Hamid Mahboubi

Distributed Deployment Algorithms for Improved Coverage in a Network of Wireless Mobile Sensors

In this paper, efficient sensor deployment strategies are developed to increase coverage in wireless mobile sensor networks. The sensors find coverage holes within their Voronoi polygons and then move in an appropriate direction to minimize them. Novel edge-based and vertex-based strategies are introduced, and their performances are compared with existing techniques. The proposed movement strategies are based on the distances of each sensor and the points inside its Voronoi polygon from the edges or vertices of the polygon. Simulations confirm the effectiveness of the proposed deployment algorithms and their superiority to the techniques reported in the literature.

Distributed Deployment Strategies for Improved Coverage in a Network of Mobile Sensors With Prioritized Sensing Field

Efficient deployment strategies are proposed for a mobile sensor network, where the coverage priority of different points in the field is specified by a given function. The multiplicatively weighted Voronoi (MW-Voronoi) diagram is utilized to find the coverage holes of the network for the case where the sensing ranges of different sensors are not the same. Under the proposed strategies, each sensor detects coverage holes within its MW-Voronoi region, and then moves in a proper direction to reduce their size. Since the coverage priority of the field is not uniform, the target location of each sensor is determined based on the weights of the vertices or the points inside the corresponding MW-Voronoi region. Simulations validate the theoretical results.

Self-Deployment Algorithms for Coverage Problem in a Network of Mobile Sensors with Unidentical Sensing Ranges

In this paper, efficient sensor deployment algorithms are proposed to improve the coverage area in the target field. The proposed algorithms calculate the position of the sensors iteratively, based on the existing coverage holes in the target field. The multiplicatively weighted Voronoi (MW-Voronoi) diagram is used to discover the coverage holes corresponding to different sensors with different sensing ranges. Under the proposed procedures, the sensors move in such a way that the coverage holes in the target field are reduced. Simulation results are provided to demonstrate the effectiveness of the deployment schemes proposed in this paper.

An Efficient Target Monitoring Scheme With Controlled Node Mobility for Sensor Networks

This paper is concerned with target monitoring using a network of collaborative mobile sensors. The objective is to compute (online) the desired sensing and communication radii of sensors as well as their location at each time instant, such that a set of prescribed specifications are met. These specifications include end-to-end connectivity preservation from the target to a fixed destination, while durability of sensors is maximized and the overall energy consumption is minimized. The problem is formulated as a constrained optimization, and a procedure is presented to solve it. Simulation results demonstrate the effectiveness of the proposed techniques.

Distributed Deployment Algorithms for Efficient Coverage in a Network of Mobile Sensors With Nonidentical Sensing Capabilities

In this paper, efficient deployment algorithms are proposed for a mobile sensor network to improve the coverage area. The proposed algorithms find the target position of each sensor iteratively, based on the existing coverage holes in the network. The multiplicatively weighted Voronoi (MW-Voronoi) diagram is used to discover the coverage holes corresponding to different sensors with different sensing ranges. Three sensor deployment algorithms are provided, which tend to either move sensors out of densely packed areas or place them in proper positions with respect to the boundaries of the MW-Voronoi regions. Under the proposed procedures, the sensors move in such a way that the coverage holes in the target field are reduced. Simulations confirm the effectiveness of the deployment algorithms proposed in this paper.

A Distributed Deployment Strategy for a Network of Cooperative Autonomous Vehicles

This brief presents a distributed deployment algorithm for a network of heterogeneous mobile agents to minimize a prescribed cost function. This function is concerned with the cost of serving the entire field by all agents, where the so called operation cost of different agents are not necessarily the same. The problem is investigated for the case where agents have different types of dynamics. Using a multiplicatively-weighted Voronoi diagram, the field is partitioned to smaller regions (one for each agent). A distributed coverage control law is then provided that guarantees the convergence of agents to the optimal configuration with respect to the above-mentioned cost function. The effectiveness of the proposed algorithm is demonstrated by simulations and experiments on a testbed with two types of unmanned vehicles (aerial and ground).

Distributed coordination of multi-agent systems for coverage problem in presence of obstacles

This paper presents new algorithms for distributed deployment of a network of multi-agent systems to minimize prescribed cost function. It is assumed that the so-called “operation cost” of distinct agents can be different. The problem is investigated for both cases of an obstacle-free environment and a fixed-obstacle environment. For the former case, the center multiplicatively weighted Voronoi (CMWV) configuration is introduced, and it is shown to be the optimal configuration. A distributed coverage control is also provided which guarantees that the configuration of the agents converges to this optimal configuration. For the case of a fixed-obstacle environment, the visibility-aware multiplicatively weighted Voronoi (VMW-Voronoi) diagram is introduced and a motion coordination strategy is presented to achieve the desired objective. Simulations demonstrate the effectiveness of the proposed algorithms in both cases.

Self-deployment algorithms for field coverage in a network of nonidentical mobile sensors: Vertex-based approach

In this paper, efficient deployment algorithms are proposed for a mobile sensor network to enlarge the coverage area. The proposed algorithms calculate the position of the sensors iteratively based on existing coverage holes in the field. To this end, the multiplicatively weighted Voronoi (MW-Voronoi) diagram is used for a network of mobile sensors with different sensing ranges. Under the proposed procedures, the sensors move in such a way that the coverage holes in the network are reduced. Simulation results are provided to demonstrate the effectiveness of the deployment schemes proposed in this paper.

Optimal target tracking strategy with controlled node mobility in mobile sensor networks

This paper is concerned with target tracking using a network of collaborative sensors. The objective is to compute (online) the desired sensing and communication radii of sensors as well as their location at each time instant, such that a set of prescribed specifications are achieved. These specifications include end-to-end connectivity preservation from the target to a fixed destination, while durability of sensors is maximized and the overall energy consumption is minimized. The problem is formulated as a constrained optimization, and a procedure is presented to solve it. Simulation results demonstrate the effectiveness of the proposed techniques.

Distributed deployment algorithms for improved coverage in mobile sensor networks

In this paper, sensor deployment strategies are studied for effective coverage in wireless sensor networks. In the proposed algorithms, each sensor discovers the coverage holes within its Voronoi polygons, and then moves in a proper direction to minimize them. Novel edge-based and vertex-based strategies are proposed for efficient sensor deployment, and their features are compared with existing techniques. The algorithms proposed in this paper consider the distances of each sensor and the points inside its corresponding Voronoi polygon from the edges or vertices of the polygon. It is shown that the methods introduced in this work outperform existing strategies. Simulations confirm the effectiveness of the proposed deployment algorithms, and their superiority over the techniques reported in the literature.