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IEEE Aerospace Conference (AeroConf)

作者： Carden, Joshua Deacon, Shaun Kessler, Paul Speth, Paul Analyt Mech Associates Inc 21 Enterprise Pkwy Suite 300 Hampton VA 23666 USA 1 N Dryden St Hampton VA 23681 USA

ISBN: (纸本)9781728174365

With the rapid growth in the capabilities of smaller satellites, satellite architectures that replace a single, extremely capable spacecraft with multiple, cheaper ones are gaining in popularity. Unfortunately, the orbit design process for constellations can be significantly more involved, especially when the relative placement of the individual spacecraft within the constellation is not constrained by mission and/or science objectives. Optimizing a satellite constellation in the presence of multiple, competing objectives is a highly complex problem to which many traditional mathematical optimization methods cannot be applied and few tools exist to help mission designers search for promising candidate mission designs. The Generation-based Evolutionary Tool for the optimization of Constellations (GenETOC) has been created to search for near-optimal constellation design options. GenETOC combines a modified version of the Non-dominated Sorting Genetic Algorithm II (NSGA II) with STK Components libraries (a 3rd *** package created by Analytical Graphics Inc.) to create a framework that enables a mission designer to generate a simulation that models the design problem and obtain a family of potential, near-optimal solutions that can be investigated more in detail. GenETOC was developed in C# using the .NET framework with Windows Presentation Foundation (WPF) serving as the framework from which to create the graphical user interface (GUI). GenETOC user inputs can be categorized into three major data components: definition of the problem (areas of interest, satellite decision parameters, and sensor configurations), definition of performance objectives, and specification of the genetic algorithm (GA) parameters. In the problem definition component, the user is prompted to define the areas of interest against which the performance metrics will be computed, define the sensor parameters and attach them to specific spacecraft, select which satellite orbital parameters wil

关键词： orbit constellations coverage optimization revisit optimization genetic algorithm

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An Improved Method of WSN coverage Based on Enhanced PSO Algorithm 8

An Improved Method of WSN Coverage Based on Enhanced PSO Alg...

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IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

作者： Kong, Hongshan Yu, Bin Zhengzhou Inst Sci & Technol Zhengzhou Henan Peoples R China

ISBN: (纸本)9781538681787

Aimed at the unreasonable distribution of sensors' random deployment, an improved method of WSN coverage based on enhanced PSO algorithm is presented. The dynamic adjustment of inertia coefficient and mutation operator are introduced to improve the standard PSO algorithm, which can improve the global convergence speed and particle diversity, and can avoid falling into local convergence. The enhanced PSO algorithm is applied to the optimization of WSN coverage, which can increase the maximum coverage. According to the simulation results, compared with PSO in coverage, the enhanced algorithm is superior.

关键词： Wireless sensor Network Particle swarm optimization coverage optimization coverage rate

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LTE optimization Engineering Handbook 1.

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2017年

作者： Xincheng Zhang

ISBN: (数字)9781119158981

ISBN: (纸本)9781119158974

A comprehensive resource containing the operating principles and key insights of LTE networks performance optimization LTE optimization Engineering Handbook is a comprehensive reference that describes the most current technologies and optimization principles for LTE networks. The text offers an introduction to the basics of LTE architecture, services and technologies and includes details on the key principles and methods of LTE optimization and its parameters. In addition, the author clarifies different optimization aspects such as wireless channel optimization, data optimization, CSFB, VoLTE, and video optimization. With the ubiquitous usage and increased development of mobile networks and smart devices, LTE is the 4G network that will be the only mainstream technology in the current mobile communication system and in the near future. Designed for use by researchers, engineers and operators working in the field of mobile communications and written by a noted engineer and experienced researcher, the LTE optimization Engineering Handbook provides an essential guide that: Discusses the latest optimization engineering technologies of LTE networks and explores their implementation Features the latest and most industrially relevant applications, such as VoLTE and HetNets Includes a wealth of detailed scenarios and optimization real-world case studies Professionals in the field will find the LTE optimization Engineering Handbook to be their go-to reference that includes a thorough and complete examination of LTE networks, their operating principles, and the most current information to performance optimization.

