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MULTI-INDUSTRIAL APPLICATIONS OF CLOUD AND INTELLIGENT EDGE computing IN SMART CITIES 4

MULTI-INDUSTRIAL APPLICATIONS OF CLOUD AND INTELLIGENT EDGE ...

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4th international conference on Distributed Sensing and Intelligent Systems, ICDSIS 2023

作者： Kiran, P.B. Narendra William, P. Ogudo, Kingsley A. Khalaf, Osamah Ibrahim Lovely Professional University Jalandhar Phagwara Punjab Delhi India Department of Information Technology Sanjivani College of Engineering Savitribai Phule Pune University Pune India Depending of Electrical and Electronics Engineering FEBE University of Johannesburg Johannesburg South Africa Department of Solar Al-Nahrain Research Center for Renewable Energy Al-Nahrain University Jadriya Baghdad Iraq

ISBN: (纸本)9781839539954

This research examines how cloud and intelligent edge computing are affecting smart city physical environments. This shows how these technologies might transform urban life. Cloud and intelligent edge computing may improve urban life and sustainability. These applications are useful across sectors. Integrating centralized cloud resources with decentralized edge devices makes these applications operational. This technology may make cities more livable and environmentally friendly. This article focuses on how recent technological breakthroughs are affecting transportation, healthcare, energy management, and public safety. The combination of edge and cloud computing makes smart cities feasible and accessible. These cities are efficient, adaptive, and environmentally conscious. The convergence's environment will spur technology and urban innovation, which will change how people live in cities in the future. Additionally, these qualities will create an environment that encourages urban planning and technological innovation. This research examines the benefits of cloud and intelligent edge computing for various enterprises. These technology advances are affecting several industries, including public safety, energy management, transportation, and healthcare. This article devotes a lot of attention to each of these specific areas. This study shows the necessity of communication protocols and standards and how to use them by offering a step-by-step strategy for data collection, analysis, and interpretation. We will focus on message fundamentals and network operation throughout the study. The results show that smart edge and cloud computing in smart cities increase energy efficiency, sustainability, and mobility. © The Institution of Engineering & technology 2023.

关键词： Sustainable city

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UAVs-Assisted Edge Networks Optimization Based on Constrained Particle Swarm Algorithm 23

UAVs-Assisted Edge Networks Optimization Based on Constraine...

引用

23rd IEEE international conference on Communication technology, ICCT 2023

作者： Zhang, Lei Wen, Fangqing Li, Xudong Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang China College of Computer and Information Technology China Three Gorges University Yichang China

ISBN: (纸本)9798350325959

The mobility of unmanned aerial vehicles (UA Vs) has attracted widespread attention in mobile edge computing (MEC). Due to limitations in UAVs communication capacity and onboard power, the performance of UA Vs-assisted MEC networks faces significant challenges. To address this, this paper constructs a multi-objective optimization model for a UAVs-assisted MEC networks and derives multi objective functions that characterize network performance, including capacity, energy consumption, and latency. Furthermore, a constraint particle swarm optimization algorithm with low computational complexity is proposed. This includes designing a multi-objective evaluation strategy that balances diversity and convergence, as well as an adaptive constraint handling mechanism for managing constraints. Finally, the proposed algorithm is used to simultaneously optimize the capacity and energy consumption while meeting the requirements of UAVs computational resources and user task latency. Experimental results demonstrate that our algorithm can significantly reduce energy consumption while enhancing capacity and transmission rate, without significantly increasing algorithm complexity. © 2023 IEEE.

关键词： mobile edge computing particle swarm optimization UAVs communication

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A simulated annealing genetic algorithm based on reinforcement learning for flexible job shop scheduling problem

A simulated annealing genetic algorithm based on reinforceme...

