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

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Coverage in Wireless Sensor Network Phani Teja Kuruganti AICIP lab

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.

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.

Gaussian Distribution of a Sensor

Coverage Problems in WSN Seapahn 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

Algorithm

Voronoi triangulation and Breach Path

Power Efficient Organization of Wireless Sensor Networks Sasa 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.

Algorithm for assigning points into fields

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

Sensor Placements for Grid Coverage under Imprecise Detections Santpal 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

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.

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.

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

Coverage Map Technique Image Map of the Coverage

Coverage Map Technique

Under-represented Coverage

Over-represented Coverage

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

References  Coverage Problems in WSN, Seapahn Meguerdichian, Farinaz Koushanfar, Miodrag Potkonjak, Mani.B.Srivastava  Power Efficient Organization of Wireless Sensor Networks Sasa Slijepcevic, Miodrag Potkonjak  Sensor Placements for Grid Coverage under Imprecise Detections Santpal 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

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