关键词： Guide to LTE networks resource to LTE networks handbook of LTE networks principles of LTE networks approaches to LTE networks performance optimization of LTE networks working with LTE networks professional guide to LTE networks comprehensive review of LTE networks understanding LTE networks technical guide to LTE networks LTE Basement LTE optimization and principle and method coverage optimization Capacity optimization Internal interference optimization Drop call optimization Latency optimization Mobility optimization CS fall back optimization VoLTE optimization PRACH optimization Physical cell ID optimization Tracking areas optimization Uplink Signal optimization HetNet optimization QoE evaluation and optimization strategy Signalling based optimization LTE optimization Engineering Handbook Xincheng Zhang

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optimization of piezoelectric cantilever energy harvesters including non-linear effects

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SMART MATERIALS AND STRUCTURES 2014年第8期23卷

作者： Patel, R. McWilliam, S. Popov, A. A. Univ Nottingham Dept Mech Mat & Mfg Engn Nottingham NG7 2RD England Univ Nottingham Dept Mech Mat & Mfg Engn Semenyih Malaysia

This paper proposes a versatile non-linear model for predicting piezoelectric energy harvester performance. The presented model includes (i) material non-linearity, for both substrate and piezoelectric layers, and (ii) geometric non-linearity incorporated by assuming inextensibility and accurately representing beam curvature. The addition of a sub-model, which utilizes the transfer matrix method to predict eigenfrequencies and eigenvectors for segmented beams, allows for accurate optimization of piezoelectric layer coverage. A validation of the overall theoretical model is performed through experimental testing on both uniform and non-uniform samples manufactured in-house. For the harvester composition used in this work, the magnitude of material non-linearity exhibited by the piezoelectric layer is 35 times greater than that of the substrate layer. It is also observed that material non-linearity, responsible for reductions in resonant frequency with increases in base acceleration, is dominant over geometric non-linearity for standard piezoelectric harvesting devices. Finally, over the tested range, energy loss due to damping is found to increase in a quasi-linear fashion with base acceleration. During an optimization study on piezoelectric layer coverage, results from the developed model were compared with those from a linear model. Unbiased comparisons between harvesters were realized by using devices with identical natural frequencies-created by adjusting the device substrate thickness. Results from three studies, each with a different assumption on mechanical damping variations, are presented. Findings showed that, depending on damping variation, a non-linear model is essential for such optimization studies with each model predicting vastly differing optimum configurations.

关键词： energy harvesting piezoelectric beam geometric non-linearity material non-linearity coverage optimization mechanical damping

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Improved whale optimization algorithm and its application in heterogeneous wireless sensor networks

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2021年第5期17卷

作者： Yue, Yinggao You, Hairong Wang, Shuxin Cao, Li Wenzhou Univ Oujiang Coll Wenzhou 325035 Zhejiang Peoples R China Hubei Univ Arts & Sci Comp Sch Xiangyang Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang Peoples R China

Aiming at the problems of node redundancy and network cost increase in heterogeneous wireless sensor networks, this article proposes an improved whale optimization algorithm coverage optimization method. First, establish a mathematical model that balances node utilization, coverage, and energy consumption. Second, use the sine-cosine algorithm to improve the whale optimization algorithm and change the convergence factor of the original algorithm. The linear decrease is changed to the nonlinear decrease of the cosine form, which balances the global search and local search capabilities, and adds the inertial weight of the synchronous cosine form to improve the optimization accuracy and speed up the search speed. The improved whale optimization algorithm solves the heterogeneous wireless sensor network coverage optimization model and obtains the optimal coverage scheme. Simulation experiments show that the proposed method can effectively improve the network coverage effect, as well as the utilization rate of nodes, and reduce network cost consumption.

关键词： Heterogeneous wireless sensor networks whale optimization algorithm coverage optimization sine and cosine algorithm energy balance

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Boundary Reconstruction for Wireless Sensor Networks

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IEEE ACCESS 2024年 12卷 168445-168455页

作者： Sivadasan, Sreeram Govindan, Nagarajan Parakkat, Amal Dev Sathyabama Inst Sci & Technol Chennai 600119 India Inst Polytech Paris Telecom Paris LTCI F-91120 Palaiseau France

Wireless Sensor Networks (WSNs) are critical for various applications ranging from environment monitoring to industrial monitoring. The varying and continuously growing interest in this field demands an understanding of the sensor node distribution to ensure robustness and to improve resource utilization for data processing and decision making. In this paper, we focus on reconstructing the boundaries of a wireless sensor network, which also has a lot of applications in IoT and Robotics. As these sensor node locations can be considered as a set of points in the 2D plane, boundary detection of a WSN can be related to classical shape reconstruction problem in Computational Geometry. In this paper, we extend a simple and generic strategy for hole detection to a geometric solution for boundary/shape reconstruction. Furthermore, we introduce a simple and controllable heuristic algorithm to patch the coverage holes identified by our boundary reconstruction algorithm. Not only does this study improve the reliability of WSNs, but it also provides a useful tool for the extensive domain of computational geometry and shape analysis. Our different experiments show that the proposed reconstruction algorithm outperforms the existing state-of-the-art methods, and hole patching gives a simple and controllable solution for mobile node placement.

