Abstract

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.

Highlights

  • Over the last decade, Wireless Sensor Networks (WSN) have generated a considerable enthusiasm from the networking researchers community

  • In this paper, we address the Wireless Sensor Network (WSN) deployment issue

  • We consider that each point in the deployment area is associated a differentiated detection probability threshold, which must be satisfied by our deployment method

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Summary

Introduction

Wireless Sensor Networks (WSN) have generated a considerable enthusiasm from the networking researchers community. A sensor is supposed to surely detect (detection probability is equal to 1) an event if and only if the distance between the sensor and the event is less than a particular sensing range This model was mainly considered in works addressing area coverage problems, such as target detection or k-coverage problem [2]. WSN by ensuring the network connectivity and the deployment field characterized by: (1) a probabilistic event detection model and (2) a geographical irregularity of the sensed event To solve this problem we propose an original pseudo-random method, based on the Tabu Search algorithm.

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Initialization
Neighborhood exploration function
Cost function and selection of new solution
Initialization stage
Selection of new solution
Findings
Conclusion and Future Work
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