引用

2023 international conference on Algorithms, High Performance computing, and Artificial Intelligence, AHPCAI 2023

作者： Wang, Yuqing Zhao, Dequn Ma, Hongwei Zhang, Suming Deng, Qianhua Faculty of Information Technology Beijing University of Technology Beijing China Beijing Institute of Astronautical Systems Engineering Beijing China China Telecom Group Beijing China

ISBN: (纸本)9781510671881

The flexible job-shop scheduling problem surpasses the limitations of conventional workshop scheduling problems that reduce machine constraints, increase uncertainty, and belong to the NP-hard problem. An adaptive simulated annealing genetic algorithm based on reinforcement learning is put forward to overcome the constraints of complex parameter determination and poor local search capabilities that standard genetic algorithms face when dealing with flexible job shop scheduling. The approach uses a multi-parent POX crossover operation and introduces a simulated annealing algorithm into the mutation operation to enhance the method's capability for both global and local optimization in the evolution process. The tournament method is combined with the optimal strategy to ensure the algorithm's convergence. The crossover and mutation parameters are dynamically adjusted and optimized using the reinforcement learning algorithm in conjunction with the improved simulated annealing genetic algorithm so that the parameters of the algorithm can adapt to the evolution process according to experience, and the searchability and computational efficiency of the algorithm are improved. By testing and examining the common examples, the proposed algorithm's rationality and superiority are ultimately demonstrated. © 2023 SPIE. All rights reserved.

关键词： Genetic algorithms

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A Functional Link-based Volterra Equalizer for 112Gbps O-band PAM-4 Optical systems 15

A Functional Link-based Volterra Equalizer for 112Gbps O-ban...

引用

15th international conference on Information Optics and Photonics, CIOP 2024

作者： Xu, Tongkai Hao, Chunling Yin, Kun Shi, Yanhui Chen, Chen Hu, Chuliang Zhejiang Lab Hangzhou311121 China Institute of Innovative Computing Technology CAS Hangzhou310015 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

Intensity Modulation and Direct Detection (IMDD) technology, with its low latency, low power consumption, and high throughput advantages, has emerged as the preferred solution for high-efficiency data transmission and exchange between large-scale computing clusters. Digital Signal Processing (DSP) technology can further enhance IMDD transmission performance by compensating for transmission impairments. In this paper, we propose a Functional Link-based Volterra equalizer (FL-Vol) that combines the Functional Link Artificial Neural Network (FLANN) and the Volterra equalizer (Vol). The FL-Vol demonstrates superior nonlinear characterization capabilities, benefiting from higher-order terms in the extended basis functions and cross terms in the Vol. We select the classical Least Mean Square (LMS) criterion for self-adaptive parameter iteration and utilize a variable step-size algorithm based on a modified sigmoid function to balance the rate of convergence and steady-state error. We validate the equalization performance of FL-Vol through a single lane 112Gbps O-band PAM-4 IMDD transmission experiment. Our performance comparison of these equalizers reveals that the 2nd-FL-Vol offers up to a 2dBm improvement in equalization performance with similar computational complexity compared to the 2nd-Vol. Furthermore, the 2nd-FL-Vol reduces computational complexity by approximately 30% while maintaining similar equalization performance compared to the 3rd-Vol. Notably, despite the theoretical advantage of the 3rd-Vol structure in nonlinear characterization, the 2nd-FL-Vol consistently outperforms the 3rd-Vol, especially at higher received optical powers. Additionally, as expected, the variable step-size algorithm improves the performance of all equalizers. © 2024 SPIE.

关键词： Equalizers

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Transforming Workspaces: The convergence of Li-Fi, FTTO, and PoE 8th

Transforming Workspaces: The Convergence of Li-Fi, FTTO, and...

