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An approach to localization scheme of wireless sensor networks based on artificial neural networks and Genetic algorithms

An approach to localization scheme of wireless sensor networ...

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Annual IEEE Northeast workshop on Circuits and Systems (NEWCAS)

作者： Stephan H. Chagas João B. Martins Leonardo L. de Oliveira UFSM PPGI Santa Maria Brazil UFSM GMICRO Santa Maria Brazil

Localization of nodes in wireless sensor networks without the use of GPS is important for applications such as military surveillance, environmental monitoring, robotics, domotics, animal tracking, and many others. Low cost and energy efficient sensors require methods that compute their position using indirect information such as RSSI (Received Signal Strength Indicator). This work presents an artificial neural networks (ANNs) approach to localization in wireless sensor networks through the adjustment of the ANNs structures using Genetic algorithms. A population of feedforward ANNs containing their structure in a genetic code is evolved during 20 generations. Each individual is evaluated through the training of the artificial neural network and further calculation of its root mean square error for all the testing set. The RSSI measurements were used as the artificial neural networks inputs to localize the nodes. The approach was tested using the MATLAB-based Probabilistic Wireless Network Simulator (Prowler) to collect the artificial neural networks input data, under simulated static indoor network environment of 26×26 meters with 8 anchor nodes, i.e., nodes with awareness of their positions. The MATLAB's genetic algorithms and artificial neural networks toolboxes were used. Results using the best artificial neural network structure found after optimization had a root mean square error of 0.41 meters, a maximum error of 1.07 meters and a minimum error of 0.014 meters.

关键词： Wireless sensor networks Sensors Artificial neural networks Training optimization Biological neural networks

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optimization of sparse matrix redistribution on multicomputers

Optimization of sparse matrix redistribution on multicompute...

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international Conference on Parallel Processing workshops (ICPPW)

作者： Ching-Hsien Hsu Department of Electrical Engineering Nan Kai College Nantou Taiwan

In many scientific applications, dynamic data redistribution of sparse matrices is used to enhance the performance of SPMD programs. Since the redistribution is performed at runtime, it is critical to the performance of a parallel program. We present a method which aims to improve the efficiency of block-cyclic data redistribution of sparse matrices. The main idea of the proposed technique is first to develop closed forms for generating the vector index set of each source/destination processor. Based on the vector index set and the non-zero structure of sparse matrices, two efficient algorithms, vector2message (v2m) and message2vector (m2v) can be derived. The v2m algorithm is used to extract non-zero elements from the source matrix and packs them into messages while m2v is used to unpack messages and construct the destination matrix. A theoretical model to analyze the performance of the proposed technique is also presented in the paper. Our method is compared to a dense redistribution strategy and the histogram method on an IBM SP2 parallel machine. The experimental results show that our techniques can efficiently perform sparse matrix data redistribution.

关键词： Sparse matrices Runtime Costs Data mining Educational institutions Data communication Performance analysis Scattering Histograms Parallel machines

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Improving the Partial Product Tree Compression on Signed Radix-2m Parallel Multipliers

Improving the Partial Product Tree Compression on Signed Rad...

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Annual IEEE Northeast workshop on Circuits and Systems (NEWCAS)

作者： Leandro M. G. Rocha Morgana Macedo Guilherme Paim Eduardo Costa Sergio Bampi Graduate Program in Microelectronics (PGMicro) - Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Graduate Program on Electronic Engineering and Computing - Catholic University of Pelotas (UCPel) Pelotas Brazil

ISBN: (数字)9781728170442

ISBN: (纸本)9781728170459

Arithmetic operations are intrinsic to any embedded devices, and they usually have a significant impact on the circuit speed, area, and power consumption. applications like video processing, digital signal processing, machine learning, among others, rely heavily on multipliers to execute their algorithms. Radix-2 m multipliers have been reported as one of the most power-efficient circuits. However, their architecture has not been explored nor optimized to improve the circuit quality. This work proposed two sign extension optimization techniques for these multipliers, aiming for better power efficiency and a smaller area. The baseline radix-4 (m=2) multiplier and its optimized versions were synthesized in a commercial 65nm technology to evaluate their performance. Results show that the optimized versions achieve power efficiency gains from 16.4% up to 78.6%, with circuit area reduction up to 49.2%.

关键词： Adders optimization Power dissipation Computer architecture Digital signal processing Signal processing algorithms Standards

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FPGA Implementation of Genetic Algorithm-Driven Commutation for H-Bridge Inverters

FPGA Implementation of Genetic Algorithm-Driven Commutation ...

