A new gaussian elimination-based algorithm for parallel solution of linear equations

AbstractIn this paper, a variant of Gaussian Elimination (GE) called Successive Gaussian Elimination (SGE) algorithm for parallel solution of linear equations is presented. Unlike the conventional GE algorithm, the SGE algorithm does not have a separate back substitution phase, which requires O(N) steps using O(N) processors or O(log22 N) steps using O(N3) processors, for solving a system of linear algebraic equations. It replaces the back substitution phase by only one step division and possesses numerical stability through partial pivoting. Further, in this paper, the SGE algorithm is shown to produce the diagonal form in the same amount of parallel time required for producing triangular form using the conventional parallel GE algorithm. Finally, the effectiveness of the SGE algorithm is demonstrated by studying its performance on a hypercube multiprocessor system

Estimation of the seismic response of buildings and the effect of different scaling methods for ground motion

The Seismic design code of Canada is changing rapidly to accommodate the needs of the future generation of buildings for management of earthquake hazard mitigation. In this context the recent advancement in Earthquake Technology and Structural Engineering has emphasized on the need for a better methodology and in-depth investigation into the area of structural performance evaluation in order to ensure that structures designed for the areas of high and moderate seismic hazard to the expected standards and meet the objective of life safety and collapse prevention in a real life scenario. In order to ensure the above performance objectives for a building structure, it is necessary to estimate its capacity with respect to the demand, and the dynamic response corresponding to the design levels of earthquakes. The research carried out here aims to investigate: (i) the earthquake demand and capacity profiles of a set of set of moment frame buildings designed according to the latest version of the National Building Code of Canada, and (ii) the effect of scaling and spectral matching techniques commonly applied to ground motions on the seismic demand parameters determined using the dynamic time history analysis. A set of buildings with steel moment resisting frames of 5, 10, 15, 20 stories in height and located in Vancouver area of Canada have been considered in this study. An extensive review has been conducted to determine the existing methods for performance-based design and the techniques available to selecting and scaling suite of earthquake records to perform a fully non-linear dynamic analysis in time domain. Based on that, a range of scaling techniques including linear scaling techniques, and spectral matching technique have been considered for an ensemble of recorded ground motion time histories. In addition a set of artificially generated spectrum-compatible earthquake records are also considered. The static pushover analysis has been carried out and the corresponding capacity curves have been obtained and interpreted with commonly used performance-based design methods. It is observed that all the methods considered here confirm that the existing design based on the code procedure is adequate and conservative. The pushover curves are also compared to the results obtained from the Time history analysis to determine the performance achievements of the buildings. The interstory drift obtained from the time history analysis using different scaling methods show a uniform and consistent pattern of deformation in low rise to medium rise frames whereas dispersion greater dispersion of the results has been observed in tall buildings. Other response quantities such as the lateral drift, base shear and bending moment show similar patterns. Based on the results from the research it is suggested to use the artificial records if site specific real ground motion records are unavailable. The scope for further research lies in exploring ways to the possibility of new scaling techniques that can control the dispersion in the response more effectivel

Joint energy and throughput optimization for MEC-enabled multi-UAV IoRT networks

In this paper, we study an Unmanned Aerial Vehicle (UAV) enabled Mobile Edge Computing (MEC) service provisioning to the Internet of Remote Things (IoRT) devices spread randomly on the ground in a remote area. The data generated by the IoRT devices is collected by the UAVs, which immediately relay the data collected to an MEC device installed on the ground at a nearby location. The MEC device receives the data from the UAVs, and sends the results back to the UAVs, which in turn relay them to IoRT devices. We aim to minimize the energy consumption by the IoRT devices and the UAVs, while maximizing the system throughput subject to bandwidth, power, information-causality, and UAVs’ trajectory constraints. We formulate the problem as a Mixed Integer Non Linear Programming problem, which is a complex and non-convex optimization problem. To make the problem tractable, we use variable relaxation. We further develop an iterative algorithm based on Block Coordinate Descent method, to jointly optimize the connection scheduling, power control, bit transmission scheduling, bandwidth allocation, and trajectories of the UAVs. Numerical results demonstrate the convergence of the algorithm and superiority of the proposed model with respect to conventional methods. Our proposed system model of placing MEC at ground shows 9% improvement in energy consumption when compared to carrying out computations at MEC carried by UAV and a 99% improvement when compared to placing MEC at the satellite. The proposed system model shows a 0.2% lower system throughput on average, compared to placing MEC at UAV, which is tolerable considering gains in terms of energy consumption

