Omni directional sensors - acoustic or seismic the coverage can be assumed as a 2D-Gaussian envelope.

3. Sensors and Coverage • Placement of sensor nodes – full coverage, minimal energy consumption. • The sensor placement is in-deterministic • The sensor however are not dynamic enough to assume a deterministic position to assume maximum coverage. • Thus the problem now works around three issues of sensor field – under-covered, aptly covered, over covered. • Each case redundancies still exist due to placement.

4. Gaussian Distribution of a Sensor

5. Coverage Problems in WSNSeapahn Meguerdichian, Farinaz Koushanfar, Miodrag Potkonjak, Mani.B.Srivastava • Computational geometry and graph theoretic techniques – Voronoi Diagrams and graph search algorithms • Centralized approach – Assumes a central command centre. • Optimal polynomial time algorithm for coverage in sensor network • Converts continuous geometric problem into discrete graph problem

6. Algorithm

7. Voronoi triangulation and Breach Path

8. Power Efficient Organization of Wireless Sensor NetworksSasa Slijepcevic, Miodrag Potkonjak • A heuristic that organizes the available sensor nodes into mutually exclusive sets where the members of each of these sets of nodes completely monitors the given area. • Only one such set is active at any moment and consumes power the other set is activated when the first one is deactivated. • Assumes isotropic circular sensing systems.

9. Algorithm for assigning points into fields

10. Set K-Cover Problem Set K-Cover Problem Does the collection of subsets contain K disjoint set of covers of set A A most constrained and least constrained heuristic is developed to simulate the real scenarios This is a centralized technique and very computationally intensive since it uses simulated annealing

11. Sensor Placements for Grid Coverage under Imprecise DetectionsSantpal S.Dhillon, Krishnendu Chakrabarty, S.S.Iyengar • Resource-based optimization framework for sensor resource management • Represents sensor field as grid (2 or 3-dimensional) and works on deterministic placement of the senor nodes. • The algorithm places each sensor on a grid point, one sensor at a time – greedy heuristic. • Comparison is done between random placement Vs their deterministic PLACE_SENSORS algorithm

12. Discussion • The Voronoi Tessellation and Simulated annealing will provide good result but will have to little to offer in the context of distributed self-organized networks. • Computational ability is also a concern. • This requires a more real time and distributed algorithm for coverage issue.

13. Coverage Map Technique • Assume an omni-directional sensor with isotropic sensing capability leading to a 2D-Gaussian. • Establish a cluster head and allow each node initially to beacon it’s location obtained from the GPS to the cluster head • Produce a image map at the cluster head to represent the deployed sensor field’s Gaussians and look for black patches and bright patches on the Image. • Obtain the maximum likelihood between sensors based on the probability density function. • Fix a threshold ( p(x,y) > 0.70 ) to shutdown the sensor since the sensors are likely to cover the same area of the sensor field.

14. Coverage Map Technique • The accuracy of estimation can be acquired by knowing the variance of the sensor.

15. Coverage Map Technique Image Map of the Coverage

16. Coverage Map Technique

17. Under-represented Coverage

18. Over-represented Coverage

19. Conclusion and Future work • The related work and our approach in sensor field coverage is shown. • The coverage map technique promises to decrease redundancy. • Different sensor modalities should be considered and subsequently correlation factor should be observed. • Efficient physical level node scheduling scheme for energy consumption

20. References • Coverage Problems in WSN, Seapahn Meguerdichian, Farinaz Koushanfar, Miodrag Potkonjak, Mani.B.Srivastava • Power Efficient Organization of Wireless Sensor NetworksSasa Slijepcevic, Miodrag Potkonjak • Sensor Placements for Grid Coverage under Imprecise DetectionsSantpal S.Dhillon, Krishnendu Chakrabarty, S.S.Iyengar • On the Coverage and Detectability of Large-scale Wireless Sensor Networks Benyuan Liu, Don Towsley • Unreliable Sensor Grids : Coverage, Connectivity and Diameter Sanjay Shakkottai, R.Srikant and Ness B.Shroff