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IEEE international Autumn Meeting on Power, Electronics and Computing (ROPEC)

作者： Cristian Sámano Adolfo R. Lopez José M. Sosa Gerardo Vazquez-Guzman Susana Estefany De León Aldaco Jesus Aguayo-Alquicira Felipe J. Torres Electronics Division TecNM/ITS de Irapuato Irapuato Mexico Electronics Department TecNM/CENIDET Cuernavaca Mexico Mechanics Department DICIS Universidad de Guanajuato Salamanca Mexico

ISBN: (数字)9798331530525

ISBN: (纸本)9798331530532

This paper presents the implementations of a commutation sequence for a five and seven-level cascaded H-bridge multilevel inverter (CHBMLI) using a Field Programmable Gate Array (FPGA). The switching angles were calculated using a Genetic Algorithm (GA) to minimize the Total Harmonic Distortion (THD) in the output. The versatility and efficiency of the CHBMLI inverters are highlighted due to their modular configuration, which allows for generating high-fidelity output voltages and minimizing harmonics in the output signal. The fundamental frequency switching modulation technique generates the required output voltages. The FPGA implementation, carried out in VHDL, achieved THD values of 15.4% and 10.4% for the 5-level and 7-level inverters respectively, closely matching the theoretical values. The capability of FPGAs to handle the generation of control sequences for each voltage level is demonstrated with a laboratory prototype. These results demonstrate the effectiveness of the proposed approach, offering a viable and efficient solution for applications in renewable energy systems and motor control. Future work could explore further optimizations and extensions of this method to even more complex inverter configurations.

关键词： VHDL Commutation Switches multilevel inverters Inverters Voltage control Field programmable gate arrays Power harmonic filters optimization Genetic algorithms

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Optimized Octtree Datastructure and Access Methods for 3D Mapping

Optimized Octtree Datastructure and Access Methods for 3D Ma...

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IEEE international workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Jann Poppinga Max Pfingsthorn Soren Schwertfeger Kaustubh Pathak Andreas Birk School of Engineering and Science Electrical Engineering and Computer Science (EECS) Jacobs University Bremen Bremen Germany

3D maps are becoming increasingly important for robots operating in real world scenarios. As occupancy grids are a popular standard in 2D mapping, it is a natural choice to extend them to spatial representation in 3D. But this approach suffers from large memory requirements that render 3D grids unfeasible for realistic mapping applications. A well-known alternative is quadtrees in 2D, respectively octtrees for 3D, where cells that contain identical information are collapsed into a single node in a tree. But octtrees only allow relative slow access to the spatial information stored in them. Here, a very efficient implementation of an octtree is presented. It is based on technical optimizations as well as newly introduced heuristics like the exploitation of typical access patterns. It is shown that the optimizations are indeed beneficial through experiments with real world 3D sensor data. In addition to basic access methods, a very fast nearest neighbor operation -as needed for example for registration in SLAM or map merging algorithms -for octtrees is presented. It is shown in experiments with real world data that this nearest neighbor operation outperforms a comparable operation on occupancy grids by far.

关键词： optimization methods Robot sensing systems Data security Nearest neighbor searches Jacobian matrices Simultaneous localization and mapping Merging Safety Mobile robots Conferences

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A Systemic Strategy for Tuning Intra-node Collective Communication on Multicore Systems

A Systemic Strategy for Tuning Intra-node Collective Communi...

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Japan-China Joint workshop on Frontier of Computer Science and Technology (FCST)

作者： Zhiqiang Liu Junqiang Song Kaijun Ren Fen Xu Xiaoling Qu College of Computer National University of Defense Technology Changsha Hunan China China Aerodynamics Research and Development Center Mianyang Sichuan China

In HPC domain, a majority of applications build on MPI and employ collective operations in their communication kernels. Improving the performance of collectives has been long term focused by a lot of work. Recently, in the optimization work of collectives on multi-core clusters, hierarchical algorithm designs are remark-able. This kind of algorithms can greatly reduce the inter-node traffic but increase the intra-node traffic load at the same time. Meanwhile, in hierarchical collectives, the part of intra-node collectives take more and more time while the number of cores in each node keeps growing. Improving the performance of intra-node collectives is critical to the holistic performance. However, on multi-cores, the factor of process affinity greatly impacts the performance of an intra-node collective. This peculiarity challenges us how to improve the overall performance of intra-node collectives. Towards this problem, in this paper, we propose a novel and systemic strategy for tuning the performance of intra-node collectives. As illustrative examples, we have implemented our strategy on a dual-socket Intel Clovertown platform and successfully tuned the performance of Broadcast and Allgather up to 14% and 52% improvement together.

关键词： Multicore processing Broadcasting Algorithm design and analysis Telecommunication traffic Kernel Clustering algorithms Computer science Educational institutions Application software Design optimization

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Evolving Intelligent Systems: Methods, Learning, & applications

Evolving Intelligent Systems: Methods, Learning, & Applicati...