Estimation of Seismic response of buildings and the effect of different scaling methods for ground motion

The Seismic design code of Canada is changing rapidly to accommodate the needs of the future generation of buildings for management of earthquake hazard mitigation. In this context the recent advancement in Earthquake Technology and Structural Engineering has emphasized on the need for a better methodology and in-depth investigation into the area of structural performance evaluation in order to ensure that structures designed for the areas of high and moderate seismic hazard to the expected standards and meet the objective of life safety and collapse prevention in a real life scenario. In order to ensure the above performance objectives for a building structure, it is necessary to estimate its capacity with respect to the demand, and the dynamic response corresponding to the design levels of earthquakes. The research carried out here aims to investigate: (i) the earthquake demand and capacity profiles of a set of set of moment frame buildings designed according to the latest version of the National Building Code of Canada, and (ii) the effect of scaling and spectral matching techniques commonly applied to ground motions on the seismic demand parameters determined using the dynamic time history analysis. A set of buildings with steel moment resisting frames of 5, 10, 15, 20 stories in height and located in Vancouver area of Canada have been considered in this study. An extensive review has been conducted to determine the existing methods for performance-based design and the techniques available to selecting and scaling suite of earthquake records to perform a fully non-linear dynamic analysis in time domain. Based on that, a range of scaling techniques including linear scaling techniques, and spectral matching technique have been considered for an ensemble of recorded ground motion time histories. In addition a set of artificially generated spectrum-compatible earthquake records are also considered. The static pushover analysis has been carried out and the corresponding capacity curves have been obtained and interpreted with commonly used performance-based design methods. It is observed that all the methods considered here confirm that the existing design based on the code procedure is adequate and conservative. The pushover curves are also compared to the results obtained from the Time history analysis to determine the performance achievements of the buildings. The interstory drift obtained from the time history analysis using different scaling methods show a uniform and consistent pattern of deformation in low rise to medium rise frames whereas dispersion greater dispersion of the results has been observed in tall buildings. Other response quantities such as the lateral drift, base shear and bending moment show similar patterns. Based on the results from the research it is suggested to use the artificial records if site specific real ground motion records are unavailable. The scope for further research lies in exploring ways to the possibility of new scaling techniques that can control the dispersion in the response more effectively

CalibNet: Geometrically Supervised Extrinsic Calibration using 3D Spatial Transformer Networks

3D LiDARs and 2D cameras are increasingly being used alongside each other in sensor rigs for perception tasks. Before these sensors can be used to gather meaningful data, however, their extrinsics (and intrinsics) need to be accurately calibrated, as the performance of the sensor rig is extremely sensitive to these calibration parameters. A vast majority of existing calibration techniques require significant amounts of data and/or calibration targets and human effort, severely impacting their applicability in large-scale production systems. We address this gap with CalibNet: a self-supervised deep network capable of automatically estimating the 6-DoF rigid body transformation between a 3D LiDAR and a 2D camera in real-time. CalibNet alleviates the need for calibration targets, thereby resulting in significant savings in calibration efforts. During training, the network only takes as input a LiDAR point cloud, the corresponding monocular image, and the camera calibration matrix K. At train time, we do not impose direct supervision (i.e., we do not directly regress to the calibration parameters, for example). Instead, we train the network to predict calibration parameters that maximize the geometric and photometric consistency of the input images and point clouds. CalibNet learns to iteratively solve the underlying geometric problem and accurately predicts extrinsic calibration parameters for a wide range of mis-calibrations, without requiring retraining or domain adaptation. The project page is hosted at https://epiception.github.io/CalibNetComment: Appeared in the proccedings of the IEEE International Conference on Intelligent Robots and Systems (IROS) 201

Improving DTN Routing Performance Using Many-to-Many Communication: A Performance Modeling Study

Abstract-Delay-Tolerant Networks (DTNs) have emerged as an exciting research area with a number of useful applications. Most of these applications would benefit greatly by a reduction in the message delivery delay experienced in the network. The delay performance of DTNs is adversely affected by contention, especially severe in the presence of higher traffic rates and node densities. Many-to-Many (M2M) communication can handle this contention much better than traditional oneto-one communication employing CSMA. In this paper, for the first time, we analytically model the expected delivery delay of a DTN employing epidemic routing and M2M communication. The accuracy of our model is demonstrated by matching the analytical results against those from simulations. We also show using simulations that M2M communication significantly improves the delay performance (with respect to one-to-one CSMA) for highcontention scenarios. We believe our work will enable the effective application of M2M communication to reduce delivery delays in DTNs