Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks

Abstract

Deployment is a fundamental issue in wireless sensor networks (WSNs), which affects the performance and lifetime of the networks. Usually the sensor locations are precomputed based on "perfect" sensor detection model, whereas sensors may not always provide reliable information, either due to operational tolerance levels or environmental factors. Therefore, it is very important to take into account this uncertainty in the deployment process. In this paper, we address the problem of sensor deployment in a mixed sensor network where the mobile and static nodes work collaboratively to perform deployment optimization task. We consider the Gaussian white noise in the environment and present a centralized algorithm (FABGM for short) which discoveres vacancies by using detection model based on false alarm and moves the mobile nodes according to the method based on bipartite graph matching in this study. In this algorithm, the management node of the WSNs collects the geographical information of all of the static and mobile sensors. Then, the management node executes the algorithm to get the best matches between mobile sensors and coverage holes. Simulation results are presented to demonstrate the effectiveness of the proposed approach.

T-MQM: Testbed based Multi-metric Quality Measurement of Sensor Deployment for Precision Agriculture-A Case Study

“…Although random deployment has been considered yet, the presence of obstacles in the field of interest has not been realized. Uncertainty Aware Deployment Technique (UADT) has been evaluated using detection probability and connectivity percentage in mixed wireless sensor networks [20]. In particular, authors have suggested a deployment approach which discovers coverage holes by computing joint detection probability and moves the appropriate mobile sensors into coverage holes using bipartite graph based approach.…”

“…Therefore, qualitative measurements of these geometrical model based deployment patterns for precision agriculture use case of WSNs need to be investigated considering the early stage development in precision agriculture use case of WSNs [9,12]. Further, most of these geometrical model-based deployment patterns have been evaluated using single [13][14][15][16] or double [17][18][19][20] metrics of coverage and connectivity. In real applications, performance of these geometrical model-based deployment patterns are quite different and far away from the reported performance in literature which are based on evaluations considering single or double metrics of coverage and connectivity [21].…”

3D Self-Deployment Algorithm in Mobile Wireless Sensor Networks

“…While, the dynamic deployment methods are mainly used in a mobile WSNs (i.e. the sensor node has mobility) [3], after being scattered in AOI, the sensor nodes accomplish deployment autonomously. The autonomous deployment of mobile WSNs is a process in which the mobile sensor nodes adjust their positions dynamically according to a certain algorithm.…”