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international workshop on Genetic and Evolving Systems, GEFS

作者： Nikola Kasabov Dimitar Filev Discovery Research Institute Auckland University of Technology Auckland New Zealand Intelligent Control & Information Systems Ford Research and Advanced Engineering Center Dearborn MI USA

The basic concept, formulation, background, and a panoramic view over the recent research results and open problems in the newly emerging area of Evolving Intelligent Systems are summarized in this short communication. Intelligent systems can be defined as systems that incorporate some form of reasoning that is typical for humans. Fuzzy Systems are well known for being able to formalize human knowledge that still separates humans from machines. Artificial Neural Networks have proven to be a useful form of parallel processing of information that employs principles from the organization of the brain. Finally, the evolution is a phenomenon that was initially used to solve optimization problems inspired by the progress in Genetic algorithms, Evolutionary Computing, and Genetic Programming. These types of evolutionary algorithms are mimicking the natural selection that takes place in populations of living creatures over generations. More recently, the evolution of individual systems within their life-span (self-organization, learning through experience, and self-developing) has attracted attention. These systems called `evolving' came as a result of the research on practical intelligent systems and on-line learning algorithms that are capable of extracting knowledge from data and performing a higher level adaptation of model structure as well as model parameters. Evolving systems can also be considered an extension of the multi-model concept known from the control theory, and of the on-line identification of fuzzy rule-based models. They can also be regarded as an extension of the methods for on-line learning neural networks with flexible structure that can grow and shrink.

关键词： Intelligent systems Humans Artificial intelligence Learning systems Fuzzy systems Artificial neural networks Parallel processing Genetic algorithms Genetic programming Evolutionary computation

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Assessing the impact of rainfall on system bandwidth for broadband fixed wireless applications

Assessing the impact of rainfall on system bandwidth for bro...

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Advanced international Conference on Telecommunications (AICT)

作者： S. Walsh E. Garcia S. Sezer Northern Ireland Science Park ECIT Queen''s University Belfast Belfast UK

Due to the presence of location dependent channel errors on wireless links, many wireless scheduling algorithms have been proposed which aim to provide efficient distribution of resources and fair allocation of available bandwidth to flows. Traditionally, these algorithms have adopted a two state model to represent the bandwidth of individual wireless channels, i.e., channels can be in a 'good' state or in a 'bad' state. In actual fact, the bandwidth of each channel depends on the adaptive techniques employed by the wireless system (e.g., coding and modulation). The paper considers different levels of rainfall and examines the impact of these levels in conjunction with suitable adaptive mechanisms on the available system bandwidth. A wireless link bandwidth model is presented which shows an accurate depiction of bandwidth variations to be used for design, optimization and benchmarking of wireless network schedulers. Knowledge of the link bandwidth is crucial for an intelligent scheduling algorithm since the scheduler must know how much bandwidth is available in order to perform fair reallocation.

关键词： Bandwidth Quality of service Scheduling algorithm Job shop scheduling WiMAX Programmable control Adaptive control Degradation Resource management Wireless networks

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Conditional and Composite Temporal Constraints with Preferences

Conditional and Composite Temporal Constraints with Preferen...

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international workshop on Temporal Representation and Reasoning (TIME)

作者： M. Mouhoub A. Sukpan Department of Computer Science University of Regina Regina Canada

Preferences in temporal problems are common but significant in many real world applications. In this paper, we extend our temporal reasoning framework, managing numeric and symbolic information, in order to handle preferences. Unlike the existing models managing single temporal preferences, ours supports four types of preferences, namely: numeric and symbolic temporal preferences, composite preferences and conditional preferences. This offers more expressive power in representing a wide variety of temporal constraint problems. The preferences are considered here as a set of soft constraints using a c-semiring structure with combination and projection operators. Solving temporal constraint problems with preferences consists of finding a solution satisfying all the temporal constraints while optimizing the preference values. This is handled by a variant of the branch and bound algorithm, we propose in this paper, and where constraint propagation is used to improve the time efficiency. Preliminary tests, we conducted on randomly generated temporal constraint problems with preferences, favor the forward checking principle as a constraint propagation strategy

关键词： Computer science Application software Constraint optimization Testing Approximation methods Stochastic systems Approximation algorithms

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Texture image classification based on support vector machine and bat algorithm

Texture image classification based on support vector machine...

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IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Zhiwei Ye Lie Ma Mingwei Wang Hongwei Chen Wei Zhao Beijing Key Laboratory of Urban Spatial Information Engineering Beijing China School of Computer Science Hubei University of Technology China

ISBN: (纸本)9781467383622

Texture is the vital feature for remote sensing image classification, however, it is hard to be described and recognized by computer vision. As a result, lots of approaches have been presented to identify texture image. Among these methods, support vector machine (SVM) is the most successfully used one, which takes advantages of avoiding local optimum, conquering dimension disaster with small samples. Nevertheless, the selection of the kernel function parameter and error penalty factor has impact on the precision of SVM notably. Some methods have been put forward to learn good parameters for SVM. However, the traditional tuning methods may be inefficient or not robust. Hence, a novel meta-heuristic-bat algorithm is suggested to acquire the optimal parameters for SVM in the paper. In final, experimental results on actual remote sensing texture images manifest that the proposed approach is robust, it is able to distinguish different texture images with high accuracy.

关键词： Support vector machines optimization Image classification Remote sensing Classification algorithms Kernel Sociology

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