关键词： Shape measurement Wireless sensor networks Sensors Reconstruction algorithms Surveys Object recognition Mobile nodes Surveillance Smart cities Security Shape reconstruction Delaunay triangulation coverage hole detection dynamic node placement coverage optimization

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Titul Research on Wireless Network coverage for Transformation and Upgrading of Exhibition Management with Artificial Intelligence Technology

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APPLIED MATHEMATICS AND NONLINEAR SCIENCES 2023年

作者： Dou, Peilin Zheng, Guohua Shanghai Int Studies Univ Xianda Coll Econ & Humanities Shanghai 200080 Peoples R China Shanghai Xunmeng Informat Technol Co Ltd Shanghai 200050 Peoples R China

The rapid development of artificial intelligence and modern communication technology provides a powerful opportunity to realize the transformation, upgrading and high-quality development of exhibition management. To solve the optimal coverage problem of wireless network in the exhibition area, a new generation of artificial intelligence algorithm is introduced to propose a novel method for solving the network coverage problem based on Harris Hawk optimization (HHO) algorithm. From the perspective of maximizing coverage and minimizing coverage redundancy, the multi-objective coverage optimization problem of wireless network nodes is optimally extracted into a function and solved using the improved HHO (IHHO) algorithm. Through the simulation of the wireless network coverage in the exhibition area, the experimental results show that the comprehensive evaluation index score of the optimization algorithm reaches 98.03%, which is higher than the traditional particle swarm optimizer (PSO) and the standard HHO. The proposed IHHO algorithm can be effectively applied to the network coverage problem and has a greater advantage over the traditional optimization methods in terms of improving node coverage, and has great practicality.

关键词： Keyword Artificial intelligence exhibition management wireless network coverage optimization Harris Hawk optimization algorithm

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Hierarchic optimization for indoor application

Hierarchic optimization for indoor application

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European Conference on Antennas and Propagation

作者： Lajos Nagy Andrea Farkasvolgyi Department of Broadband Infocommunication and Electromagnetic Theory Budapest University of Technology and Economics Hungary

ISBN: (纸本)9781424447534

Recently there is a growing interest in providing and improving radio coverage for mobile phones and WLANs inside buildings. The need of such coverage appears mainly in office buildings, shopping malls, train stations where the subscriber density is very high. The cost of cellular systems and also the one of indoor wireless systems depend highly on the number of base stations required to achieve the desired coverage for a given level of field strength. This paper presents an approach in optimizing the indoor radio coverage using multiple access points for indoor environments. The Genetic Algorithm (GA) and Simulated Annealing (SA) are used to determine the optimal access point positions to achieve optimum coverage. Next a hierarchic optimization method is introduced and finally comparisons are made for the methods suggested.

关键词： WLAN Indoor wave propagation Heuristic optimization coverage optimization radio coverage BASE STATION CARRIER SYSTEM coverage access points wireless local area network (WLAN) cellular system multiple access Mobile phones field strength optimization method Railroad stations built structure Buildings optimal access

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Online Evolution of Femtocell coverage Algorithms Using Genetic Programming

Online Evolution of Femtocell Coverage Algorithms Using Gene...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

作者： Lester Ho Holger Claussen Davide Cherubini Bell Laboratories Alcatel-Lucent Blanchardstown Business & Technology Park Dublin 15 Ireland

ISBN: (纸本)9781467362337

The wide adoption of smartphones has resulted in an exponential increase in the demand for wireless data. To address this problem, operators have started deploying large numbers of small cells. In order to operate such small cell network cost-effectively they need to be able to intelligently optimize their configuration, which can be achieved by applying machine learning techniques such as genetic programming. The use of genetic programming has previously been used to derive joint coverage algorithms for a group of enterprise femtocells. However, the evolution of the algorithms was performed in an offline manner, on a pre-defined simulation model of the deployment scenario. In this paper, an approach to perform the evolution in an online manner using an automated model building process is presented. The model building process uses network traces as inputs to create a hierarchical Markov model that is shown to be able to capture the behavior of the femtocell network well. It is shown that the resulting environment model can effectively drive the on-line evolution of coverage optimization algorithms.

关键词： Femtocell coverage optimization online genetic programming model building

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