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IEEE International Conference on Communications in China (ICCC)

作者： Jiajun Wang Xingjian Ding Jianxiong Guo Zhiqing Tang Deying Li Faculty of Information Beijing University of Technology Beijing China Advanced Institute of Natural Sciences Beijing Normal University Zhuhai China School of Information Renmin University of China Beijing China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

With the continuous development of mobile networks and sensing devices, spatiotemporal crowdsourcing has gradually become a new intelligent sensing paradigm for data acquisition and sharing in the Industrial Internet of Things. How to reasonably allocate tasks to workers in a dynamic environment to maximize the platform utility has become a research hotspot. Many past works have made great efforts in this regard, but most of them only consider the long-term constraints of resources, and ignore the short-term ability constraints of workers to provide resources. In this paper, we consider a platform-centered online spatiotemporal crowdsourcing system, where mobile workers have long-term and short-term resource constraints, while the platform has a long-term budget constraint. We aim to find an online worker scheduling scheme to maximize the platform’s long-term utility without violating the constraints of workers and the platform. To address the problem, we first transform the long-term utility maximization problem into a real-time utility maximization problem by leveraging the Lyapunov optimization. Then, we design a centralized algorithm based on Markov approximation to solve the real-time optimization problem. Furthermore, we demonstrate that our proposed approach can achieve near-optimal performance for our problem. Finally, we evaluate our designs by numerical simulation experiments, and the results demonstrate the effectiveness of our algorithms.

关键词： Job shop scheduling Transforms approximation algorithms Reliability engineering Numerical simulation Real-time systems Spatiotemporal phenomena

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Motion Planning for Object Manipulation by Edge-Rolling

Motion Planning for Object Manipulation by Edge-Rolling

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Maede Boroji Vahid Danesh Imin Kao Amin Fakhari Department of Mechanical Engineering Stony Brook University Stony Brook NY USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

A common way to manipulate heavy objects is to maintain at least one point of the object in contact with the environment during the manipulation. When the object has a cylindrical shape or, in general, a curved edge, not only sliding and pivoting motions but also rolling the object along the edge can effectively satisfy this condition. Edge-rolling offers several advantages in terms of efficiency and maneuverability. This paper aims to develop a novel approach for approximating the prehensile edge-rolling motion on any path by a sequence of constant screw displacements, leveraging the principles of screw theory. Based on this approach, we proposed an algorithmic method for task-space-based path generation of object manipulation between two given configurations using a sequence of rolling and pivoting motions. The method is based on an optimization algorithm that takes into account the joint limitations of the robot. To validate our approach, we conducted experiments to manipulate a cylinder along linear and curved paths using the Franka Emika Panda ***— https://***/MX1-MAR9ubc

关键词： Shape Fasteners approximation algorithms Planning Optimization Intelligent robots

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Using Two Colour Necklaces to Fairly Allocate Coalition Value Calculations

Using Two Colour Necklaces to Fairly Allocate Coalition Valu...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Terry R. Payne Luke Riley Katie Atkinson Paul Dunne University of Liverpool Liverpool UK Quant London UK

ISBN: (数字)9798331504946

ISBN: (纸本)9798331504953

One of the challenges in forming coalitions within characteristic function games is in determining a suitable strategy for distributing coalition value calculations across a community of agents. The formation of coalitions of agents typically requires a quantitative assessment of the synergy resulting from the collaboration of different agents; however, the number of coalitions increases exponentially with the number of agents available. Although some approaches have been proposed that reduce this search space through approximation, several approaches adopt an exhaustive search by allocating subsets of calculations across different agents. The properties of these approaches can differ, and may result in uneven or redundant allocations. In this paper, we show how Combinatorial Necklaces of beads in two colours can be used to generate canonical sequences for determining coalition value calculation distributions. By using these sequences, coalitions can be allocated to those agents that appear in them, as well as balancing the computational load approximately evenly (with respect to the number of coalition allocation calculations and number of operations) across the agents. Furthermore, such necklaces can be generated simply and efficiently with algorithms that have been proven to generate all necklaces, for a given size $(N)$ and set of colours $(k)$ in constant amortized time or CAT, i.e. where the total time is $O(N_{k}(n))$ .

关键词： Collaboration Color Games Prediction algorithms approximation algorithms Encoding Resource management Intelligent agents

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Solving Ordinary Differential Equations of First and Second Order Using a Single Numerical Algorithm with Four Equidistant Points

Solving Ordinary Differential Equations of First and Second ...

