The Experts below are selected from a list of 1986 Experts worldwide ranked by ideXlab platform
Abdallah Shami - One of the best experts on this subject based on the ideXlab platform.
-
physical topology discovery scheme for wireless sensor networks using random walk process
Global Communications Conference, 2016Co-Authors: Tianqi Yu, Xianbin Wang, Abdallah ShamiAbstract:Wireless sensor networks (WSNs) are widely considered as the most important information gathering platform in enabling Internet of Things (IoT). In order to evolve the traditional WSNs for low-power and low-loss IoT applications, time slotted channel hopping (TSCH) MAC protocol has been proposed to tackle the single channel and inefficient medium access drawbacks through improved network topology awareness. However, the problem of maintaining the physical topology of a WSN at the server end remains unresolved. In this paper, we propose a novel physical topology discovery scheme for WSNs by exploitation of random walk process and iterative Multilateration localization algorithm. Explicitly, information specific to the sensor nodes, including IDs and neighbor tables, are collected in the random walk process. The physical topology is then reconstructed at the server end based on the collected information and the iterative Multilateration localization algorithm. Simulation results indicate that the average location offset between the established topology and the ground- truth topology can be as low as 1.26m.
-
GLOBECOM - Physical Topology Discovery Scheme for Wireless Sensor Networks Using Random Walk Process
2016 IEEE Global Communications Conference (GLOBECOM), 2016Co-Authors: Tianqi Yu, Xianbin Wang, Abdallah ShamiAbstract:Wireless sensor networks (WSNs) are widely considered as the most important information gathering platform in enabling Internet of Things (IoT). In order to evolve the traditional WSNs for low-power and low-loss IoT applications, time slotted channel hopping (TSCH) MAC protocol has been proposed to tackle the single channel and inefficient medium access drawbacks through improved network topology awareness. However, the problem of maintaining the physical topology of a WSN at the server end remains unresolved. In this paper, we propose a novel physical topology discovery scheme for WSNs by exploitation of random walk process and iterative Multilateration localization algorithm. Explicitly, information specific to the sensor nodes, including IDs and neighbor tables, are collected in the random walk process. The physical topology is then reconstructed at the server end based on the collected information and the iterative Multilateration localization algorithm. Simulation results indicate that the average location offset between the established topology and the ground- truth topology can be as low as 1.26m.
Tianqi Yu - One of the best experts on this subject based on the ideXlab platform.
-
physical topology discovery scheme for wireless sensor networks using random walk process
Global Communications Conference, 2016Co-Authors: Tianqi Yu, Xianbin Wang, Abdallah ShamiAbstract:Wireless sensor networks (WSNs) are widely considered as the most important information gathering platform in enabling Internet of Things (IoT). In order to evolve the traditional WSNs for low-power and low-loss IoT applications, time slotted channel hopping (TSCH) MAC protocol has been proposed to tackle the single channel and inefficient medium access drawbacks through improved network topology awareness. However, the problem of maintaining the physical topology of a WSN at the server end remains unresolved. In this paper, we propose a novel physical topology discovery scheme for WSNs by exploitation of random walk process and iterative Multilateration localization algorithm. Explicitly, information specific to the sensor nodes, including IDs and neighbor tables, are collected in the random walk process. The physical topology is then reconstructed at the server end based on the collected information and the iterative Multilateration localization algorithm. Simulation results indicate that the average location offset between the established topology and the ground- truth topology can be as low as 1.26m.
-
GLOBECOM - Physical Topology Discovery Scheme for Wireless Sensor Networks Using Random Walk Process
2016 IEEE Global Communications Conference (GLOBECOM), 2016Co-Authors: Tianqi Yu, Xianbin Wang, Abdallah ShamiAbstract:Wireless sensor networks (WSNs) are widely considered as the most important information gathering platform in enabling Internet of Things (IoT). In order to evolve the traditional WSNs for low-power and low-loss IoT applications, time slotted channel hopping (TSCH) MAC protocol has been proposed to tackle the single channel and inefficient medium access drawbacks through improved network topology awareness. However, the problem of maintaining the physical topology of a WSN at the server end remains unresolved. In this paper, we propose a novel physical topology discovery scheme for WSNs by exploitation of random walk process and iterative Multilateration localization algorithm. Explicitly, information specific to the sensor nodes, including IDs and neighbor tables, are collected in the random walk process. The physical topology is then reconstructed at the server end based on the collected information and the iterative Multilateration localization algorithm. Simulation results indicate that the average location offset between the established topology and the ground- truth topology can be as low as 1.26m.
Jean Michel Sprauel - One of the best experts on this subject based on the ideXlab platform.
-
Effects of number of digits in large-scale Multilateration
Precision Engineering, 2020Co-Authors: Jean Marc Linares, Santiago Arroyave-tobón, José Pires, Jean Michel SprauelAbstract:Since many years ago, Multilateration has been used in precision engineering notably in machine tool and coordinate measuring machine calibration. This technique needs, first, the use of laser trackers or tracking interferometers, and second, the use of nonlinear optimization algorithms to determine point coordinates. Research works have shown the influence of the experimental configuration on measure precision in Multilateration. However, the impact of floating-point precision in computations on large-scale Multilateration precision has not been addressed. In this work, the effects of numerical errors (rounding and cancellation effects) due to floating-point precision (number of digits) were studied. In order to evaluate these effects in large-scale Multilateration, a Multilateration measurement system was simulated. This protocol is illustrated with a case study where large distances (≤20 m) between pairs of target points were simulated. The results show that the use of multi-precision libraries is recommended to control the propagation of uncertainties during the Multilateration computation.
