Kaveh Moezzi

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.

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.

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.

Stability of uncertain piecewise affine systems with time delay: delay-dependent Lyapunov approach

This paper addresses the problem of robust stability of piecewise affine (PWA) uncertain systems with unknown time-varying delay in the state. It is assumed that the uncertainty is norm-bounded and that upper bounds on the state delay and its rate of change are available. A set of linear matrix inequalities (LMI) is derived providing sufficient conditions for the stability of the system. These conditions depend on the upper bound of the delay. The main contributions of the paper are as follows. First, new delay-dependent LMI conditions are derived for the stability of PWA time-delay systems. Second, the stability conditions are extended to the case of uncertain PWA time-delay systems. Numerical examples are presented to show the effectiveness of the approach.

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.

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.

Adaptive robust control of uncertain neutral time-delay systems

In this paper, the problem of adaptive robust stabilization of neutral time-delay systems with uncertainties is investigated. It is assumed that the system parameters are subject to uncertainties with unknown bounds, but with known functional properties. A novel memoryless adaptive robust state feedback controller is proposed, and an adaptive scheme is introduced to estimate the bounds on uncertainties. A set of time-dependent trajectories which follow specific switching dynamic equations are utilized in the adaptive scheme and in the adaptive robust control input to achieve the stability of the closed-loop system. It is shown that by applying the proposed adaptive robust control input the states of the resultant closed- loop uncertain time-delay system will be uniformly ultimately bounded. The simulation results elucidate the effectiveness of the proposed approach.

Two-stage energy-optimal formation reconfiguration strategy

In this paper, the concept of two-stage energy-optimal reconfiguration strategy for formation flying of autonomous agents is presented. It is desired to move the agents to a special designated formation in the idle time (the time between the completion of the current formation mission and the issuance of the next reconfiguration command), in order to minimize the expected value of the reconfiguration energy consumption. The position of each agent in the special designated formation is obtained as a function of the agents current position and the weighted center of gravity of the set of possible positions for that agent. It is shown that this strategy can reduce energy consumption considerably compared to conventional strategies. In the case of constrained acceleration, it is shown that the results remain the same as the unconstrained case if the reconfiguration time is sufficiently longer than its minimum possible value. The effectiveness of the proposed strategy is illustrated by simulation.

Controller Design for Rate Assignment in Wireless Networks

In this paper, data-rate assignment in IS-856 uplink (reverse link) is studied. The problem is first formulated in an interference model framework, and then a dynamic control strategy is developed for efficient rate assignment. In the first step, the controller is designed for the special case when the number of users in the network is fixed. Then, the minimum time required for a dynamic network (where the number of users is subject to change) to achieve a desired performance is obtained. The simulation results are presented to elucidate the effectiveness of the proposed approach.

Energy and time efficient formation reconfiguration strategies

Energy-efficient and time-efficient reconfiguration strategies for formation flying of autonomous agents are presented. It is assumed that a finite set of possible formations is given, and that the probability of each formation in this set is known a priori. The idea is to move the agents to floating stations in the idle time, i.e. the time between the accomplishment of the last reconfiguration task and the issuance of the next reconfiguration command, to minimize the expected value of the energy consumption or reconfiguration time. In the energy-efficient strategy, the position of each floating station is derived as a function of the agents current position, and the weighted center of gravity of the set of possible positions for that agent. In the time-efficient strategy, on the other hand, it turns out that the problem of finding the position of the corresponding floating stations is non-convex. To address this issue, a method is provided to reduce the global minimum search space to a convex compact set. Consequently, a numerical procedure for finding an arbitrarily precise global minimum is proposed in this case. The effectiveness of the proposed strategies is illustrated via simulation.