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Science, Engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Bankola Gbenga Ogunware Ezekiel Olaoluwa Omole Adefunke Bosede Familua Peter Onu Ridwanulahi Iyanda Abdlganiy Femi Emmanuel Amoyedo Kehinde Peter Ajewole Patrick Moses Edoma Department of Mathematics and Statistics Joseph Ayo Babalola University Ikeji - Arakeji Nigeria Department of Physical Sciences Mathematics Programme Landmark University Omu-Aran Nigeria Department of Mathematics First Technical University Ibadan Oyo State Nigeria Department of Mechanical Engineering (Mechatronics) Landmark University Omu-Aran Nigeria Distant Learning Institute University of Lagos Lagos State Nigeria Department of Statistics Federal University of Technology Akure Ondo State Nigeria

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

This paper investigates a distinct numerical algorithm for the solution of first and second orders initial value problems. The new method was developed using interpolation and collocation approach, with power series approximate solution used as interpolating polynomials. The numerical integrators of the block were obtained by evaluating the non-interpolation points within the chosen integration interval. To assess the efficiency of the proposed block method, it was tested on some first and second orders ordinary differential equations with initial value problems, and the results produced outperformed existing methods in terms of accuracy.

关键词： Interpolation Accuracy Ordinary differential equations approximation algorithms Polynomials Sustainable development Business

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DDPG Algorithm with Elastic Replay Buffer Assisting in the Optimization of the NOMA System

DDPG Algorithm with Elastic Replay Buffer Assisting in the O...

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Intelligent Computing and Human-Computer Interaction (ICHCI), International Conference on

作者： Wenjing Zheng JingHan Wang Wenwen Fu Jun Li Fei Lin Xuehan Zheng He Gao School of Information and Automation Qilu University of Technology (Shandong Academy of Sciences) Jinan China School of Information and Electrical Engineering Shandong Jianzhu University Jinan China Shandong Zhengchen Technology co. LTD Jinan China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

Non-orthogonal multiple access networks inspired by cognitive radio technology can enhance energy efficiency and address the issue of spectrum resource scarcity. However, resource allocation strategies are still needed for optimization. This paper applies deep reinforcement learning (DRL) algorithms to optimize transmission strategies. We propose a DDPG algorithm integrated with elastic experience replay, which helps the agent strike a better balance between exploring new strategies and utilizing existing experiences. Simulation results demonstrate that the proposed algorithm achieves a higher transmission rate compared to the standard DDPG algorithm, random algorithm and greedy algorithm.

关键词： Training Fading channels NOMA Heuristic algorithms Simulation Storage management approximation algorithms Resource management Optimization Time-varying systems

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Qpopss: Query and Parallelism Optimized Space-Saving for Finding Frequent Stream Elements

SSRN

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SSRN 2024年

作者： Jarlow, Victor Stylianopoulos, Charalampos Papatriantafilou, Marina Dept. Computer Science and Eng. Chalmers Un. of Technology and Un. of Gothenburg Gothenburg Sweden R&D Dept. AstaZero Gothenburg Sweden emnify Berlin Germany

The frequent elements problem, a key component in demanding stream-data analytics, involves selecting elements whose occurrence exceeds a user-specified threshold. Fast, memory-efficient Ε-approximate synopsis algorithms select all frequent elements but may overestimate them depending on Ε (user-defined parameter). Evolving applications demand performance only achievable by parallelization. However, algorithmic guarantees concerning concurrent updates and queries have been overlooked. We propose Query and Parallelism Optimized Space-Saving (QPOPSS), providing concurrency guarantees. The design includes an implementation of the Space-Saving algorithm supporting fast queries, implying minimal overlap with concurrent updates. QPOPSS integrates this with the distribution of work and fine-grained synchronization among threads, swiftly balancing high throughput, high accuracy, and low memory consumption. Our analysis, under various concurrency and data distribution conditions, shows space and approximation bounds. Our empirical evaluation relative to representative state-of-the-art methods reveals that QPOPSS’s multi-threaded throughput scales linearly while maintaining the highest accuracy, with orders of magnitude smaller memory footprint. © 2024, The Authors. All rights reserved.

