Survey of Deployment Algorithms in Wireless Sensor Networks: Coverage and Connectivity Issues and Challenges

International audienceWireless Sensor Networks (WSNs) have many fields of application, including industrial, environmental, military, health and home domains. Monitoring a given zone is one of the main goals of this technology. This consists in deploying sensor nodes in order to detect any event occurring in the zone of interest considered and report this event to the sink. The monitoring task can vary depending on the application domain concerned. In the industrial domain, the fast and easy deployment of wireless sensor nodes allows a better monitoring of the area of interest in temporary worksites. This deployment must be able to cope with obstacles and be energy efficient in order to maximize the network lifetime. If the deployment is made after a disaster, it will operate in an unfriendly environment that is discovered dynamically. We present a survey that focuses on two major issues in WSNs: coverage and connectivity. We motivate our study by giving different use cases corresponding to different coverage, connectivity, latency and robustness requirements of the applications considered. We present a general and detailed analysis of deployment problems, while highlighting the impacting factors, the common assumptions and models adopted in the literature, as well as performance criteria for evaluation purposes. Different deployment algorithms for area, barrier, and points of interest are studied and classified according to their characteristics and properties. Several recapitulative tables illustrate and summarize our study. The designer in charge of setting up such a network will find some useful recommendations, as well as some pitfalls to avoid. Before concluding, we look at current trends and discuss some open issues

Relocation of Mobile Wireless Sensors in the Presence of Obstacles

International audienceIn many applications (e.g military, environment monitoring), wireless sensors are randomly deployed in a given area. Unfortunately, this deployment is not efficient enough to ensure area coverage and network connectivity. Algorithms based on Virtual Forces are used to improve the random initial deployment. In this paper, we want to ensure coverage and network connectivity in a given area containing obstacles. We enhance the Distributed Virtual Forces Algorithm (DVFA) to cope with obstacles. Obstacles are characterized by prohibiting both the physical presence of sensors and the wireless communication. Performance evaluation shows that DVFA provides an efficient deployment even if obstacles exist in the considered area

GDVFA: A distributed algorithm based on grid and virtual forces for the redeployment of WSNs

International audienceThe distributed virtual forces deployment algorithm provides a very good area coverage and guarantees network connectivity for a sufficient number of sensor nodes. It relies on local information between neighboring sensor nodes. However, its main drawback is node oscillations and hence a high amount of sensor node energy wasted. The grid based strategy divides the monitored area into virtual cells. Each cell center determines the position of a sensor node. In this paper we propose GDVFA that combines the advantages of both strategies: on the one hand coverage and connectivity for virtual forces strategy and on the other hand avoidance of node oscillations for grid strategy. Simulation results reported in this paper show that GDVFA considerably reduces the energy consumed by sensor nodes. This comes from: 1) the detection of redundant nodes that are put in sleep mode, and 2) the avoidance of node oscillations by stopping nodes

Overview of deployment and redeployment algorithms for mobile wireless sensor networks

International audienceWireless sensor networks are usually randomly deployed in the monitored region. This initial deployment does neither achieve area coverage, nor ensure network connectivity. Thus, a redeployment algorithm has to be applied in order to meet these two requirements. In this paper, we overview existing centralized redeployment algorithms such as virtual forces or particle swarm optimization category, as well as distributed algorithms such as Distributed Self-Spreading Algorithm, Force based Genetic Algorithm, Mass-Spring Relaxation Algorithm, unified Scheme for Deployment and Relocation. We then discuss some open issues related to algorithm convergence, assumptions about the initial knowledge available like the initial topology, number of sensor nodes and obstacle positions

Data gathering architecture for temporary worksites based on a uniform deployment of wireless sensors

International audienceData management is an important issue in wireless sensor networks. However, the data gathering process may be unsuccessful in disconnected or random networks: some data gathered cannot be delivered to the sink, coverage holes may occur and result in missing data. To cope with this problem, we propose two distributed redeployment algorithms (DVFA and ADVFA), based on virtual forces, that provide a uniform deployment of sensor nodes. Both ensure a full area coverage and network connectivity. Hence, an accurate data gathering can be done. For that purpose, we define a three-tier architecture where after the execution of a redeployment algorithm, sensor nodes are uniformly deployed to monitor a temporary worksite. A uniform deployment provides a better balancing of the routing tree (used to report the data gathered) leading to smaller data gathering delays. We also show how to save energy during the data gathering phase. We compute the optimal number of sensors needed to cover an area. Using this result, we parameterize DVFA and evaluate its performances. We then propose ADVFA to cope with DVFA drawbacks (e.g. node oscillations greedy in energy). ADVFA adapts the target distance between two neighbors to the number of operational nodes discovered. ADVFA outperforms DVFA, considerably reducing the distance traveled by nodes and then maximizing network lifetime by saving energy

Redeployment of Mobile Wireless Sensors in the Presence of Obstacles

International audienceUsually, wireless sensors are randomly deployed in a given area. Unfortunately, this deployment is not efficient enough to ensure area coverage and network connectivity. Algorithms based on Virtual Forces are used to improve the random initial deployment. In this paper, we want to ensure coverage and network connectivity in a given area containing obstacles. We enhance the Distributed Virtual Forces Algorithm (DVFA) to cope with obstacles. Obstacles are characterized by prohibiting both the physical presence of sensors and the wireless communication. Performance evaluation shows that DVFA provides an efficient deployment even if obstacles exist in the considered area

Redeployment of Randomly Deployed Wireless Mobile Sensor Nodes

International audienceWireless sensor networks (WSN) are generally ran- domly deployed in a given area. This initial deployment does not achieve neither area coverage, nor network connectivity. Thus, a redeployment algorithm has to be applied in order to achieve these two goals. This algorithm should meet performance criteria like saving energy and achieving stability. Our contribution in this paper is the design of DVFA, a distributed redeployment algorithm based on virtual forces. We simulate its behavior with NS2 and compare its performances with CVFA, a centralized version also based on virtual forces

Impact of prone position on outcomes of COVID-19 patients with spontaneous breathing

International audienceBackground: In this study, we explored whether early application of the prone position (PP) can improve severe hypoxemia and respiratory failure in coronavirus disease 2019 (COVID-19) patients with spontaneous breathing.Methods: This is a prospective observational study of severe, critically ill adult COVID-19 patients admitted to the intensive care unit. All vital parameters were recorded in real time for all patients. Moreover, the results of chest computed tomography (CT), when available, were analyzed.Results: PP was applied in 21 patients who were breathing spontaneously. The application of PP was associated with a significant increase in oxygen saturation measured by pulse oximetry (SpO2) from 82%±12% to 96%±3% (P0.05 for both).Conclusions: Our study confirmed that the early application of PP can improve hypoxemia and tachypnea in COVID-19 patients with spontaneous breathing. Randomized controlled trials are needed to confirm the beneficial effects of PP in COVID-19 patients with spontaneous breathing