-
Measurement Parameters Optimized for Sequential Multilateration in Calibrating a Machine Tool with a DOE Method
Applied Sciences, 2016Co-Authors: Fabien Ezedine, Jean Marc Linares, Julien Chaves-jacob, Jean Michel SprauelAbstract:Improving volumetric error compensation is one of the machine tool user's key objectives. Smart compensation is bound to calibration accuracy. Calibration quality depends largely on its setup factors. An evaluation criterion is thus required to test the quality of the compensation deduced from these setup factors. The residual error map, which characterizes post-compensation machine errors, is therefore chosen and then needs to be evaluated. In this study, the translation axes of a machine tool were calibrated with a Multilateration tracking laser interferometer. In order to optimize such measurements, the residual error map was then characterized by two appliances: a laser interferometer and the tracking laser already employed for the calibration, using for that purpose the sequential Multilateration technique. This research work thus aimed to obtain a smart setup of parameters of machine tool calibration analyzing these two residual error maps through the Design Of Experiment (DOE) method. To achieve this goal, the first step was to define the setup parameters for calibrating a compact machine tool with a Multilateration tracking laser. The second step was to define both of the measurement processes that are employed to estimate the residual error map. The third step was to obtain the optimized setup parameters using the DOE method.
-
Measurement Parameters Optimized for Sequential Multilateration in Calibrating a Machine Tool with a DOE Method
Applied Sciences, 2016Co-Authors: Fabien Ezedine, Jean Marc Linares, Julien Chaves-jacob, Jean Michel SprauelAbstract:International audienceImproving volumetric error compensation is one of the machine tool user's key objectives. Smart compensation is bound to calibration accuracy. Calibration quality depends largely on its setup factors. An evaluation criterion is thus required to test the quality of the compensation deduced from these setup factors. The residual error map, which characterizes post-compensation machine errors, is therefore chosen and then needs to be evaluated. In this study, the translation axes of a machine tool were calibrated with a Multilateration tracking laser interferometer. In order to optimize such measurements, the residual error map was then characterized by two appliances: a laser interferometer and the tracking laser already employed for the calibration, using for that purpose the sequential Multilateration technique. This research work thus aimed to obtain a smart setup of parameters of machine tool calibration analyzing these two residual error maps through the Design Of Experiment (DOE) method. To achieve this goal, the first step was to define the setup parameters for calibrating a compact machine tool with a Multilateration tracking laser. The second step was to define both of the measurement processes that are employed to estimate the residual error map. The third step was to obtain the optimized setup parameters using the DOE method
Xianbin Wang - One of the best experts on this subject based on the ideXlab platform.
-
physical topology discovery scheme for wireless sensor networks using random walk process
Global Communications Conference, 2016Co-Authors: Tianqi Yu, Xianbin Wang, Abdallah ShamiAbstract:Wireless sensor networks (WSNs) are widely considered as the most important information gathering platform in enabling Internet of Things (IoT). In order to evolve the traditional WSNs for low-power and low-loss IoT applications, time slotted channel hopping (TSCH) MAC protocol has been proposed to tackle the single channel and inefficient medium access drawbacks through improved network topology awareness. However, the problem of maintaining the physical topology of a WSN at the server end remains unresolved. In this paper, we propose a novel physical topology discovery scheme for WSNs by exploitation of random walk process and iterative Multilateration localization algorithm. Explicitly, information specific to the sensor nodes, including IDs and neighbor tables, are collected in the random walk process. The physical topology is then reconstructed at the server end based on the collected information and the iterative Multilateration localization algorithm. Simulation results indicate that the average location offset between the established topology and the ground- truth topology can be as low as 1.26m.
-
GLOBECOM - Physical Topology Discovery Scheme for Wireless Sensor Networks Using Random Walk Process
2016 IEEE Global Communications Conference (GLOBECOM), 2016Co-Authors: Tianqi Yu, Xianbin Wang, Abdallah ShamiAbstract:Wireless sensor networks (WSNs) are widely considered as the most important information gathering platform in enabling Internet of Things (IoT). In order to evolve the traditional WSNs for low-power and low-loss IoT applications, time slotted channel hopping (TSCH) MAC protocol has been proposed to tackle the single channel and inefficient medium access drawbacks through improved network topology awareness. However, the problem of maintaining the physical topology of a WSN at the server end remains unresolved. In this paper, we propose a novel physical topology discovery scheme for WSNs by exploitation of random walk process and iterative Multilateration localization algorithm. Explicitly, information specific to the sensor nodes, including IDs and neighbor tables, are collected in the random walk process. The physical topology is then reconstructed at the server end based on the collected information and the iterative Multilateration localization algorithm. Simulation results indicate that the average location offset between the established topology and the ground- truth topology can be as low as 1.26m.
Aitor Olarra - One of the best experts on this subject based on the ideXlab platform.
-
integrated Multilateration for machine tool automatic verification
Cirp Annals-manufacturing Technology, 2018Co-Authors: Unai Mutilba, Jose A Yaguefabra, Eneko Gomezacedo, Gorka Kortaberria, Aitor OlarraAbstract:Abstract Multilateration based approaches are widely accepted as the most adequate solution for geometric characterisation of medium and large machine tools. However, its application, either in a sequential mode or in a simultaneous approach, leads to industrial limitations such as total time consumption or thermal drift that prevent an automatic calibration. This work presents an integrated Multilateration verification procedure where a tracking interferometer is directly attached to the manufacturing system spindle as a tool, which tackles several of the mentioned limitations. Results of both simulations and experimental tests show that levels of uncertainty in the range of micrometres can be guaranteed.