关键词： approximation algorithms

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Fast MLE-Based Device Activity Detection for Massive Grant-Free Access via PSCA and PSCANet

Fast MLE-Based Device Activity Detection for Massive Grant-F...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Bowen Tan Ying Cui IoT Thrust HKUST (GZ) Guangzhou China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Fast and accurate device activity detection is the critical challenge in grant-free access for supporting massive machine-type communications (mMTC). The state-of-the-art methods have an unsatisfactory error rate or computation time. To address these outstanding issues, we propose new maximum likelihood estimation (MLE)-based device activity detection methods that achieve superior tradeoffs between the error rate and computation time using optimization and deep learning techniques. Specifically, we propose an innovative parallel successive convex approximation (PSCA) algorithm for solving the noncon-vex MLE problem. We show that it allows parallel computations, uses up to the objective function’s second-order information, converges to the problem’s stationary points, and has a low per-iteration computational complexity compared to the state-of-the-art algorithms for the MLE problem. Then, we propose a PSCA-driven deep unrolling neural network implementation, called PSCANet, to reduce the overall computation time of PSCA. PSCANet elegantly marries PSCA’s parallel computation mechanism with the parallelizable neural network architecture and effectively optimizes its step sizes based on vast data samples. Numerical results demonstrate that PSCA and PSCANet can significantly reduce the error rate and computation time compared to the state-of-the-art methods, revealing their significant values for mMTC in 5G and beyond.

关键词： Maximum likelihood estimation Accuracy Error analysis 5G mobile communication Neural networks Computer architecture approximation algorithms Linear programming Computational complexity Optimization

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Exploration of Flavor Sample for Odor Reproduction In Mass Spectrum Space

Exploration of Flavor Sample for Odor Reproduction In Mass S...

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IEEE SENSORS

作者： Hanqing Zhao Dani Prasetyawan Takamichi Nakamoto Institute of Innovative Research Tokyo Institute of Technology Yokohama Japan

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Olfaction is one of the important senses. In particular, we often sniff food smells. In this study, we used mass spectrometry data of food to search for approximating odor reproduction recipes for odor components. We used principal component analysis, Nonnegative Matrix Factorization and Non-negative Least Squares algorithms for the analysis of 100 food samples. In particular, we analyzed 20 component odor recipes, Through the experimental results, the 20 odor components recipe is able to approximate the target odor with appropriate accuracy.

关键词： Accuracy Mass spectroscopy approximation algorithms Sensors Principal component analysis

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Method of Successive approximations for Optimal Control under Uncertainty of Initial Data: An Interval Approach

Method of Successive Approximations for Optimal Control unde...

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International Conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Sofia Mustafina Elvira Gizzatova Tatiana Mikhaylova Department of Mathematical and Computer Modeling Ufa University of Science and Technology Ufa Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

This article discusses the development of an interval algorithm based on the method of successive approximations for solving optimal control problems under uncertainty of initial data. To achieve this goal, interval analysis methods are applied, allowing for the consideration of variations in system parameters. A numerical implementation of the algorithm is provided, along with a description of a computational experiment using a model example. The results demonstrate that the proposed method can construct confidence intervals for the solutions to the optimal control problem, making it useful for practical applications in situations with uncertainty in initial parameters.

关键词： Uncertainty Computational modeling Decision making Optimal control Process control approximation algorithms Mathematical models Energy efficiency Numerical models Reliability

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Federated Reinforcement Learning for Resource Allocation in V2X Networks

Federated Reinforcement Learning for Resource Allocation in ...

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IEEE Conference on Vehicular Technology (VTC)

作者： Kaidi Xu Shenglong Zhou Geoffrey Ye Li Department of Electrical and Electronic Engineering Imperial College London London UK The School of Mathematics and Statistics Beijing Jiaotong University Beijing China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

Resource allocation significantly impacts the performance of vehicle-to-everything (V2X) networks. Most existing algorithms for resource allocation are based on optimization or machine learning (e.g., reinforcement learning). In this paper, we explore resource allocation in a V2X network under the framework of federated reinforcement learning (FRL). On one hand, the usage of RL overcomes many challenges from the model-based optimization schemes. On the other hand, federated learning (FL) enables agents to deal with a number of practical issues, such as privacy, communication overhead, and exploration efficiency. The framework of FRL is then implemented by the in-exact alternative direction method of multipliers (ADMM), where subproblems are solved approximately using policy gradients and their second moments. The developed algorithm, FRLPGiA, has a nice numerical performance compared with some baseline methods for solving the resource allocation problem in a V2X network.

关键词： Training Vehicular and wireless technologies Privacy Machine learning algorithms Federated learning Reinforcement learning approximation algorithms

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