International audienceUnderwater sensors technology has experienced a tremendous development over the last decade. They have generated considerable community enthusiasm, which applied them to a wide range of cases that could enhance human and animal habitat conditions e.g. climate changes prediction or pollution surveillance. In this paper, we address the issue of deploying a UWSN in an area characterized by the geographical irregularity of the sensed event. Our specific application context regards the monitoring of the water quality in a small closed area (e.g. a lake). For this purpose, we propose a differentiated deployment algorithm (DDA) based on a mesh representation method inspired from the image processing and 3D modeling field
International audienceIn this paper, we will address a WSN deployment problem. The main objectives are i) reduce the cost of deployment, ii) ensure the requested event detection probabilities, iii) guarantee the network connectivity, and iv) maximize the lifetime of the network. We will formalize the problem as multi-objective combinatorial optimization problem. To resolve the problem, we will propose a new deployment algorithm named MODA. It will be based on evolutionary and neighborhood search algorithms. The obtained results are better than the deployment strategies found in the literature
In this paper, we address the Wireless Sensor Network (WSN) deployment issue. We assume that the observed area is characterized by the geographical irregularity of the sensed events. Formally, we consider that each point in the deployment area is associated a differentiated detection probability threshold, which must be satisfied by our deployment method. Our resulting WSN deployment problem is formulated as a Multi-Objectives Optimization problem, which seeks to reduce the gap between the generated events detection probabilities and the required thresholds while minimizing the number of deployed sensors. To overcome the computational complexity of an exact resolution, we propose an original pseudo-random approach based on the Tabu Search heuristic. Simulations show that our proposal achieves better performances than several other approaches proposed in the literature. In the last part of this paper, we generalize the deployment problem by including the wireless communication network connectivity constraint. Thus, we extend our proposal to ensure that the resulting WSN topology is connected even if a sensor communication range takes small values.
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