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Coverage in Wireless Sensor Network Phani Teja Kuruganti AICIP lab

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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.

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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.

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Gaussian Distribution of a Sensor

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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

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Algorithm

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Voronoi triangulation and Breach Path

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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.

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Algorithm for assigning points into fields

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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

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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

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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.

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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.

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

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Coverage Map Technique Image Map of the Coverage

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Coverage Map Technique

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Under-represented Coverage

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Over-represented Coverage

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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

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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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