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8th international conference on Information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Sridhar, Nidhi Neha, S. Mallikarjunaiah, Devanth Nadiger, Niranjan M. Venugopal, N. Department of Electrical and Electronics PES University Karnataka Bengaluru560085 India

ISBN: (纸本)9789819766741

The seamless integration of technology is crucial in today's workplace to improve occupant comfort, productivity, and efficiency. A high-bandwidth, low-latency connectivity option that can handle a variety of data-intensive applications is provided by Fiber to the Office (FTTO). FTTO can be integrated with Light Fidelity (Li-Fi), Power-over-Ethernet (PoE), building management system (BMS), and BMS integration systems to further improve building operations, create a ubiquitous wireless network, and offer power and data delivery to linked devices with a single cable. The paper (Jamil and Mittal, 14th IEEE India Council international conference (INDICON), pp. 1–6, 2017) reviews building energy management systems (BEMS), computer-based control systems designed to regulate and optimize the energy use of buildings. An overview of BEMS and its importance for improving energy efficiency and reducing energy costs is given in the study's introduction. The paper (Shailesh in 4th international conference on Applied and Theoretical computing and Communication technology (iCATccT), pp. 193–194, 2018) introduces the idea of energy-efficient LED lighting based on Power-over-Ethernet (PoE) technology. The authors argue that PoE technology can provide a more efficient and flexible alternative for powering LED lighting systems than traditional AC power systems. It also discusses the possible benefits of using PoE technology for LED lighting systems, such as increased lighting management flexibility, reduced maintenance costs, and increased energy efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Fiber to the x

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Locally Linear Embedding Based on Gannet Optimization Algorithm 4

Locally Linear Embedding Based on Gannet Optimization Algori...

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4th IEEE international conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Zhu, Yiqi Yang, Yang Fang, Yilin Nai, Wei Yang, Zan Li, Dan Huzhou College School of Electronic Information Huzhou China Huzhou College Huzhou Key Laboratory for Urban Multidimensional Perception and Intelligent Computing Huzhou China Huzhou College Public Teaching and Research Department Huzhou China

ISBN: (纸本)9798350363586

The analysis and feature extraction of high-dimensional data can help people solve various problems in current industry applications, and manifold learning is a type of data dimensionality reduction method developed based on the concept of topological manifolds. Locally linear embedding (LLE) algorithm, as a classic manifold learning algorithm, has attracted much attention due to its low computational complexity and strong scalability. However, the objective function of LLE algorithm may contain absolute value terms and cannot be guaranteed to be convex. Traditional derivative dependent solving methods are difficult to obtain its optimal solution, making it impossible to achieve effective feature extraction of data. In this paper, an LLE based on gannet optimization algorithm (GOA) has been proposed, and it is supposed to be used as a derivative-free optimization method to effectively solve the problems of non-differentiable of non-convex objective function, premature convergence, and easy to fall into local optimum in the process of solving the objective function of LLE. © 2024 IEEE.

关键词： Optimization algorithms

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convergence of APCARD and RFID for Attendance System

Convergence of APCARD and RFID for Attendance System

引用

2022 IEEE international conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2022

作者： Jun Jie, Ho Aysa Abdul Halim Sithiq, Hairul Azlina Abd Rahman, Nor Asia Pacific University of Technology and Innovation Technology Park Malaysia

ISBN: (纸本)9781665483162

Attendance plays an important role in education. Lecturers can use it to track the academic progress of their students. Admin and non-academic staff can ensure that international students are attending classes, complying with the law when in another country. Hence, an RFID based attendance is to be made for APU students, where students are required to have a minimum 80% of attendance to pass their modules. This research aims to intend to develop an attendance-based system using the RFID chip embedded in every APIIT student's APCard. This system helps in reducing human error, fake attendances, and the students' attendance in classes can be generated for analytical purposes. © 2022 IEEE.

关键词： Students

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Tasks classification across edge servers nodes using K-means with multi-objective constraints Chebyshev distance 15

Tasks classification across edge servers nodes using K-means...

引用

15th international conference on Innovations in Information technology, IIT 2023

作者： Ayat, Imene Mechta, Djamila Harous, Saad Farhat Abbas University Setif1 Department of Computer Science Setif Algeria University of Sharjah Department of Computer Science Sharjah United Arab Emirates

