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Samovar: An evaluation framework for real time applications deployment over WSANs
, 2010
"... Wireless Sensor and Actuator Networks (WSANs) combine sensors and actuators interconnected by wireless networks in order to perform distributed sensing and acting tasks. Closedloop controllers can therefore be deployed on WSANs; such systems have to meet specific requirements in terms of performanc ..."
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Wireless Sensor and Actuator Networks (WSANs) combine sensors and actuators interconnected by wireless networks in order to perform distributed sensing and acting tasks. Closedloop controllers can therefore be deployed on WSANs; such systems have to meet specific requirements in terms of performance, dependability, energy and cost which raises great challenges due to the unreliability of wireless communications. A way to ensure that a system meets the required properties is to model it and go through its analysis. Building a model requires both deep knowledge on the system as well as on the used framework. Therefore there is a need for frameworks wellsuited to the targeted systems and to the properties to verify. We propose an approach meeting these conditions and a simulation framework, Samovar, based on Matlab / Simulink, allowing the modeling of the network protocols (Mac and routing services) and the resources sharing policy thanks to the TrueTime toolbox. Several classes of components (application, nodes, networks and middleware) and a clear semantics for their composition are identified. Furthermore, the design of Samovar was also driven by the need to transfer easily software components model between the concrete systems and its simulated model. The modeling and simulation method as well as the Samovar framework are illustrated on a Pursuit Evasion Game. 1
Classifying the Heterogeneous MultiRobot Online Search Problem into Quadratic Time Competitive Complexity Class
"... Abstract — We explore the problem where a group of robots with different velocities search for a target in an unbounded unknown environment. The target position is unknown, hence, an online search algorithm is developed. The HMRSTM algorithm (Heterogeneous MultiRobot Search Time Multiplication), ..."
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Abstract — We explore the problem where a group of robots with different velocities search for a target in an unbounded unknown environment. The target position is unknown, hence, an online search algorithm is developed. The HMRSTM algorithm (Heterogeneous MultiRobot Search Time Multiplication), launches a group of n robots from a common starting location to search for the target. The robots are assigned to search inside a series of concentric discs with increasing radii. Each robot is assigned to search inside a disc and when completing the search inside this disc without finding the target, the robot is assigned to search in the next unoccupied disc. We prove that every algorithm that solves this search problem must have at least a quadratic time competitive complexity and prove that the HMRSTM algorithm’s complexity is also quadratic. Hence, we obtain both an upper and lower bound on the time competitive complexity of the search problem. Consequently, HMRSTM is proved to be optimal. Simulations in various environments show that the average case performance of HMRSTM is superior to that of homogeneous multirobot and single robot algorithms. In depth simulation analyses evaluated the effect of several other parameters such as the initial disc search time, the distribution of the velocities, the number of robots and the position of the target. I.
A Wireless Sensor Network Localization Method Based on Dynamic Path Loss Exponent
"... path loss exponent; positional accuracy Abstract. The path loss exponent shows the effect of space environment on the RF signals in wireless communication model. In most RSSI based location method the path loss exponent is assigned a fixed empirical value which can not reflect the actual environment ..."
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path loss exponent; positional accuracy Abstract. The path loss exponent shows the effect of space environment on the RF signals in wireless communication model. In most RSSI based location method the path loss exponent is assigned a fixed empirical value which can not reflect the actual environmental impact of the wireless signal, which lead to low position accuracy and considerable positioning error. Aiming at some complex and rapidly changing environment a path loss exponent dynamic acquired algorithm is proposed, which can calculate the actual path loss exponent with the distance and the RSSI value information between adjacent beacon nodes. On basis of the path loss exponent dynamic acquired algorithm a path loss exponent dynamic acquired based localization algorithm is proposed which can estimate the blind node position with the actual path loss exponent, and can improve the adaptability to the environment of the RSSI location algorithm. The simulation shows that the positioning accuracy of proposed method is significantly improved and the effect of proposed method is more precise than the common RSSI method under the same environment.
A Novel Quadrilateral Projection Positioning Algorithm to Improve Ranging Accuracy of High Speed Stackers*
"... Abstract. High speed stackers are the critical equipments for automated storage/retrieval systems to improve efficiency and throughput. And the positioning technique is the key to speed regulating. The low cost and easy installation indoor positioning of wireless sensor network is applied in this si ..."
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Abstract. High speed stackers are the critical equipments for automated storage/retrieval systems to improve efficiency and throughput. And the positioning technique is the key to speed regulating. The low cost and easy installation indoor positioning of wireless sensor network is applied in this situation. A novel quadrilateral projection algorithm taken advantage of the linear moving of stackers is proposed to reduce the complexity of the algorithm and improve ranging accuracy of positioning.