A Simple Method for the Deployment of Wireless Sensors to Ensure Full Coverage of an Irregular Area with Obstacles

International audienceIn this paper, we focus on the deployment of wireless sensor nodes in an arbitrary realistic area with an irregular shape, and with the presence of obstacles that may be opaque. Moreover, we propose a simple projection-based method that tends to minimize the number of sensor nodes needed to fully cover such an area. This method starts with the opti-mal uniform deployment based on the triangular tessellation encompassing the whole area. Then, it projects some exter-nal sensor nodes on the border to ensure full coverage and connectivity. We show that this method outperforms the contour-based one using various types of irregular areas

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

Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3D Indoor Monitoring

As a result of extensive research over the past decade or so, wireless sensor networks (wsns) have evolved into a well established technology for industry, environmental and medical applications. However, traditional wsns employ such sensors as thermal or photo light resistors that are often modeled with simple omni-directional sensing ranges, which focus only on scalar data within the sensing environment. In contrast, the sensing range of a wireless video sensor is directional and capable of providing more detailed video information about the sensing field. Additionally, with the introduction of modern features in non-fixed focus cameras such as the pan, tilt and zoom (ptz), the sensing range of a video sensor can be further regarded as a fan-shape in 2d and pyramid-shape in 3d. Such uniqueness attributed to wireless video sensors and the challenges associated with deployment restrictions of indoor monitoring make the traditional sensor coverage, deployment and networked solutions in 2d sensing model environments for wsns ineffective and inapplicable in solving the wireless video sensor network (wvsn) issues for 3d indoor space, thus calling for novel solutions. In this dissertation, we propose optimization techniques and develop solutions that will address the coverage, deployment and network issues associated within wireless video sensor networks for a 3d indoor environment. We first model the general problem in a continuous 3d space to minimize the total number of required video sensors to monitor a given 3d indoor region. We then convert it into a discrete version problem by incorporating 3d grids, which can achieve arbitrary approximation precision by adjusting the grid granularity. Due in part to the uniqueness of the visual sensor directional sensing range, we propose to exploit the directional feature to determine the optimal angular-coverage of each deployed visual sensor. Thus, we propose to deploy the visual sensors from divergent directional angles and further extend k-coverage to ``k-angular-coverage\u27\u27, while ensuring connectivity within the network. We then propose a series of mechanisms to handle obstacles in the 3d environment. We develop efficient greedy heuristic solutions that integrate all these aforementioned considerations one by one and can yield high quality results. Based on this, we also propose enhanced depth first search (dfs) algorithms that can not only further improve the solution quality, but also return optimal results if given enough time. Our extensive simulations demonstrate the superiority of both our greedy heuristic and enhanced dfs solutions. Finally, this dissertation discusses some future research directions such as in-network traffic routing and scheduling issues

F.: Arbitrary obstacles constrained full coverage in wireless sensor networks

Abstract. Coverage is critical for wireless sensor networks to monitor a region of interest and to provide a good quality of service. In most cases we need to achieve full coverage which means every point inside the region (excluding the obstacles) must be covered by at least one sensor. The problem of placing the minimum number of sensors to achieve full coverage for a region with obstacles is NP-hard. Most existing coverage methods, such as contour-based ones, simply place sensors along the boundaries to cover the holes near obstacles and the region boundary. These methods are inefficient especially when obstacles or the region become irregular. In this paper, based on computational geometry, we design a full coverage method, which accurately finds the uncovered holes and places sensors efficiently for both the regular and irregular obstacles and regions. Specifically, we show that the more irregular of the obstacles and the region, the more sensors our method saves

Cooperative Coverage Control of Multi-Agent Systems

In this dissertation, motion coordination strategies are proposed for multiple mobile agents over an environment. It is desired to perform surveillance and coverage of a given area using a Voronoi-based locational optimization framework. Efficient control laws are developed for the coordination of a group of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with double-integrator and non-holonomic dynamics. The autonomous vehicles aim to spread out over the environment while more focus is directed towards areas of higher interest. It is assumed that the so-called ``operation costs'' of different agents are not the same. The center multiplicatively-weighted Voronoi configuration is introduced, which is shown to be the optimal configuration for agents. A distributed control strategy is also provided which guarantees the convergence of the agents to this optimal configuration. To improve the cooperation performance and ensure safety in the presence of inter-agent communication delays, a spatial partition is used which takes the information about the delay into consideration to divide the field. The problem is also extended to the case when the sensing effectiveness of every agent varies during the mission, and a novel partition is proposed to address this variation of the problem. To avoid obstacles as well as collision between agents in the underlying coverage control problem, a distributed navigation-function-based controller is developed. The field is partitioned to the Voronoi cells first, and the agents are relocated under the proposed controller such that a pre-specified cost function is minimized while collision and obstacle avoidance is guaranteed. The coverage problem in uncertain environments is also investigated, where a number of search vehicles are deployed to explore the environment. Finally, the effectiveness of all proposed algorithms in this study is demonstrated by simulations and experiments on a real testbed