ISBN: (纸本)9798350382396

Edge computing provides benefits such as reduced latency by processing data closer to its source, but it faces challenges due to limited processing power, memory, and storage capacity. To address these limitations and enhance system efficiency, task classification becomes crucial in edge computing. By categorizing tasks, resources can be allocated effectively. This paper presents a novel approach for classifying tasks and edge servers based on CPU and memory capacities. The proposed model treats tasks and edge servers as points and applies the K-means method by adding multi-objective constraints Chebyshev distance. The distance metric considers two objectives: The distance between points and the number of tasks and edge servers. Unlike traditional K-means algorithms that often result in clusters with either one server or clusters without servers, our model ensures that nearly every cluster contains at least one server. Simulation results demonstrate the fast convergence of the proposed model, evaluated through clustering using inertia and silhouette coefficient. It is important to note that this classification does not directly influence task scheduling or resource allocation processes. Instead, it serves as a preliminary step to improve the effectiveness of these subsequent processes. By strategically placing more powerful tasks on higher-capacity servers, and vice versa, our approach aims to reduce the workload of the scheduler and enhance resource allocation or task scheduling. This classification framework has the potential to achieve efficient task and resource management in edge computing environments. © 2023 IEEE.

关键词： Edge computing

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Robust Variable Structure PID Controller for Two-Joint Flexible Manipulator 7th

Robust Variable Structure PID Controller for Two-Joint Flexi...

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7th international conference on computing, Control and Industrial Engineering, CCIE 2023

作者： Long, Yecheng You, Jia Huang, Yiyang Chen, Zhenliang Shi, Mengxin Zhuhai Power Supply Bureau of Guangdong Power Grid Corporation Zhuhai519000 China Shenzhen Aerospace Science and Technology Innovation Research Institute Shenzhen518063 China School of Aerospace Science and Technology Xidian University Xi’an710126 China

ISBN: (纸本)9789819927296

In order to deal with the low convergence rate issue of the classical control method in the control problem of double-joint flexible manipulator, a variable structure PID control method is proposed. This method improves the convergence rate of the system by designing the control parameters under the premise of maintaining the advantages of simple structure and strong robustness of the classical PID controller. The variable structure dynamic control parameters are introduced to realize the improvement of the convergence rate along the sliding mode motion of the designed uniform speed section when the system state is far away from the equilibrium point;the integral isolation algorithm is introduced to avoid the decrease of the convergence rate caused by the premature introduction of the integral term and improve the steady-state accuracy. Finally, the system stability is analyzed by Lyapunov stability theory, and the proposed method is verified by physical simulation. The results show that the method proposed in this paper improves the convergence time by more than 80% compared with the classical PID control method, while maintaining the same steady-state accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Three term control systems

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Deep Reinforcement Learning Based Computation Offloading in SWIPT-assisted MEC Networks 31

Deep Reinforcement Learning Based Computation Offloading in ...

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31st international conference on Computer Communications and Networks (ICCCN)

作者： Wan, Changwei Guo, Songtao Yang, Yuanyuan Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

Computation offloading is an effective method to relieve user equipment (UE) from the limited battery capacity and computation resource in mobile edge computing (MEC) networks. However, it is challenging to obtain offloading strategy timely and accurately under diverse computation task requirements and changeable network channel states in multi-user and resource-constrained network environment. In this paper, we consider the network dynamics and UE's resource constraints and aim to minimize the energy consumption of all UEs by jointly optimizing the offloading decision, the central processing unit (CPU) frequency and the power split ratio in a dynamic MEC network. To be specific, we introduce simultaneous wireless information and power transmission (SWIPT) technology in MEC networks to prolong UE's operation time. More importantly, we propose an online computation offloading algorithm based on deep deterministic policy-gradient (DDPG), named Enhanced DDPG (EDDPG), to solve the energy consumption minimization problem. In particular, EDDPG can make real-time decisions without complete network information and adapt to time-varying environments and different requirements. Furthermore, we introduce the priority experience replay technology in EDDPG to accelerate the convergence by using experience tuples. Simulation results show that our proposed algorithm can effectively reduce the energy consumption of UEs and enable them complete more computing tasks within the time limit. Compared with other baseline methods, it can accelerate the convergence and improve the system performance effectively.

关键词： Computation offloading Mobile edge computing Deep reinforcement learning Wireless information and power transmission Energy consumption

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